Video - Visualizing Vector Data (Part 2): Rule-Based Visualizations and Labelling

Catalogue number: Catalogue number: 89200005

Issue number: 2020010

Release date: November 19, 2020

QGIS Demo 10

Visualizing Vector Data (Part 2) - Rule-Based Visualizations and Labelling - Video transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Visualizing Vector Data (Part 2) - Rule-Based Visualizations and Labelling")

Welcome back everyone. So following up from Part 1 of Visualizing Vector Data where we explored the application of symbology styles to different field types.

Today we'll apply rule-based visualizations, including both symbologies and labelling schemes. These styles can be used to assign different visualization parameters to features in a layer based on their attributes, such as using different fields, symbols or formatting for visualization. We'll use the rules to create a scale-dependent visualization of feature classes in the CPRoads layer.

Additionally, we'll discuss the use of available symbology file formats and how to load them to vector datasets. This will enable you to rapidly visualize datasets, including those in other locations or collection periods that share the same parameters, as well as share your visualization styles with others.

We'll conclude with additional labelling procedures, such as developing multi-field and conditional labelling expressions.

Double left click the CPRoads layer to open the Layer Properties box. In the Symbology tab, we'll begin by applying a Categorized style to the Class field created in the Field Calculator demo and click Classify to add them to the tab. The Categorized style is being used to establish the Symbol and Legend Values prior to switching to the Rule-Based style.

We can left-click and drag to reorder classes in the tab. We'll place them in ascending order to ensure that larger classes do not obscure the visualization of smaller classes. With them in Ascending order, we can now select Recreational through Arterial, holding shift between left-clicks, then right-click and select Change Colour – which we'll alter to Black. Repeating with the Ramps and Highways class, we'll alter the colour to Red. And just like the Graduated Symbology applied to grain elevators in the previous demo, we'll adjust the line widths for each class, double-left clicking to open the Symbol Selector. For Lane we'll apply a width of 0.2, Local a width of 0.3 and Collector a width of 0.8. Then we can select Arterial and Ramp together and edit the line widths to 1. Finally for our Highways class we can use a width of 1.5.

So with the visualization and legend values established now we can switch to the rule-based style. This will add a few additional parameters including Rule, Min and Max Scale columns. Select an entry and click on the Pencil icon or double left click it to open the Edit Rule box. Here we'll replace current rules with the original expressions used to create the Class field.And this is so we can apply the visualization not only to the CPRoads layer but to the original Road_Segments layer in Manitoba as well as those in other provinces that have the same visualization parameters. Clicking the Expression box, we'll replace the rule with "road_class" > 316 AND "road_class" < 321 for the Recreational class. And we'll copy the last component of the expression for parametrizing our other classes. Clicking OK. Check the Scale Range box. And for the Minimum scale, beyond which visualization is suspended, select 50,000 from the drop-down. We'll set the Maximum scale to 0, as we do not want to suspend rendering as we zoom in further.

Optionally, we can also single left click to edit rules in-situ within the symbology tab. So Lane classes corresponded to values of 307 OR 321. And we'll enter 100,000 for the minimum scale. I'll enter the remaining expressions and minimum scale values, specified in the video description.

So now we can click Apply and OK and take a look at our dynamic visualization of different road classes. With the current scale slightly greater than 1 in 1 million, all we can see is our highways. But zooming in slightly further, the Collector and Arterial classes appear, and even further the Lane and Local classes.

Now let's select the rules from the Symbology tab, copy using Ctrl C, and then Paste them into the Labels tab after selecting Rule-Based from the drop-down. For both the Symbology and Labels tab we can add new rules using the plus icon and parametrize them in the Edit Rule box. Individual rules can also be suspended by toggling them off or completely removed with the minus icon. We'll remove our Recreational and Ramp classes for labelling. We still need to open the edit rule box for each entry, first to check the Label box feature and specify the field used in labelling. Additionally, we will want to apply smaller minimum scale values for our labels.

So double-left clicking the Lane class, check the Labels box and select "official_s" field from the drop-down. This will label our features by the full road name. Copy the label field, which we'll paste for our other classes. So, we'll increase the text size by 1 in ascending order, so for Lane leave the default size of 10. We'll apply text buffers that match the line widths applied to each class back in the rule-based symbology. And for the Placement, there is a variety of options which vary between vector geometry types. For Local and Lane Classes we'll use Curved – the others using Parallel, and for all classes we'll switch Placement from Above to On Line. We can specify the Maximum Angle between characters at the bottom of the tab. Finally we'll alter the minimum scale to 1 in 50,000 for our Lane class. I'll parametrize the remaining classes and then we'll restart. As noted we can also use the rule-based style to apply different fields in visualization. So, for our Highway class, lets use the Route_Numb field. Change the Font Size to 14. Instead of a text buffer we'll apply a text-background, selecting Ellipse from the Shape drop-down and applying a buffer of 0.5 around the text. Change the fill colour to blue and the outline to red, with a width of 0.25. Finally, as specified earlier change the Placement from Above to On Line. Now let's examine the visualization.

So as we can see, there's many repeating labels, since it's a roads segments file – where each line between junctions is a separate entry in the attribute table. And this results in a messy appearance. Therefore, there are two options – in the Rendering tab, scrolling down to the bottom we can select Merge Connected Lines to Remove Duplicate labels. This will remove most repeating labels. Alternatively we can use the Dissolve Tool and select the "official_s" field, which will combine roads with the same name into one feature. So we'll use the Dissolve tool to ensure that all duplicates are removed. Multiple fields can be specified for Dissolving as needed, such as ensuring that different roads with the same name are not combined.

Rather than re-entering the rules for our Dissolved layers, simply copy and paste the style from the CPRoads layer. Use All Categories to ensure that both the symbology and labels are retained. So this enables rapid visualization between layers so long as they are of the same geometry type and share the same visualization parameters. If we decided we only want to apply labelling or symbology scheme, the visualization parameters can also be specified when pasting.

So toggling the Dissolved layer on and CPRoads off , we can see that all duplicates have been removed – significantly improving the visualization. Zooming in further we can begin to see our curved labels for the Lane and Local classes.

So now let's discuss the symbology styles for saving our visualizations. There are a few file formats available in QGIS with different uses. The two main types for vectors are under the Export options.

The first is the Layer Definition File or .qlr. This format is explicitly tied to the source dataset. So save the file in the same directory as the source layer. And the definition file can then be loaded directly into QGIS. Simply double-left click to load it in to the Layers Panel with the pre-defined visualization parameters, including both the symbology and labels. The same should apply when loading the source layer. For this layer I used the Merge Connected Lines in the Labels Rendering sub-tab. Zooming out we can see that most, but not all duplicates have been removed.

The second format, the QGIS Layer Style File or .qml, is similar. It saves the visualization parameters but is not tied to the source dataset. Thus, it is helpful for sharing visualizations with others, or applying created visualizations to the same dataset in a different location or time period. To load this file go in to the Layer Properties box, click the Style tab and Load Style. The specific visualization parameters can be specified in the Categories box. Then locate and load it from directory. We can copy and paste the style to the Ontario Road Segments file. And now the visualization is applied across Manitoba and Ontario, with the dynamic rendering as we zoom in and out. So this underscores the utility of these visualization files.

Within the Symbology tab we can also save edited or created colour ramps. This format is not tied to any layer. But, saved colour ramps can be accessed from the Color Ramp drop-down. For example, I inverted the Spectral colour ramp and saved it as a Temperature colour ramp with Add to Favorites checked, meaning it's immediately accessible in the first Colour Ramp drop-down. I also saved the Heat Map style from our Grain Elevators layer in the previous demo, with Favourites unchecked, so it's in the expanded All Colour Ramps side-bar.

Now for the final component let's use expression syntax to generate multi-field labels and conditional labelling schemes. For the first we'll select the Grain Elevators layer and open the Field Calculator.

We'll provide the name MFLabel for the field name, change the type to text with a length of 100. Expand the Fields and Values drop-downs to see the available fields. Now we can enter generic text components with single quotes, staring with Oper colon space closed quote for the rail operator. Then use the two vertical dash lines (||) to separate different components of the expression, here adding the Railway field. Adding the separators again, single quote and hit Enter twice, and then type Co – colon - space and close quote, followed by the separators and the Company_Consolidated field. Finally, we'll add a comma and a space enclosed by single quotes, then the separators and the PR field. We can now see an example of the label in the Preview output.

So now open the Layer Properties box, and in the Labels tab select Single Labels and then the MFLabel field at the bottom of the drop-down. Once again we can specify a text-size and a buffer. In the Placement tab, we'll set where the labels should be placed, which as noted varies between geometry types. Cartographic could be used for mapping but may increase rendering times. Here we'll use the Offset from Point and specify the Centre. Based on the spacing in our label, this should place our label above and below the points. For the Rendering tab add a minimum scale of 1 in 500,000, then click OK.

Zooming in beyond the Minimum Scale value, our multi-field labels appear for each elevator – indicating the railway operator, company and abbreviated province. This can be reapplied to any layers, fields and vector geometry types to provide key information in labelling.

Now let's explore conditional labelling, used to label features with certain criteria or specified attributes. Toggle on and open the CPRoads' Layer Properties Box and switch to Single Labels. Click the Expression button beside the Label. And expanding the Conditionals drop-down double-left click CASE, and examine the syntax on the right. So once it's added to the Expression box, we can now specify the criteria or conditions. In general, its CASE WHEN, then you need to specify the conditions, what to do when the conditions are satisified, and what to do otherwise, adding ELSE. Here we'll use the Class field and the IN operator, adding Arterial, Collector and Highway classes to label our major road features. Now we need to specify the labelling field after THEN, selecting route_num from the Fields and Values drop-down. Finally we need to specify what to do with the other features, after ELSE we can add NULL. Now we can click Apply and OK.

Though all of our Highway features are now labelled by their route numbers. However, the Collector and Arterial roads are not labelled since they lack route numbers. So lets add another conditional expression, an IF statement, to the label after THEN. So the format for IF statements is specifying the criteria, then entering what to do when it's true, followed by what to do if it's FALSE separated by commas. So here we'll specify if the Route Number is NOT NULL, label by the Route Number, otherwise use the Speed_Rest field – which we populated in the Field Calculator demo.

So now all of our specified classes are being labelled. This is not a particularly aesthetically pleasing visualization, but does demonstrate that we can use expressions to specify the attributes or conditions for which labels should be generated. Further, we can nest expressions within one another to ensure the specific attributes and label parameters of interest are used. Apply these expression skills to other datasets in specifying the conditions and attributes to use.

In this demo, we covered rule-based symbologies and labelling schemes. We also learned how to copy and paste styles, as well as save and load symbology files to rapidly visualize vector datasets. Finally, we explored labels in greater detail including using expressions to create multi-field and conditional labelling schemes. Apply these skills for parametrizing, saving and sharing vector visualizations. These skills are fundamental to creating logical, easily interpretable visualizations and maps of spatial data. In the next tutorial we'll cover procedures for joining datasets by attributes, including one-to-one and one-to-many joins.

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Description of farm family income components

Total income: The sum of net operating income and off‑farm income of each taxfiling member of a family involved in a single farm, either a single unincorporated farm or a single incorporated farm.

Off-farm income: The sum of employment income, investment income, pension income, and total other income.

Employment income: The sum of wages and salaries and net non-farm self-employment income.

Wages and salaries: The sum of gross wages and salaries before deductions (including commission income) as per T4 slips, and other employment income such as tips and gratuities. Total wages and salaries also includes tax-exempt employment income earned on an Indian reserve.

Net non-farm self-employment income: Business income, professional income, commission income and fishing income, on a net basis. The net income is the amount reported after expenses and costs are deducted from the gross income.

Investment income: The sum of net rental income, net limited partnership income, the amount of dividends actually received from taxable Canadian corporations (excluding dividends received from the farming corporations), and interest and other investment income.

Pension income: Old Age Security pension, Canada or Quebec Pension Plan benefits, other pensions and superannuation, and net federal supplements. Since 2007, spouses or common-law partners may jointly elect to split pension income. To avoid double-counting, the amount reported by the pension transferee is not included in the estimates, as the full pension amount has been reported by the pensioner.

Total other income: The sum of government social transfers (excluding pension amounts) and other income.

Government social transfers (excluding pension amounts): Employment Insurance and other benefits, Workers' compensation benefits, social assistance payments, Canada Child Tax Benefit (CCTB), Universal Child Care Benefit (UCCB) and provincial family benefits. Both the CCTB and UCCB ended in June 2016 and were replaced by the Canadian Child Benefit (CCB).

Other income: Registered disability savings plan (RDSP) income, taxable amount of support payments received, items reported on line 130 of the T1 tax return such as scholarships, fellowships and bursaries, lump-sum payments from pensions and deferred profit-sharing plans received when leaving a plan, retiring allowances (severance pay), death benefits (other than CPP or QPP death benefits), withdrawals from AgriInvest account (Fund 2) by unincorporated operators, and other income (such as registered education savings plan income and training allowances). Registered retirement savings plan (RRSP) income of people aged 65 or older is also included.

Net operating income: The profit or loss of the farm operation measured by total operating revenues minus total operating expenses, excluding capital cost allowance or amortization of tangible assets, the value of inventory adjustments and other adjustments for tax purposes. The net operating income of the farm is multiplied by the family's share in the corporation or the partnership. The net operating income is also equal to the sum of net program payments and net market income.

Net program payment: Program payments and insurance proceeds after deducting stabilization levies or fees (government levies).

Net market income: Total operating revenues minus total operating expenses minus net program payments.

Total income adjusted for capital cost allowance (CCA) or amortization of tangible assets: The sum of net operating income adjusted for capital cost allowance or amortization of tangible assets and off-farm income of each taxfiling member of a family involved in a single farm, either a single unincorporated farm or a single incorporated farm.

Adjustment for capital cost allowance (CCA) or amortization of tangible assets: The amount of the adjustment for capital cost allowance or amortization of tangible assets.

Capital cost allowance (CCA): A tax term for depreciation used to define the portion of the cost of the depreciable property, such as equipment and buildings, that is tax-deductible. After the calculation of the capital cost allowance, farmers may deduct any amount up to the maximum allowable.

Amortization of tangible assets: Includes amortization of leasehold improvements and amounts referred to as depreciation. Depreciation is a term used to define the loss in value of an asset over its estimated life due to wear and tear and obsolescence.

Net operating income adjusted for capital cost allowance (CCA) or amortization of tangible assets: The net operating income minus the adjustment for capital cost allowance or amortization of tangible assets. The net operating income of the farm adjusted for CCA or amortization of tangible assets is multiplied by the family's share in the corporation or the partnership.

Net market income adjusted for capital cost allowance (CCA) or amortization of tangible assets: Total operating revenues minus total operating expenses including capital cost allowance or amortization of tangible assets minus net program payments.

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Persons using Real Time Remote Access (RTRA) may not use it for any other purpose except that which was agreed upon in the application.

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The annual subscription runs from April 1st to March 31st. Organizations can subscribe at any time of the year at a prorated fee.

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Data - RTRA

Administrative data

Statistics available – Frequencies

Canadian Cancer Registry (CCR)
Survey details
CCR 1992-2015
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CCR CCR 5 WEIGHT
  • PPROVBIR
  • PDPROVBIR
  • PDCOUNBIR
  • TPIN
  • TTRN
  • TPLACRES
  • TPOSTCOD
  • TCODPLAC
  • TCENTRAC
  • TMETHDIAG
  • TMETHUSED
  • TMETHCONF
  • PDATBIR
Canadian Emergency Response Benefit (CERB)
Survey details
CERB 2020
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CERB2020 CERB2020 10 WEIGHT
  • GEO_SOURCE
  • LOCAL
  • PCODE
  • PRCD
  • SACTYPE
  • CMA
  • CMACA
  • CTNAME
  • SGC
  • CSDTYPE
  • PRCDDA
  • EIER_REAE
  • PRER
  • NAICS_BR2019
  • ERB_ID
  • BUS_SIZE1
  • BUS_SIZE2
  • BUS_ID
  • CERB_EW1 to CERB_EW38
Canadian Survey on Business Conditions (CSBC)
Survey details
CSBC 2020 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2020Q2 CSBC2020Q2 10 CWEIGHT  
CSBC 2020 Quarter 3
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2020Q3 CSBC2020Q3 10 CWEIGHT  
CSBC 2021 Quarter 1
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2021Q1 CSBC2021Q1 10 CWEIGHT  
CSBC 2021 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2021Q2 CSBC2021Q2 10 CWEIGHT  
CSBC 2021 Quarter 3
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2021Q3 CSBC2021Q3 10 CWEIGHT  
CSBC 2021 Quarter 4
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2021Q4 CSBC2021Q4 10 CWEIGHT  
CSBC 2022 Quarter 1
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2022Q1 CSBC2022Q1 10 CWEIGHT  
CSBC 2022 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2022Q2 CSBC2022Q2 10 CWEIGHT  
CSBC 2022 Quarter 3
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2022Q3 CSBC2022Q3 10 CWEIGHT  
CSBC 2022 Quarter 4
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2022Q4 CSBC2022Q4 10 CWEIGHT  
CSBC 2023 Quarter 1
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2023Q1 CSBC2023Q1 10 CWEIGHT  
CSBC 2023 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2023Q2 CSBC2023Q2 10 CWEIGHT  
CSBC 2023 Quarter 3
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2023Q3 CSBC2023Q3 10 CWEIGHT  
CSBC 2023 Quarter 4
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2023Q4 CSBC2023Q4 10 CWEIGHT  
CSBC 2024 Quarter 1
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2024Q1 CSBC2024Q1 10 CWEIGHT  
CSBC 2024 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2024Q2 CSBC2024Q2 10 CWEIGHT  
CSBC 2024 Quarter 3
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2024Q3 CSBC2024Q3 10 CWEIGHT  
CSBC 2024 Quarter 4
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2024Q4 CSBC2024Q4 10 CWEIGHT  
CSBC 2025 Quarter 1
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2025Q1 CSBC2025Q1 10 CWEIGHT  
CSBC 2025 Quarter 2
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CSBC2025Q2 CSBC2025Q2 10 CWEIGHT  
Canadian Vital Statistics – Birth Database (CVSB)
Survey details
CVSB 2021
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSB2021 CVSB2021 5 WEIGHT
  • RESIDENCE_POSTALCODE
  • PLACEOFBIRTH_CENSUSDIVISION
  • PLACEOFBIRTH_CENSUSSUBDIVISION
  • BIRTH_DAY
  • MOTHER_BIRTH_DAY
  • FATHER_BIRTH_DAY
  • CERTIFICATION_DAY
CVSB 2023
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSB2023 CVSB2023 5 WEIGHT
  • RESIDENCE_POSTALCODE
  • PLACEOFBIRTH_CENSUSDIVISION
  • PLACEOFBIRTH_CENSUSSUBDIVISION
  • BIRTH_DAY
  • MOTHER_BIRTH_DAY
  • FATHER_BIRTH_DAY
  • CERTIFICATION_DAY
Canadian Vital Statistics – Death Database (CVSD)
Survey details
CVSD 2000
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2000 CVSD2000 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2001
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2001 CVSD2001 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2002
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2002 CVSD2002 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2003
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2003 CVSD2003 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2004
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2004 CVSD2004 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2005
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2005 CVSD2005 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2006
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2006 CVSD2006 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2007
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2007 CVSD2007 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2008
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2008 CVSD2008 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2009
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2009 CVSD2009 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2010
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2010 CVSD2010 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2011
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2011 CVSD2011 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2012
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2012 CVSD2012 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2013
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2013 CVSD2013 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2014
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2014 CVSD2014 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2015
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2015 CVSD2015 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2016
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2016 CVSD2016 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2017
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2017 CVSD2017 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2018
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2018 CVSD2018 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2019
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2019 CVSD2019 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2020
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2020 CVSD2020 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2021
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2021 CVSD2021 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2022
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2022 CVSD2022 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
CVSD 2023
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
CVSD2023 CVSD2023 5 WEIGHT
  • RECORD_STATUS
    REGISTRATION_NUMBER
    IMP090R
    IMP100R
    IMP110R
    IMP120R
    IMP140R
    PLACEOFDEATH_CITY
    PLACEOFDEATH_CENSUSDIVISION
    PLACEOFDEATH_CENSUSSUBDIVISION
    RESIDENCE_CENSUSDIVISION
    RESIDENCE_CENSUSSUBDIVISION
    RESIDENCE_POSTALCODE
    DEATH_DAY
    BIRTH_DAY
    CERTIFICATION_DAY
    NAME
    SPOUSE_SURNAME
    SPOUSE_INITIALS
    SPOUSE_SURNAME
    SPOUSE_INITIALS
    FATHER_SURNAME
    FATHER_INITIALS
    MOTHER_SURNAME
    MOTHER_INITIALS
    SPOUSE_GIVEN_NAME1
    SPOUSE_GIVEN_NAME2
    SPOUSE_GIVEN_NAME3
    FATHER_GIVEN_NAME1
    FATHER_GIVEN_NAME2
    FATHER_GIVEN_NAME3
    MOTHER_GIVEN_NAME1
    MOTHER_GIVEN_NAME2
    MOTHER_GIVEN_NAME3
    MOTHER_CURRENT_SURNAME
Diversity and Skills Database (DSD)
DSD
Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
DSD DSD 10 WEIGHT
    Homicide Survey
    Survey details
    Homicide Survey
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    HOMICIDE
    • CSC_1961_1973
    • CSC_1974_1983
    • CSC_1984_1993
    • CSC_1994_2003
    • CSC_2004_2013
    • INC_1961_1973
    • INC_1974_1983
    • INC_1984_1993
    • INC_1994_2003
    • INC_2004_2013
    • VICTIM_1961_1973
    • VICTIM_1974_1983
    • VICTIM_1984_1993
    • VICTIM_1994_2003
    • VICTIM_2004_2013
    • POPS_BYCANPROV_1961_1973
    • POPS_BYCANPROV_1974_1983
    • POPS_BYCANPROV_1984_1993
    • POPS_BYCANPROV_1994_2003
    • POPS_BYCANPROV_2004_2013
    • POPS_BYRESP_1961_1973
    • POPS_BYRESP_1974_1983
    • POPS_BYRESP_1984_1993
    • POPS_BYRESP_1994_2003
    • POPS_BYRESP_2004_2013
    3 WEIGHT  
    Postsecondary Student Information System (PSIS)
    Survey details
    PSIS
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSIS
    • ENROLMENT
    • GRADUATE
    5 WEIGHT  
    Postsecondary Student Information System – Non Institutional (PSISNOINST)
    Survey details
    PSISNOINST
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSISNOINST
    • ENROLMENT
    • GRADUATE
    5 WEIGHT  
    Registered Apprenticeship Information System (RAIS)
    Survey details
    RAIS 1991-2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    RAIS199108 RAIS 5 WEIGHT
    • RAIS2_FTPTSTAT_CODE
    • RAIS2_HIGEDLEV_CODE
    • RAIS2_TRAINING_CODE
    • RANDOM_NUMBER
    • DURHOURS_MEASURE
    • DURHOURS_MEASURE_COUNT
    • DURPGM_MEASURE
    • DURPGM_MEASURE_COUNT
    • INICREDR_MEASURE
    • INICREDR_MEASURE_COUNT
    • TOTHCOMP_MEASURE
    • TOTHCOMP_MEASURE_COUNT
    RAIS 2009-2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    RAIS200918 RAIS 5 WEIGHT
    • RAIS2_FTPTSTAT_CODE
    • RAIS2_HIGEDLEV_CODE
    • RAIS2_TRAINING_CODE
    • RANDOM_NUMBER
    • DURHOURS_MEASURE
    • DURHOURS_MEASURE_COUNT
    • DURPGM_MEASURE
    • DURPGM_MEASURE_COUNT
    • INICREDR_MEASURE
    • INICREDR_MEASURE_COUNT
    • TOTHCOMP_MEASURE
    • TOTHCOMP_MEASURE_COUNT
    RAIS 2019-2028
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    RAIS201928 RAIS 5 WEIGHT
    • RAIS2_AGE_CODE
    • RAISHIST_DATECERT_YYYYMM_CODE
    • RAISHIST_DATEREG_YYYYMM_CODE
    • RAIS2_DURHOURS_CODE
    • RAIS2_PREAPTGD_YYYY_CODE
    • RAIS2_PRECERTRAIS_CODE
    • RAIS2_PRECERTRAIS_SUBTRADE_CODE
    • RAIS2_PREAPTGRAIS_CODE
    • RAIS2_TRADERAIS_CODE
    • RAIS2_SUBTRADE_CODE
    • RAIS2_MAJOR_TRADE_CODE
    • RAIS2_OCCUPATION_CODE
    • RANDOM_NUMBER
    • DURHOURS_MEASURE_COUNT
    • DURPGM_MEASURE_COUNT
    • INICREDR_MEASURE_COUNT
    • TOTHCOMP_MEASURE_COUNT
    • RAIS2_DURPGM_CODE
    • RAIS2_FTPTSTAT_CODE
    • RAIS2_HIGEDLEV_CODE
    • RAIS2_INICREDR_CODE
    • RAIS2_TOTHCOMP_CODE
    • RAIS2_TRAINING_CODE
    Uniform Crime Reporting Survey (UCR)
    Survey details
    UCR
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    UCR
    • INC2008
    • INC2009
    • INC2010
    • INC2011
    • INC2012
    • SINGLE_ACCUSED2008
    • SINGLE_ACCUSED2009
    • SINGLE_ACCUSED2010
    • SINGLE_ACCUSED2011
    • SINGLE_ACCUSED2012
    • VIC2008
    • VIC2009
    • VIC2010
    • VIC2011
    • VIC2012
    • CSC2008
    • CSC2009
    • CSC2010
    • CSC2011
    • CSC2012
    5 WEIGHT  

    Crowdsourcing data

    Statistics available – Proportions

    Impacts of COVID-19 on Canadians (ICC)
    Survey details
    ICC2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020 ICC 10 WEIGHT
    • COLLWK
    • VERDATE
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM_05
    ICC2020MH
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020MH ICC 10 WEIGHT
    • VERDATE
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM1_35
    • DEM_05
    • IMMYR
    ICC2020PS
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020PS ICC 10 WEIGHT
    • VERDATE
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM1_35
    • DEM_05
    • IMMYR
    ICC2020TIO
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020TIO ICC 10 WEIGHT
    • VERDATE
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM1_35
    • DEM_05
    • IMMYR
    ICC2020PDP
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020PDP ICC 10 WEIGHT
    • VERDATE
    • RESPLANG
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM1_35
    • DEM_05
    • IMMYR
    ICC2020LTC
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020LTC ICC 10 WEIGHT
    • VERDATE
    • RESPLANG
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM_05
    ICC2020ED
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ICC2020ED ICC 10 WEIGHT
    • VERDATE
    • RESPLANG
    • DEM_15
    • CMA
    • CT
    • CSDUID
    • MASTERID
    • DEM1_35
    • DEM_05
    • IMMYR

    Social data

    Statistics available – All

    Aboriginal Children's Survey (ACS)
    Survey details
    ACS 2006
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ACS2006 ACS2006 20 WTPM
    • PRCDDA
    • DIREGION
    • SGC
    • CSDTYPEH
    • CSDTYPE1
    • CACMACOD
    • DURBRUR
    • PCSD1
    Aboriginal Peoples Survey (APS)
    Survey details
    APS 2001 (Adult)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2001AD APS_ADULTS_RDC 20 WGT_PST2
    • APS_COMMNAME_REGROUP
    • CACMA
    • PWCMA
    • PRCDDA
    • CSDTYPEH
    • PEDEA
    • PCSD
    • PCSD1
    • PCSD5
    • CSDTYPE1
    • REGIONN
    • CSDTYPE5
    • PWSGC
    • G05CKBX
    • G05R021
    • G05R051
    APS 2001 (Arctic)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2001AR APS_ARCTIC_RDC 20 WGT_PST2
    • APS_COMMNAME_REGROUP
    • CACMA
    • PWCMA
    • PRCDDA
    • CSDTYPEH
    • PEDEA
    • REGIONN
    • PCSD
    • PCSD1
    • PCSD5
    • CSDTYPE1
    • CSDTYPE5
    • PWSGC
    • G05CKBX
    • G05R021
    • G05R051
    APS 2001 (Child)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2001CH APS_KIDS_RDC 20 WGT_PST2
    • APS_COMMNAME_REGROUP
    • CACMA
    • PRCDDA
    • CSDTYPEH
    • PEDEA
    • REGIONN
    • PCSD
    • PCSD1
    • PCSD5
    • CSDTYPE1
    • CSDTYPE5
    APS 2001 (Metis)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2001ME APS_METIS_RDC 20 WGT_PST2
    • APS_COMMNAME_REGROUP
    • CACMA
    • PWCMA
    • PRCDDA
    • CSDTYPEH
    • PEDEA
    • REGIONN
    • PCSD
    • PCSD1
    • PCSD5
    • CSDTYPE1
    • CSDTYPE5
    • PWSGC
    • G05CKBX
    • G05R021
    • G05R051
    APS 2006 (Adult)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2006AD APS2006AD 50 WTPM
    • PRCDDA
    • DIREGION
    • SGC
    • CSDTYPEH
    • CSDTYPE1
    • CSDTYPE5
    • CACMACOD
    • DURBRUR
    • PCSD1
    • PCSD5
    • PWCMA
    • PWSGC
    APS 2006 (Child)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2006CH APS2006CH 20 WTPM
    • PRCDDA
    • DIREGION
    • SGC
    • CSDTYPEH
    • CSDTYPE1
    • CSDTYPE5
    • CACMACOD
    • PCSD1
    • PCSD5
    • PWCMA
    • PWSGC
    APS 2006 (Arctic)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2006AR APS2006AR 20 WTPM
    • PRCDDA
    • DIREGION
    • SGC
    • CSDTYPEH
    • CSDTYPE1
    • CSDTYPE5
    • CACMACOD
    • DURBRUR
    • PCSD1
    • PCSD5
    APS 2006 (Metis)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2006ME APS2006ME 50 WTPM
    • PRCDDA
    • DIREGION
    • SGC
    • CSDTYPEH
    • CSDTYPE1
    • CSDTYPE5
    • CACMACOD
    • DURBRUR
    • PCSD1 PCSD5
    • PWCMA
    • PWSGC
    • POB_SGC
    APS 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2012 APS2012 20 WGHT
    • NPRCDDA
    • NSGC
    • CSDTYPE1
    • CSDTYPE5
    • NCSDTYPE
    • CMA1
    • CMA5
    • NCMACA
    • WCMA
    • NCMACAT
    • PCSD1
    • PCSD5
    • PWSGC
    APS 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2017 APS2017 50 WGHT
    • MASTERID
    • PROXY
    • VERDATE
    • INU_REG
    • PRCDDA
    • SGC
    • CMACA
    • POPCTRRA
    • DPL
    • DPLTYPE
    • PR_HRUID
    • PCD1
    • PCSD1
    • CMA1
    • PCD5
    • PCSD5
    • CMA5
    • PWCD
    • PWSGC
    • PWCMA
    • DAGEINTM
    • DAGEINTY
    • AGECEN16
    • HC_05
    • NUNITS
    • HC_10
    • DJOBTENM
    • NAIC17_2
    • NAIC17_3
    • NAIC12SS
    • NAIC2012
    • NOC16_2
    • NOC16_3
    • NOC16_4
    • NOC16MAJ
    • NOC16MIN
    • NOC2016
    • PJA_10A
    • DLASTWKM
    • DWSUB
    • DWSUBRD
    • TOTINCPT
    • EMPINPT
    • CSDTYPE
    • CMACAT
    • INUREGST
    • CMACAST
    • POPCTRSZ
    • JT_05
    • JT_15
    • DJOBSTY
    • HOU_Q20
    • PSC_20
    • SPS_05
    • CFHH
    • CFNM
    • CFCNT_PP
    • CFKIDNUM CFKID0T4
    • CFKID5T9
    • CFK10T14
    • CFK0T14
    • CFK15T17
    • CFK18T24
    • CFKGE25
    • EFCNT_PP
    • BEDRM
    • ROOMS
    • HOURS
    • WEEKS
    • PWDIST2R
    • PWDUR
    • HH_NEARN
    • CF_NEARN
    • EF_NEARN
    APS 2017 NUNAVUT INUIT SUPPLEMENT (NIS)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    APS2017NIS APS2017NIS 10 WGHT
    • MASTERID
    • PROXY
    • VERDATE
    • INU_REG
    • PRCDDA
    • SGC
    • CMACA
    • POPCTRRA
    • DPL
    • DPLTYPE
    • PR_HRUID
    • PCD1
    • PCSD1
    • CMA1
    • PCD5
    • PCSD5
    • CMA5
    • PWCD
    • DPWNCD
    • PWSGC
    • DPWNCSD
    • PWCMA
    • DAGEINTM
    • DAGEINTY
    • AGECEN16
    • HC_05
    • NUNITS
    • HC_10
    • DJOBTENM
    • NAIC17_2
    • NAIC17_3
    • NAIC12SS
    • NAIC2012
    • NOC16_2
    • NOC16_3
    • NOC16_4
    • NOC16MAJ
    • NOC16MIN
    • NOC2016
    • PJA_10A
    • DLASTWKM
    • DWSUB
    • DWSUBRD
    • TOTINCPT
    • EMPINPT
    • CSDTYPE
    • CMACAT
    • INUREGST
    • CMACAST
    • POPCTRSZ
    • JT_05
    • JT_15
    • DJOBSTY
    • HOU_Q20
    • PSC_20
    • SPS_05
    • CFHH
    • CFNM
    • CFCNT_PP
    • CFKIDNUM
    • CFKID0T4
    • CFKID5T9
    • CFK10T14
    • CFK0T14
    • CFK15T17
    • CFK18T24
    • CFKGE25
    • EFCNT_PP
    • BEDRM
    • ROOMS
    • HOURS
    • WEEKS
    • PWDIST2R
    • PWDUR
    • HH_NEARN
    • CF_NEARN
    • EF_NEARN
    Access and Support to Education and Training Survey (ASETS)
    Survey details
    ASETS 2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    ASETS2008 ASETS2008 10 WTPM
    • REGION
    • UARATYPE
    • IM_Q01
    • IM_Q02
    • IM_Q03
    • IM_Q04
    • IM_Q06
    • IM_Q07
    • IM_Q09
    • IM_Q10
    • IM_Q11A
    • IM_Q11B
    • IM_Q11C
    • IM_Q12
    • IM_Q13
    Adult Education and Training Survey (AETS)
    Survey details
    AETS 2003
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    AETS2003 AETS2003 500 WTPM
    • ERTAB
    • CMATAB
    • FRAME
    • STRAFRAM
    • TYPE
    • DM_Q04
    Canadian Armed Forces Health Survey (CAFHS)
    Survey details
    CAFHS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAFHS2019 CAFHS2019 10 WTPM
    • DMI_14
      DMI_05
      DMI_12B
      DMI_13B
      DMI_15B
      HWT_02B
      HWT_02C
      DEM_07
    Canadian Health Measures Survey (CHMS)
    Survey details
    CHMS 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHMS2017 CHMS 1000 WGT_FULL
    • C2_DAY
    • C2_MTH
    • C2_YEAR
    • PROXY
    • PPI_02
    • PPI_03
    • PPID03
    • SITESTRT
    • SITEEND
    • CLC_MOB
    • CLC_DOB
    • SITE
    • DHH_PRN
    • IMG_02
    • CLINICID
    • DHH_DOB
    • DHH_MOB
    • LAFCIC12
    • LAFCOC11
    • LAFCIC17
    • LAFCOC16
    • LAEC02A
    • LAEC02B
    • LAEC02C
    • LAEC03A
    • LAEC03B
    • LAEC03C
    • LAEC06A
    • LAEC06B
    • LAEC06C
    Canadian Community Health Survey (CCHS)
    Survey details
    CCHS 2002
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2002 HS 500 WTSB_M
    • ADMB_DAT
    • ADMB_ENT
    • ADMB_LHH
    • ADMB_N10
    • ADMB_N12
    • ADMB_STA
    • ADMBDN09
    • PERSONID
    • SAMPLEID
    • DHHB_DOB
    • DHHB_MOB
    • GEOB_PC
    • GEOBDCD
    • GEOBDCMA
    • GEOBDCSD
    • GEOBDEA
    • GEOBDFED
    • SAMB_ACP
    • SAMB_OCP
    • SAMBDLNK
    • SAMBDSHR
    • WTSB_S
    CCHS 2002 Canadian Forces
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2002CF HSCF 10 WTSB_M
    • ADMB_DAT
    • ADMB_LHH
    • ADMB_STA
    • ADMBDN09
    • PERSONID
    • SAMPLEID
    • DHHB_DOB
    • DHHB_MOB
    • SAMB_ACP
    • SAMB_OCP
    • SAMPTYPE
    • CF_B_REG
    • CF_BDREG
    CCHS 2003
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2003 HS 200 WTSC_M
    • ADMC_DOI
    • ADMC_DQI
    • ADMC_LHH
    • ADMC_MOI
    • ADMC_MQI
    • ADMC_N09
    • ADMC_N10
    • ADMC_N11
    • ADMC_N12
    • ADMC_PRX
    • ADMC_STA
    • ADMC_YOI
    • ADMC_YQI
    • ADMCFQCP
    • SAMPLEID
    • DHHC_DOB
    • DHHC_MOB
    • PERSONID
    • GEOCDCD
    • GEOCDCMA
    • GEOCDCSD
    • GEOCDDA
    • GEOCDEA
    • GEOCDFED
    • GEOCDPC
    • GEOCDSHR
    • LBFCCNIC
    • LBFCCSOC
    • SAMC_CP
    • SAMC_TYP
    • SAMCDCP2
    • SAMCDLNK
    • SAMCDSHR
    • SAMCDSJB
    • WTSC_S
    • WTSC_SJB
    • WTSCFSS1
    • WTSCFSS2
    • WTSCFSS3
    CCHS 2005
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2005 HS 200 WTSE_M
    • ADME_DOI
    • ADME_LHH
    • ADME_MOI
    • ADME_N09
    • ADME_N10
    • ADME_N11
    • ADME_N12
    • ADME_PRX
    • ADME_STA
    • ADME_YOI
    • DHHE_DOB
    • DHHE_MOB
    • GEOEDCD
    • GEOEDCMA
    • GEOEDCSD
    • GEOEDDA
    • GEOEDFED
    • GEOEDPC
    • GEOEDSHR
    • SAME_CP
    • SAME_TYP
    • SAMEDLNK
    • SAMEDSHR
    • SAMPLEID
    • WTSE_S
    CCHS 2007
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2007 HS 200 WTS_M
    • VERDATE
    • GEODCD
    • GEODCMA1
    • GEODCMA6
    • GEODCSD
    • GEODDA01
    • GEODDA06
    • GEODFED
    • GEODLHN
    • GEODPC
    • GEODSAT
    • REFPER
    • SAM_CP
    • SAM_TYP
    • SAMDLNK
    • SAMDSHR
    • SAMPLEID
    • ADM_DOI
    • ADM_MOI
    • ADM_YOI
    • ADM_LHH
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_PRX
    • ADM_STA
    • PERSONID
    • DHH_DOB
    • SDCCCB
    • LBSCSIC
    • LBSCSOC
    • INCDADR
    • WTS_S
    CCHS 20072008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS200708 CCHS200708 200 WTS_M
    • GEODPC
    • GEODHR4
    • GEODLHN
    • GEODDA06
    • GEODDA01
    • GEODCSD
    • GEODCD
    • GEODCMA6
    • GEODCMA1
    • WTS_S
    CCHS 2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2008
    • CCHS2008
    • CCHS2008SUB
    500
    • WTS_M
    • WTS_2SM
    • GEODCD
    • GEODCMA1
    • GEODCMA6
    • GEODCSD
    • GEODDA01
    • GEODDA06
    • GEODFED
    • GEODHR4
    • GEODLHN
    • GEODPC
    • GEODPRG
    • GEODPSZ
    • GEODSAT
    • GEODUR
    • GEODUR2
    CCHS 2009
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2009 HS 200 WTS_M
    • VERDATE
    • REFPER
    • SAMPLEID
    • PERSONID
    • GEODPC
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • SAM_CP
    • SAM_TYP
    • SAMDSHR
    • SAMDLNK
    • ADM_STA
    • ADM_PRX
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • DHH_DOB
    • WTS_S
    • SDCCCB
    • LBSCSIC
    • LBSCSOC
    • LBSF35S
    • INCDADR
    CCHS 2009 Healthy Aging
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2009HA HS 500 WTS_M
    • GEODCD
    • GEODCMA6
    • GEODCSD
    • GEODDA06
    • GEODFED
    • GEODPC
    • GEODPSZ
    • GEODSAT
    • GEODUR
    • GEODUR2
    • WTS_S
    • VERDATE
    • REFPER
    • SAMDSHR
    • SAMDLNK
    • SAM_CP2
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • ADM_PRX
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • DHH_DOB
    • LBFCSIC
    • LBFCSOC
    • SDC_1
    • IN2TRAT
    • IN2DADR
    • SDCCCB
    CCHS 20092010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS200910 HS 200 WTS_M
    • VERDATE
    • REFPER
    • SAMPLEID
    • SAM_CP
    • SAM_TYP
    • SAMDSHR
    • SAMDLNK
    • PERSONID
    • GEODPC
    • GEODLHN
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • GEODDA06
    • ADM_STA
    • ADM_PRX
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • WTS_S
    • DHH_DOB
    • SDCCCB
    • LBSCSIC
    • LBSCSOC
    • LBSF35S (all not applicable)
    • INWCSIC
    • INWCSOC
    • INCDADR
    CCHS 2010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2010 CCHS2010 200 WTS_M
    • GEODPC
    • GEODHR4
    • GEODBCHA
    • GEODSHR
    • GEODDHA
    • GEODRHA
    • GEODLHA
    • GEODLHN
    • GEODDA06
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • GEODPG09
    • GEODUR
    • GEODUR2
    • WTS_S
    CCHS 2011
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2011 HS 250 WTS_M
    • GEODPC
    • GEODSHR
    • GEODDA06
    • GEODCSD
    • GEODCD
    • WTS_S
    CCHS 20112012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS201112 HS 250 WTS_M
    • VERDATE
    • REFPER
    • SAMPLEID
    • SAM_CP
    • SAM_TYP
    • SAMDSHR
    • GEODPC
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • GEODDA06
    • GEODSUBZ
    • ADM_STA
    • ADM_PRX
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • DHH_DOB
    • WTS_S
    • LBSCSIC
    • LBSCSOC
    • INWCSIC
    • INWCSOC
    • INCDADR
    • INCFIMP4
    • SDDC5B1
    • SDDC5B2
    • SDDC5B3
    • SDDC61
    • SDDC62
    • SDDC63
    • SDCCCB10
    • SPVCRL12
    CCHS 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2012 HS 250 WTS_M
    • GEODPC
    • GEODSHR
    • GEODDA06
    • GEODCSD
    • GEODCD
    • WTS_S
    CCHS 2012 Mental Health
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2012MH HS 500 WTS_M
    • WTS_S
    • GEODPC
    • GEODDA11
    • GEODCD
    • GEODCMA1
    • GEODCSD
    • GEODFED
    • GEODSAT
    • GEODUR
    • GEODUR2
    CCHS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2013 HS 200 WTS_M
    • SAMPLEID
    • PERSONID
    • GEOPDCMAA
    • GEODDA11
    • GEODPC
    • GEODCSD
    • GEODCD
    • ADM_DOI
    • DHH_DOB
    • DHH_MOB
    • WTS_S
    • WTS_MHH
    CCHS 20132014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS201314 HS 200 WTS_M
    • DHH_DOB
    • GEODCD
    • GEODCMAA
    • GEODCSD
    • GEODDA06
    • GEODDA11
    • GEODFED
    • GEODPC
    • GEODSAT
    • GEODSUBZ
    • INCFIMP4
    • INWCSIC
    • INWCSOC
    • LBSCSIC
    • LBSCSOC
    • CASETYPE
    • REFPER
    • SAM_CP
    • SAM_TYP
    • SAMDLNK
    • SAMDSHR
    • SAMPLEID
    • VERDATE
    • WTS_S
    • PERSONID
    • ADM_PRX
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • SDCCCB13
    • SDCC5B1
    • SDCC5B2
    • SDCC5B3
    • SDCC61
    • SDCC62
    • SDCC63
    • INCDADR
    CCHS 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2014 CCHS 200 WTS_M
    • SAMPLEID
    • PERSONID
    • GEODCMAA
    • GEODDA11
    • GEODPC
    • GEODCSD
    • GEODCD
    • ADM_DOI
    • DHH_DOB
    • INCFIMP4
    • WTS_S
    CCHS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2015 CCHS 200 WTS_M
    • DOACC
    • DOADL
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • ADM_DOI
    • ADM_LHH
    • ADM_MOI
    • ADM_PRX
    • ADM_STA
    • ADM_YOI
    • DOADM
    • SAMDVLNK
    • SAMDVSHR
    • DOALC
    • DOALW
    • DOBPC
    • DOCCC
    • DOCCS
    • DOCHP
    • DOCIH
    • DOCMH
    • DODEN
    • DODEP
    • DHH_DOB
    • DHH_MOB
    • DODIA
    • DODRG
    • DODRM
    • DODRV
    • EHG2DVH9
    • EHG2DVR9
    • EHG2_01
    • EHG2_02
    • EHG2_03
    • EHG2_04
    • DOETS
    • DOEYX
    • DOFDC
    • DOFGU
    • DOFLU
    • DOFSC
    • DOFVC
    • DOGEN
    • GEODVCD
    • GEODVCMA
    • GEODVCSD
    • GEODVD11
    • GEODVFED
    • GEODVPC
    • GEODVSAT
    • GEODVUR
    • DOHMC
    • DOHUI
    • DOHWT
    • DOINC
    • INCFIMP4
    • DOINJ
    • DOINS
    • DOLBF
    • LBFCSIC
    • LBFCSOC
    • DOLOP
    • DOMAC
    • DOMAM
    • DOMED
    • DOMEX
    • DOMXA
    • DOMXS
    • DONBE
    • DONDE
    • DOPAA
    • DOPAP
    • DOPAY
    • DOPCU
    • DOPEX
    • DOPHC
    • DOPMK
    • DOPSA
    • DOPSC
    • DOSAC
    • CASEMODE
    • FRAMETYP
    • PERSONID
    • REFPER
    • SAMPLEID
    • SAM_CP
    • VERDATE
    • DOSCA
    • DOSDC
    • DOSFE
    • DOSLP
    • DOSMK
    • DOSPI
    • DOSPS
    • DOSSB
    • DOSTG
    • DOSTS
    • DOSUI
    • DOSWL
    • DOSXB
    • DOTAL
    • DOUCN
    • DOUPE
    • DOWST
    • DOWTM
    • WTS_S
    CCHS 20152016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS201516 HS 200 WTS_M
    • DOACC
    • DOADL
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • ADM_DOI
    • ADM_LHH
    • ADM_MOI
    • ADM_PRX
    • ADM_STA
    • ADM_YOI
    • DOADM
    • SAMDVLNK
    • SAMDVSHR
    • DOALC
    • DOALW
    • DOBPC
    • DOCCC
    • DOCCS
    • DOCHP
    • DOCIH
    • DOCMH
    • DOCPG
    • DODEN
    • DODEP
    • DHH_DOB
    • DHH_MOB
    • DODIA
    • DODRG
    • DODRM
    • DODRV
    • DOETS
    • DOEYX
    • DOFDC
    • DOFGU
    • DOFLU
    • DOFSC
    • DOFVC
    • DOGEN
    • GEODVCD
    • GEODVCMA
    • GEODVCSD
    • GEODVD11
    • GEODVFED
    • GEODVPC
    • GEODVSAT
    • DOHMC
    • DOHUI
    • DOHWT
    • DOHWT
    • DOINJ
    • DOINS
    • DOLBF
    • DOLOP
    • DOMAC
    • DOMAM
    • DOMED
    • DOMEX
    • DOMXA
    • DOMXS
    • DONDE
    • DOOHT
    • DOPAA
    • DOPAP
    • DOPAY
    • DOPCU
    • DOPEX
    • DOPHC
    • DOPMK
    • DOPSA
    • DOPSC
    • DOSAC
    • CASEMODE
    • FRAMETYP
    • PERSONID
    • REFPER
    • SAMPLEID
    • SAM_CP
    • VERDATE
    • DOSCA
    • DOSCH
    • DOSDC
    • SDCCCOB
    • DOSLP
    • DOSMK
    • DOSPI
    • DOSPS
    • DOSSB
    • DOSTS
    • DOSUI
    • DOSWL
    • DOSXB
    • DOTAL
    • DOUCN
    • DOUPE
    • DOWST
    • DOWTM
    • WTS_S
    • INCFIMPH
    • INCFIMPP
    CCHS 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2016 CCHS2016 200 WTS_M
    • SAMPLEID
    • PERSONID
    • GEODVCMA
    • GEODVD11
    • GEODVPC
    • GEODVBHA
    • GEODVLHN
    • GEODVFED
    • GEODVCSD
    • GEODVCD
    • GEODVSAT
    • GEODVASZ
    • DHH_DOB
    • DHH_MOB
    • LBFCSIC
    • LBFCSOC
    • SDCCCOB
    • DHHDVAOS
    • DHH_YOB
    • MEX_020
    • MEX_025
    • MEX_030
    • SDC_IM4
    • SDCDVRES
    • SDCDVALI
    CCHS 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2017 CCHS2017 200 WTS_M
    • VERDATE
    • REFPER
    • SAM_CP
    • FRAMETYP
    • SAMDVSHR
    • SAMDVLNK
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_LHH
    • ADM_PRX
    • INCFIMPH
    • INCFIMPP
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • CASEMODE
    • WTS_S
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVSAT
    • GEODVUR
    • GEODVUR2
    • GEODVPSZ
    • GEODVBHA
    • GEODVLHN
    • GEODVASZ
    • SAMPLEID
    • PERSONID
    • DHH_DOB
    • DHH_MOB
    • INWCSIC
    • INWCSOC
    • LBFCSIC
    • LBFCSOC
    • MEX_020
    • MEX_025
    • MEX_030
    CCHS 20172018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS201718 HS 200 WTS_M
    • VERDATE
    • REFPER
    • SAM_CP
    • FRAMETYP
    • SAMDVSHR
    • SAMDVLNK
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_LHH
    • ADM_PRX
    • INCFIMPH
    • INCFIMPP
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • CASEMODE
    • WTS_S
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVUR
    • GEODVUR2
    • GEODVPSZ
    • GEODVBHA
    • GEODVLHN
    • GEODVASZ
    • SAMPLEID
    • PERSONID
    • DHH_DOB
    • DHH_MOB
    • INWCSIC
    • INWCSOC
    • LBFCSIC
    • LBFCSOC
    • MEX_020
    • MEX_025
    • MEX_030
    CCHS 2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2018 CCHS2018 200 WTS_M
    • VERDATE
    • REFPER
    • SAM_CP
    • FRAMETYP
    • SAMDVSHR
    • SAMDVLNK
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_LHH
    • ADM_PRX
    • INCFIMPH
    • INCFIMPP
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • CASEMODE
    • WTS_S
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVUR
    • GEODVUR2
    • GEODVPSZ
    • GEODVBHA
    • GEODVLHN
    • GEODVASZ
    • SAMPLEID
    • PERSONID
    • DHH_DOB
    • DHH_MOB
    • INWCSIC
    • INWCSOC
    • LBFCSIC
    • LBFCSOC
    • MEX_020
    • MEX_025
    • MEX_030
    CCHS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2019 CCHS2019 50 WTS_M
    • VERDATE
    • REFPER
    • SAM_CP
    • FRAMETYP
    • SAMDVSHR
    • SAMDVLNK
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_LHH
    • INCFIMPH
    • INCFIMPP
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • CASEMODE
    • WTS_S
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVUR
    • GEODVUR2
    • GEODVPSZ
    • GEODVBHA
    • GEODVLHN
    • GEODVASZ
    • SAMPLEID
    • PERSONID
    • DHH_DOB
    • DHH_MOB
    • LBFCSIC
    • LBFCSOC
    • DHH_YOB
    • MEX_020
    • MEX_025
    • MEX_030
    • SUI_015
    • SUI_030
    • SUI_050
    CCHS 201920
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS201920 CCHS201920 25 WTS_M
    • GEODVPC
    • GEODVD11
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEOVDCA
    • GEOVSAT
    • GEODVBHA
    • GEODVLHN
    • GEODVSLH
    • GEODVASZ
    • SAM_CP
    • ADM_MOI
    • ADM_DOI
    • DHH_MOB
    • MEX_020
    • MEX_025
    • LBFCSIC
    • LBFCSOC
    CCHS2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2020 CCHS2020 50 WTS_M
    • GEODVPC
    • GEODVD11
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEOVDCA
    • GEOVSAT
    • GEODVBHA
    • GEODVLHN
    • GEODVSLH
    • GEODVASZ
    • SAM_CP
    • ADM_MOI
    • ADM_DOI
    • DHH_DOB
    • DHH_MOB
    • MEX_020
    • MEX_025
    • LBFCSIC
    • LBFCSOC
    CCHS 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2021 CCHS2021 100 WTS_M
    • GEODVPC
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEOVDCA
    • GEOVSAT
    • GEODVBHA
    • GEODVLHN
    • GEODVSLH
    • GEODVASZ
    • SAM_CP
    • ADM_MOI
    • ADM_DOI
    • DHH_DOB
    • DHH_MOB
    • MEX_020
    • MEX_025
    • LBFCSIC
    • LBFCSOC
    CCHS 2022 Provincial File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2022PV CCHS2022PV 100 WTS_M
    • VERDATE
    • COL_LANG
    • ADM_MOI
    • ADM_DOI
    • GEODVPC
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVBHA
    • GEODVHCS
    • GEODVSHC
    • GEODVASZ
    • GDRA_10
    • AGE_01B
    • AGE_01C
    • LBFCSIC
    • SDCCCOC
    • MEX_20
    • MEX_25
    • LBFCSOC
    • SDCCCOB
    CCHS 2022 Territories File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2022TR CCHS2022TR 100 WTS_M
    • VERDATE
    • COL_LANG
    • ADM_MOI
    • ADM_DOI
    • GEODVPC
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVBHA
    • GEODVHCS
    • GEODVSHC
    • GEODVASZ
    • GDRA_10
    • AGE_01B
    • AGE_01C
    • LBFCSIC
    • SDCCCOC
    • MEX_20
    • MEX_25
    • LBFCSOC
    • SDCCCOB
    CCHS 2023
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CCHS2023 CCHS2023 100 WTS_M
    • VERDATE
    • COL_LANG
    • ADM_MOI
    • ADM_DOI
    • SAM_CP
    • GEODVPC
    • GEODVD21
    • GEODVD16
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVBHA
    • GEODVOHR
    • GEODVASZ
    • AGE_01B
    • AGE_01C
    • GDRA_10
    • LBFCSIC
    • LBFCSOC
    • SDCCCOB
    • SDCCCOC
    • MEX_20
    • MEX_25
    Canadian Financial Capability Survey (CFCS)
    CFCS 2009
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CFCS2009 CFCS2009 1000 WTPM
    • CMA
    • DM_Q12
    • MASTERID
    • AD_Q01D
    CFCS 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CFCS2014 CFCS 1000 WTPM
    • MASTERID
    • OCC_RET
    • OCC_EMP
    • SP_OCEMP
    • IN_I02
    • IN_I04
    Canadian Forces Mental Health Survey (CFMHS)
    Survey details
    CFMHS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CFMH2013 CFMH 10 WTPM  
    Canadian Health Survey on Children and Youth (CHSCY)
    Survey details
    CHSCY 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHSCY2019 CHSCY2019 50 WTS_M
    • ADM_DOIP
    • ADM_DOIY
    • ADM_MOIP
    • ADM_MOIY
    • ADM_YOIP
    • ADM_YOIY
    • COLFLGP
    • COLFLGY
    • SAMDVLKP
    • SAMDVLKY
    • SAMDVLNK
    • SAMDVSHP
    • SAMDVSHR
    • SAMDVSHY
    • COL_MODP
    • COL_MODY
    • HWT_030
    • PAIFLAG
    • VERDATE
    • REFPER
    • GEODVBHA
    • GEODVCD
    • GEODVCMA
    • GEODVCSD
    • GEODVD16
    • GEODVFED
    • GEODVHR4
    • GEODVLHN
    • GEODVUR
    • GEODVUR2
    • GEODVPC
    • GEODVPSZ
    • GEODVSAT
    • GEODVSLH
    • GEODVP16
    • DHH_DOB
    Canadian Health Survey on Seniors (CHSS)
    Survey details
    CHSS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHSS2019 CHSS2019 30 WTS_M
    • REFPER
    • SAM_CP
    • FRAMETYP
    • SAMDVSHR
    • SAMDVLNK
    • ADM_STA
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_LHH
    • INCFIMPH
    • INCFIMPP
    • ADM_040
    • ADM_045
    • ADM_050
    • ADM_055
    • CASEMODE
    • SAMDVLAS
    • SAMDVLK
    • SAMDVSR
    • ADM_STAS
    • ADM_540
    • ADM_545
    • ADM_550
    • ADM_555
    • WTS_S
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVCMA
    • GEODVCA
    • GEODVSAT
    • GEODVHR4
    • GEODVUR
    • GEODVUR2
    • GEODVPSZ
    • GEODVBHA
    • GEODVLHN
    • GEODVASZ
    • CHSSID
    • PERSONID
    • DHH_DOB
    • DHH_MOB
    • LBFCSIC
    • LBFCSOC
    • DHH_YOB
    • SUI_015
    • SUI_030
    CHSS 2019-2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHSS201920 CHSS201920 20 WTS_M
    • SAM_CP
    • ADM_MOI
    • ADM_DOI
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVSAT
    • GEODVBHA
    • GEODVLHN
    • GEODVSLH
    • GEODVASZ
    • DHH_MOB
    • DHH_DOB
    • SDCCCOB
    • SDCC2_1
    • SDCC2_2
    • SDCC2_3
    • SDCC3_1
    • SDCC3_2
    • SDCC3_3
    CHSS 2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHSS2020 CHSS2020 50 WTS_M
    • SAM_CP
    • ADM_MOI
    • ADM_DOI
    • GEODVPC
    • GEODVD16
    • GEODVD11
    • GEODVCSD
    • GEODVFED
    • GEODVCD
    • GEODVSAT
    • GEODVBHA
    • GEODVLHN
    • GEODVSLH
    • GEODVASZ
    • DHH_MOB
    • DHH_DOB
    • SDCCCOB
    • SDCC2_1
    • SDCC2_2
    • SDCC2_3
    • SDCC3_1
    • SDCC3_2
    • SDCC3_3
    Canadian Housing Survey (CHS)
    Survey details
    CHS 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CHS2022 CHS2022 100 WEIGHT
    • VERDATE
    • DV_COLY
    • DV_COLM
    • CDCSD
    • CMACA
    • CMAPO
    • CT
    • CTLA
    • CTPO
    • DA
    • DBUID
    • ER
    • FSA
    • HR
    • PCODE
    • POPCTRCD
    • POPCTRPO
    • POPCTRSZ
    • DEST_CSD
    • DEST_CMA
    • PAC_20A
    • HOM_35
    • HOM_15
    • EVI_10A
    • SOR_05
    • CNIT1BD
    • CNIT2BD
    • CNIT3BD
    • CNIT4BD
    • CNITBACH
    • CNITYEAR
    • CHNS
    • DV_AHS
    • DV_SUITS
    • SDH_10
    • HTYPE_L
    • FS
    • R2P1
    • DOB
    • MOB
    • SEX
    • GENDER
    • IM_20
    • VAC_15
    • DV_IM05A
    • DV_IM30B
    • EFID
    • CFID
    • IMM_CAT
    Canadian Income Survey (CIS)
    Survey details
    CIS 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2012 CIS 200 FWEIGHT
    • CNTRYEDU
    • CMA2G
    • URBSZ
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • PERSONID
    • MASTERID
    • DARES
    • ERTAB
    • EIERTAB
    • CDCSD
    • CMACA
    • CMA1G
    • CMA3G
    • CMAPO
    • URBCD
    • URBPO
    • EFID
    • EFSIZE
    • EFAGOFM
    • EFAGYFM
    • CFID
    • CFSIZE
    • CFAGOFM
    • CFAGYFM
    • CNTRYBTH
    • INCFAM
    • INCSR
    CIS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2013 CIS 200 FWEIGHT
    • CNTRYEDU
    • CMA2G
    • URBSZ
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • PERSONID
    • MASTERID
    • DARES
    • ERTAB
    • EIERTAB
    • CDCSD
    • CMACA
    • CMA1G
    • CMA3G
    • CMAPO
    • URBCD
    • URBPO
    • EFID
    • EFSIZE
    • EFAGOFM
    • EFAGYFM
    • CFID
    • CFSIZE
    • CFAGOFM
    • CFAGYFM
    • CNTRYBTH
    • INCFAM
    • INCSR
    CIS 2013 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2013DIS CIS_DISAB 200 DWEIGHT
    • PERSONID
    • VERDATE
    CIS 2013 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2013CMB CIS2013CMB 250 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2014 CIS 200 FWEIGHT
    • CNTRYEDU
    • CMA2G
    • URBSZ
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • PERSONID
    • MASTERID
    • DARES
    • ERTAB
    • EIERTAB
    • CDCSD
    • CMACA
    • CMA1G
    • CMA3G
    • CMAPO
    • URBCD
    • URBPO
    • EFID
    • EFSIZE
    • EFAGOFM
    • EFAGYFM
    • CFID
    • CFSIZE
    • CFAGOFM
    • CFAGYFM
    • CNTRYBTH
    • INCFAM
    • INCSR
    CIS 2014 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2014DIS CIS_DISAB 200 DWEIGHT
    • PERSONID
    • VERDATE
    CIS 2014 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2014CMB CIS2014CMB 250 WEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2015 CIS 200 FWEIGHT
    • CNTRYEDU
    • CMA2G
    • URBSZ
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • PERSONID
    • MASTERID
    • DARES
    • ERTAB
    • EIERTAB
    • CDCSD
    • CMACA
    • CMA1G
    • CMA3G
    • CMAPO
    • URBCD
    • URBPO
    • EFID
    • EFSIZE
    • EFAGOFM
    • EFAGYFM
    • CFID
    • CFSIZE
    • CFAGOFM
    • CFAGYFM
    • CNTRYBTH
    • INCFAM
    • INCSR
    CIS 2015 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2015DIS CIS_DISAB 200 DWEIGHT
    • PERSONID
    • VERDATE
    CIS 2015 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2015CMB CIS2015CMB 200 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2016 CIS 200 FWEIGHT
    • EFDUALCD
    • CMA1G
    • CMA2G
    • CMA3G
    • CMACA
    • CMAPO
    • DARES
    • ERTAB
    • REGRES
    • EIERTAB
    • URBCD
    • URBPO
    • CFID
    • EFID
    • INCFAM
    • MASTERID
    • PERSONID
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • CNTRYEDU
    • CNTRYBTH
    CIS 2016 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2016DIS CIS_DISAB 200 DWEIGHT
    • PERSONID
    • VERDATE
    • YEAR
    CIS 2016 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2016CMB CIS2016CMB 200 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2017 CIS 200 FWEIGHT
    • EFDUALCD
    • CMA1G
    • CMA2G
    • CMA3G
    • CMACA
    • CMAPO
    • DARES
    • ERTAB
    • REGRES
    • EIERTAB
    • URBCD
    • URBPO
    • CFID
    • EFID
    • INCFAM
    • MASTERID
    • PERSONID
    • VERDATE
    • YEAR
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • MBMREG
    • CNTRYEDU
    • CNTRYBTH
    CIS 2017 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2017DIS CIS_DISAB 200 DWEIGHT
    • PERSONID
    • VERDATE
    • YEAR
    CIS 2017 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2017CMB CIS2017CMB 200 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2018 CIS 200 FWEIGHT
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • MASTERID
    • PERSONID
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • INCSR
    • EFID
    • EFDUALCD
    • CFID
    CIS 2018 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2018DIS CIS_DISAB 200 DWEIGHT
    • YEAR
    • VERDATE
    • PERSONID
    CIS 2018 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2018CMB CIS2018CMB 200 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2019 CIS 200 FWEIGHT
    • YEAR
    • INCSR
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • MASTERID
    • PERSONID
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2019 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2019DIS CIS_DISAB 200 DWEIGHT
    • YEAR
    • VERDATE
    • PERSONID
    CIS 2019 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2019CMB CIS2019CMB 200 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2020 CIS2020 200 FWEIGHT
    • YEAR
    • INCSR
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • MASTERID
    • PERSONID
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2020 – Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2020DIS CIS_2020_DISAB 200 DWEIGHT
    • YEAR
    • VERDATE
    • PERSONID
    CIS 2020 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2020CMB CIS2020CMB 100 DWEIGHT
    • INCSR
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • EFID
    • EFDUALCD
    • CFID
    CIS 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2021 CIS2021 200 FWEIGHT
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • MASTERID
    • PERSONID
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • INCSR
    • EFID
    • EFDUALCD
    • CFID
    CIS 2021 - Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2021DIS CIS2021DIS 1000 DWEIGHT
    •  
    CIS 2021 Combined File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2021CMB CIS2021CMB 200 DWEIGHT
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • MASTERID
    • PERSONID
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • INCFAM
    • INCSR
    • EFID
    • EFDUALCD
    • CFID
    CIS 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2022 CIS2022 1000 CIS_WGT
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • EFID
    • EFDUALCD
    • CFID
    • CNTRYBTH
    CIS 2022 - Disability
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2022DIS CIS2022DIS 1000 CIS_DWT
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • EFID
    • EFDUALCD
    • CFID
    • CNTRYBTH
    CIS 2022 - Plus
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2022PL CIS2022PL 1000 CISP_WGT
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • EFID
    • EFDUALCD
    • CFID
    • CNTRYBTH
    CIS 2022 - Disability Plus
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIS2022DPL CIS2022DPL 1000 CISP_DWT
    • VERDATE
    • DARES
    • CDCSD
    • ERTAB
    • EIERTAB
    • CMACA
    • CMA1G
    • CMA2G
    • CMA3G
    • CMAPO
    • URBRUR
    • URBCD
    • URBPO
    • URBSZ
    • URBSZG
    • USZGA
    • NAICSCD
    • NAICSG1
    • NOCCD
    • NOCG1
    • EFID
    • EFDUALCD
    • CFID
    • CNTRYBTH
    Canadian Internet Use Survey (CIUS)
    Survey details
    CIUS 2009
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIUS2009 CIUS2009 500 WTPM
    • ERTAB
    • CDCSD
    • MIZ
    • CMATAB
    • CMA15
    • URBAN
    • URSTAT
    CIUS 2012HH
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIUS2012HH CIUS_HH 250 WTHM
    • MASTERID
    • ERTAB
    • CDCSD
    • CMATAB
    • CMACA
    • HINCIMP
    CIUS 2012PR
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIUS2012PR CIUS_PR 1000 WTPM
    • MSTRID_P
    • ERTAB
    • CDCSD
    • CMATAB
    • CMACA
    • NAICS
    • NOCS
    • CNTRYBTH
    • CNTRYEDU
    • HINCIMP
    CIUS 2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIUS2018 CIUS 500 WTPM
    • ECI_540G
    • ECI_540J
    • ECI_540K
    • ECI_570A
    • ECI_620A
    • HINCIMP
    • MASTERID
    • RR_020CA
    • PCODE
    CIUS 2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CIUS 2020 CIUS 2020 500 WTMP
    • ECI_010G
    • ECI_010L
    • ECI_020A
    • ECI_050B
    • ECI_060A
    • EC_FL07A
    • SP_FL03A
    • SP_FL03B
    • SP_FL03C
    • SP_FL03D
    • SP_FL03E
    • SP_FL03F
    • OW_FL05A
    • OWI_100A
    • OWI_100I
    • HA_FL03A
    • HA_FL03B
    • HA_FL03C
    • HA_FL03D
    • HA_FL03E
    • HA_FL03F
    • HINCIMP
    • IMM_FLAG
    • MASTERID
    • RR_020CA
    • PCODE
    • CMA
    • SACFLAG
    • MAINCMA
    • LOCATION
    • LAN_YEAR
    • LAN_AGE
    • EFF_YEAR
    • CTRY_BIR
    • CTRY_RES
    Canadian National Immunization Coverage Survey (CNICS)
    Survey details
    CNICS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CNICS2013 CNICS2013 50
    • FWGT_KAA
    • FWGT_VAC
    • MASTERID
    • THI_I01
    • VALS_06
    • PS_D02
    CNICS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CNICS2019 CNICS2019 1000 WTMP  
    CNICS 2019P
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CNICS2019P CNICS2019P 5 WTMP  
    CNICS 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CNICS2021 CNICS2021 10 WTMP  
    CNICS 2021P
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CNICS2021P CNICS2021P 5 WTMP  
    Canadian Social Survey (CSS)
    Survey details

    Canadian Social Survey – 2021 Wave 1
    Canadian Social Survey – 2021 Wave 2
    Canadian Social Survey – 2021 Wave 3
    Canadian Social Survey – 2021 Wave 4
    Canadian Social Survey – 2022 Wave 1
    Canadian Social Survey – 2022 Wave 2
    Canadian Social Survey – 2022 Wave 3
    Canadian Social Survey – 2023 Wave 1
    Canadian Social Survey – 2023 Wave 2
    Canadian Social Survey – 2023 Wave 3
    Canadian Social Survey – 2023 Wave 4
    Canadian Social Survey – 2024 Wave 1
    Canadian Social Survey – 2024 Wave 2
    Canadian Social Survey – 2024 Wave 3
    Canadian Social Survey – 2024 Wave 4

    Canadian Social Survey – COVID-19 and Well-being
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2021W1 CSS2021W1 1000 WGT

    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Well-being, Activities and Perception of Time
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2021W2 CSS2021W2 1000 WGT

    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Well-being, Unpaid Work and Family Time
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2021W3 CSS2021W3 1000 WGT

    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Well-being, and Family Relationships
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2021W4 CSS2021W4 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Well-being, Shared Values and Trust
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2022W1 CSS2022W1 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Well-being and Caregiving
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2022W2 CSS2022W2 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Quality of Life and Cost of Living
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2022W3 CSS2022W3 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey - Quality of Life and Energy Use
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2023W1 CSS2023W1 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_10
    GDR_5

    Canadian Social Survey – Quality of Life and Energy Use Household File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2023HH CSS2023HH 500 WGT_HH

    CMA
    CT
    CSDUID

    Canadian Social Survey – Quality of Life, Virtual Health Care and Trust
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2023W2 CSS2023W2 1000 WGT

    EVI_CMA
    CMA
    CT
    CSDUID
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life, Trust, and Renter Experiences
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2023W3 CSS2023W3 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life, Health and Compassionate Communities
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2023W4 CSS2023W4 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life, Health and Impacts of Rising Prices
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2024W1 CSS2024W1 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life, Health, and Housing Costs
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2024W2 CSS2024W2 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life, Housing and Trust
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2024W3 CSS2024W3 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    Canadian Social Survey – Quality of Life and Energy Consumption Behaviours
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2024W4 CSS2024W4 1000 WGT

    EQFLAG
    CMA
    CT
    CSDUID
    CSIZEMIZ
    GDR_05
    GDR_10

    CSS2024HH
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSS2024HH CSS2024HH 500 WGT_HH

    CMA
    CT
    CSDUID
    CSIZEMIZ
    EV_10A
    EV_10B
    EV_10C
    EV_10D
    EV_10E
    EV_10F
    EV_10G
    EV_10H
    EV_10I
    EV_10J
    EV_10K
    EV_15
    EV_D20
    EV_25
    EV_30
    EV_35
    WFH_D10

    Canadian Survey on Disability (CSD)
    Survey details
    CSD 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSD2012
    • CSD2012_DISAB
    • CSD2012_NONDISAB
    100 WTPM
    • CMA
    • CMA1
    • CMA5
    • CO1
    • CO5
    • PCD
    • PCD1
    • PCD5
    • PCSD
    • PCSD1
    • PCSD5
    • POB
    • POBF
    • POBM
    • PR1
    • PR5
    • PRCDDA
    • PWCMA
    • PWSGC
    CSD 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSD2017
    • CSD2017_DISAB
    • CSD2017_NONDISAB
    100 WTPM
    • MASTERID
    • VERDATE
    • HLTHREGN
    • ECONREGN
    • CMA
    • PCD
    • PCSD
    • PRCDDA
    • PCD1
    • PCSD1
    • CMA1
    • PCD5
    • PCSD5
    • CMA5
    • PWCD
    • PWSGC
    • PWCMA
    • DIND12_3
    • DIND17_3
    • DLIND7_3
    • NAIC2012
    • DOCC16_4
    • NOC2016
    • NOC16MIN
    • YRIM
    • AGE_IMM
    • POPCTRID
    • SAC_TYPE
    • ABARRSIN
    • DICD101
    • DICD102
    • DMFS16R3
    • DMFS16
    • DOCC16_3
    • DLIND7_2
    • ABETH1
    • ABETH2
    • ABETH3
    • ABETH4
    • ABETH5
    • ABETH6
    • ADLSEE
    • ADLHEAR
    • ADLPHYS
    • ADLLRNG
    • ADLEMOT
    • ADLOTHR
    • MEDDIP
    • CIP2011
    • CIP11_4
    • POB
    • POBF
    • POBM
    • CFKID04
    • CFKID05
    • CFKID014
    • CFKID59
    • CFKID614
    • CFKD1014
    • CFKID018
    • CFKD1517
    • CFKD1824
    • CFKDGE25
    • MINCHDAG
    • NOLW1R
    • NOLW2R
    • NOLW3R
    • NOLW4R
    • HLNAW1R
    • HLNBW1R
    • MTNW1R
    • LNWAW1R
    • LNWBW1R
    • SAC1
    • SAC5
    • PWSAC
    • PWCOMMUT
    • JT_05
    • JT_10
    • JT_15
    • JT_20
    CSD 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CSD2022
    • CSD2022_DISAB
    • CSD2022_NONDISAB
    100 WTPM
    • HLTHREGN
    • ECONREGN
    • CMA
    • PCD
    • PCSD
    • PRCDDA
    • ABARRSIN
    • PCD1
    • PCSD1
    • CMA1
    • PCD5
    • PCSD5
    • CMA5
    • PWCD
    • PWSGC
    • PWCMA
    • CIP21_4
    • NOC21MIN
    • NOC21T
    • NOC21S
    • NOC2016
    • NOC2021
    • NAIC2017
    • MEDDIP
    • CIP2021
    • CIP2011
    • CIP21_4
    • CIP11_4
    • LOCSTUDY
    • DPGRSUM
    • ETH1
    • ETH2
    • ETH3
    • ETH4
    • ETH5
    • ETH6
    • ABETH1
    • ABETH2
    • ABETH3
    • ABETH4
    • ABETH5
    • ABETH6
    • NOLW1R
    • NOLW2R
    • NOLW3R
    • NOLW4R
    • MTNW1R
    • DIND17_3
    • DLIND7_3
    • DIND22_3
    • DLID22_3
    • DOCC16_4
    • DOCC21_4
    • DOCC21_5
    • DOCC16_3
    • DOCC21_3
    • DLIND7_2
    • DLID22_2
    • DMFS16
    • DMFS21
    • DMFS16R3
    • DMFS21R3
    Canadian Tobacco, Alcohol and Drugs Survey (CTADS)
    Survey details
    CTADS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Household File: CTADS2013 CTADS2013_HHLD 1000 WTHM
    • MASTERID
    • STRATUM
    • REFYEAR
    • REFMONTH
    • VALIDPC
    • FSA
    Person File: CTADS2013 CTADS2013_PRSN 1000 WTPM
    • MASTERID
    • STRATUM
    • REFYEAR
    • REFMONTH
    • VALIDPC
    • FSA
    CTADS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Household File: CTADS2015 CTADS2015HH 1000 WTHM
    • MASTERID
    • REFYEAR
    • REFMONTH
    • STRATUM
    • VERDATE
    • FINTLANG
    • TNIS_01
    Person File: CTADS2015 CTADS2015PR 1000 WTPM
    • MASTERID
    • REFYEAR
    • REFMONTH
    • POSTCODE
    • FSA
    • VERDATE
    • LP_01
    CTADS 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Household File: CTADS2017 CTADS2017H 500 WTHM
    • MASTERID
    • REFMONTH
    • STRATUM
    • VERDATE
    • FINTLANG
    • TNS2_01
    Person File: CTADS2017 CTADS2017P 1000 WTPM
    • MASTERID
    • REFMONTH
    • POSTCODE
    • FSA
    • VERDATE
    Canadian Tobacco and Nicotine Survey (CTNS)
    Survey details
    CTNS 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CTNS2021 CTNS2021 1000 WTMP
    • VERDATE
    • REFYEAR
    • REFMONTH
    • REFDAY
    • DEM_30
    • MASTERID
    • DEM_15B
    • DEM_15C
    • DEM_20
    • DEM_15A
    • DEM_25
    CTNS 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CTNS2022 CTNS2022 500 WTMP
    • DEM_30
    • DV_AGE
    Digital Economy Survey (DES)
    Survey details
    DES 2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    DES2018 DES2018 1000 WTMP
    • VERDATE
    • DES_FL20
    • DEM_30
    Employment Insurance Coverage Survey (EICS)
    Survey details
    EICS 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    EICS2014 EICS 500 WTPM
    • MASTERID
    • SRYR
    • UIRTAB
    • MONTHID
    • OCC
    • IND2
    • OCC2
    • SP_SIC
    • SP_SOC
    EICS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    EICS2015 EICS 500 WTPM
    • MASTERID
    • SRYR
    • UIRTAB
    • MONTHID
    • IND
    • IND2
    • NAICS6
    • OCC
    • OCC2
    • SP_SOC
    EICS 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    EICS2016 EICS 500 WTPM
    • IND
    • IND2
    • MASTERID
    • MONTHID
    • OCC
    • OCC2
    • SP_SIC
    • SP_SOC
    • SRYR
    • TYPES
    • WA_Q02
    • UIRTAB
    Ethnic Diversity Survey (EDS)
    Survey details
    EDS 2001
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    EDS2001 EDS2001 500 WGT_EDS
    • SL_PCODE
    • SL_CACMA
    • SL_CSDTY
    • SL_RUIND
    • SL_SGC
    • SL_PRCDA
    • SL_CTCOD
    • SL_CTNAM
    • REGION
    • PCODE
    • RUIND
    • CACMA
    • CMA8
    • CMA6
    • CMA3
    • CMA_IND
    • REGCMA
    • CSDTYPE
    • SGC
    • PRCDDA
    • IMMSTAT
    • CTCODE
    • CTNAME
    • IMMSTAT
    • IMMYC
    • IMMY2
    • X_IM_RS
    General Social Survey (GSS)
    Survey details
    GSS Cycle 16
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2002 GSS2002 1000 WGHT_PER
    • GEOCD
    • GEOCSD
    • GEOCT
    • CMACD
    • URBNRURL
    • DOR_Q240
    • URIND
    GSS Cycle 17
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2003 GSS2003 1000 WGHT_PER
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • GEO_MET_NMET
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • GEO_EA96
    • GEO_SAC_TYPE
    • DOR_Q240
    • LUC_RST
    • GEO_UA_RA
    • GEO_UA_RA_TYPE
    • CEGEOIND
    GSS Cycle 18
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2004 GSS2004 1000
    • WGHT_PER
    • WGHT_ABU
    • DOR_Q240
    • GEO_DA
    • GEO_CT_PCT
    • GEO_CSD
    • GEO_CB
    • GEO_DPL
    • GEO_MET_NMET
    • GEO_UA_RA
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_UA_RA_TYPE
    • GEO_SAC_TYPE
    • CEGEOIND
    • LUC_RST
    GSS Cycle 19
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2005 C19ANALM_NUM 1000
    • ADJWTVIC
    • WGHT_PER
    • WGHT_CSP
    • WGHT_SNT
    • DOR_Q240
    • GEO_DA
    • GEO_CT_PCT
    • GEO_CSD
    • GEO_CB
    • GEO_DPL
    • GEO_MET_NMET
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_UA_RA
    • GEO_SAC_TYPE
    • LUC_RST
    • GEO_UA_RA_TYPE
    • CEGOIND
    GSS Cycle 20
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2006 C20ANALM_NUM 1000 WGHT_PER
    • DOR_Q240
    • GEO_DA
    • GEO_CT_PCT
    • GEO_DPL
    • GEO_CSD
    • GEO_CB
    • GEO_MET_NMET
    • GEO_CD
    • GEO_CMA_CA
    • GEO_UA_RA
    • GEO_CCS
    • STRATUM
    • GEO_SAC_TYPE
    • LUC_RST
    • CT_PCT_UID
    • GEO_UA_RA_TYPE
    • CEGEOIND
    GSS Cycle 21
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2007 GSS2007 1000 WGHT_PER
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • DVDOR_Q640
    • STRATUM
    • GEO_SAC_TYPE
    • LUC_RST
    • GEO_UA_RA
    • GEO_UA_RA_TYPE
    • CEGEOIND
    GSS Cycle 22
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2008 GSS2008 1000 WGHT_PER
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • RSP_Q40
    • STRATUM
    • GEO_SAC_TYPE
    • LUC_RST
    • CT_PCT_UID
    • GEO_UA_RA
    • GEO_UA_RA_TYPE
    • CEGEOIND
    GSS Cycle 23
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2009 C23ANALM 1000
    • WGHT_PER
    • WGHT_ABU
    • GEO_DA
    • GEO_CT_PCT
    • GEO_CSD
    • GEO_CB
    • GEO_DPL
    • GEO_MET_NMET
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CCS
    • GEO_UA_RA
    • GEO_UA_RA_TYPE
    • GEO_SAC_TYPE
    • GEO_ER
    • GEO_FED
    • CEGEOIND
    • RSP_Q40
    • RSP_Q42
    • STRATUM
    • LUC_RST
    • CT_PCT_UID
    GSS Cycle 24
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2010 GSS_ANALM 1000 WGHT_PER
    • WGHT_CSP
    • WGHT_SNT
    • STRATUM
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • CT_PCT_UID
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • BDR_Q100
    • RSP_Q40
    • RSP_Q42
    • NOCS2006
    GSS Cycle 25
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2011 GSS2011 1000 WGHT_PER
    • STRATUM
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • GEO_MET_NMET
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • RESPDAY
    • NOCS2006
    GSS Cycle 26
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2012 GSS2012 1000 WGHT_PER
    • STRATUM
    • GEO_CB
    • GEO_CCS
    • GEO_CD
    • GEO_CMA_CA
    • GEO_CSD
    • CEO_MET_NMET
    • GEO_CT_PCT
    • GEO_DA
    • GEO_DPL
    • GEO_FED
    • GEO_ER
    • PCODE
    • BDR_Q100
    • NOCS2011
    GSS Cycle 27 – Social Identity
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2013 GSS 1000 WGHT_PER
    • RECID
    • COMPFLAG
    • SAMPLE
    • COLLMODE
    • SURVMNTH
    • SURVYEAR
    • LANINT
    • PCODE
    • CCSCODE
    • CSDCODE
    • CT_CODE
    • DPLCODE
    • ERCODE
    • FEDCODE
    • MET_NMET
    • POPCTR
    • SACFLAG
    • CDCODE
    • DACODE
    • DBCODE
    • STRATUM
    • CT_PCT
    • BPRCODE
    • CTZCODE1
    • CTZCODE2
    • CTZCODE3
    GSS Cycle 27 – Giving, Volunteering and Participating
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2013GVP GSS2013GVP 1000 WGHT_PER
    • RECID
    • COMPFLAG
    • PCODE
    • FEDCODE
    • ERCODE
    • CDCODE
    • CCSCODE
    • CSDCODE
    • DACODE
    • DPLCODE
    • DBCODE
    • MET_NMET
    • CT_PCT
    • POPCTR
    • POPCTR_T
    • MV1I02A
    • MV1Y02A
    • MV1I02B
    • MV1Y02B
    • MV1I02C
    • MV1Y02C
    • MV1I02D
    • MV1Y02D
    • MV1I02E
    • MV1Y02E
    • MV1I02F
    • MV1Y02F
    • MV1I02G
    • MV1Y02G
    • MV1I02H
    • MV1Y02H
    • MV1I02I
    • MV1Y02I
    • MV1I02J
    • MV1Y02J
    • MV1I02K
    • MV1Y02K
    • MV1I02L
    • MV1Y02L
    • MV1I02M
    • MV1Y02M
    • MV1I02N
    • MV1Y02N
    • MV1I02O
    • MV1Y02O
    • FG1I030
    • FG1I040
    • FG1I050
    • FG1I060
    • FG1I070
    • FG1I080
    • FG1I090
    • FG1I100
    • FG1I110
    • FG1I120
    • FG1I130
    • FG1I140
    • FG1I170
    • FG1FGIV
    • NAIC2012
    • NOCS2011
    • NOCS2006
    • BPRCODE
    • BPR_15
    • FLAGRR
    • FLAGDM
    • CTFLAG
    • CSDCHO
    • CTNAME
    GSS Cycle 29
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2015 GSS_ANALM 1000 WGHT_PER
    • AGEARRI
    • BPFCODE
    • BPMCODE
    • BPRCODE
    • BPR_15
    • BPR_17
    • DDAY
    • EQFLAG
    • LANINT
    • RECID
    • SURVMNTH
    • NAIC12W
    • NOC11W
    • NAIC12Y
    • NOC11Y
    • CCSCODE
    • CDCODE
    • CSDCODE
    • CT_PCT
    • DACODE
    • DBCODE
    • DPLCODE
    • ERCODE
    • FEDCODE
    • MET_NMET
    • PCODE
    • POPCTR
    • POPCTR_T
    • STRATUM
    • CTNAME
    • FLAGDM
    • FLAGRR
    • LANCHCD1
    • LANCHCD2
    • LANCHCD3
    • LANHHCD1
    • LANHHCD2
    • LANHHCD3
    • RELIGCDH
    GSS Cycle 30
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Full File: GSS2016 GSS2016_FULL 1000 WGHT_PER
    • BPPCODE
    • PCODE
    • BPFCODE
    • BPMCODE
    • BPRCODE
    • BPR_15
    • BPR_17
    • LANINT
    • RECID
    • SURVMNTH
    • SURVYEAR
    • SURV_DAY
    • CCSCODE
    • CDCODE
    • CSDCODE
    • CTNAME
    • CT_PCT
    • DACODE
    • DBCODE
    • DPLCODE
    • ERCODE
    • FEDCODE
    • RESPMTH
    • STRATUM
    • FLAGDM
    • FLAGRR
    • RELIGCDH
    • SPLTSMPL
    • NAIC12Y
    • NOC16Y
    Cultural Participation File: GSS2016 GSS2016_CULT 1000 WGHT_CSP
    • BPPCODE
    • PCODE
    • BPFCODE
    • BPMCODE
    • BPRCODE
    • BPR_15
    • BPR_17
    • LANINT
    • RECID
    • SURVMNTH
    • SURVYEAR
    • SURV_DAY
    • CCSCODE
    • CDCODE
    • CSDCODE
    • CTNAME
    • CT_PCT
    • DACODE
    • DBCODE
    • DPLCODE
    • ERCODE
    • FEDCODE
    • RESPMTH
    • STRATUM
    • FLAGDM
    • FLAGRR
    • RELIGCDH
    • SPLTSMPL
    • NAIC12Y
    • NOC16Y
    Sport Participation File: GSS2016 GSS2016_SPORT 1000 WGHT_SNT
    • BPPCODE
    • PCODE
    • BPFCODE
    • BPMCODE
    • BPRCODE
    • BPR_15
    • BPR_17
    • LANINT
    • RECID
    • SURVMNTH
    • SURVYEAR
    • SURV_DAY
    • CCSCODE
    • CDCODE
    • CSDCODE
    • CTNAME
    • CT_PCT
    • DACODE
    • DBCODE
    • DPLCODE
    • ERCODE
    • FEDCODE
    • RESPMTH
    • STRATUM
    • FLAGDM
    • FLAGRR
    • RELIGCDH
    • SPLTSMPL
    • NAIC12Y
    • NOC16Y
    GSS Cycle 33 – Giving file
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2018GVP GSS2018GVP 1000 WEIGHT  
    GSS Cycle 33 – Analytical file
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2018 GSS2018 1000 WGHT_PER  
    GSS 2022 – Main file
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2022MN GSS2022MN 1000 WGHT_PER
    • SURVYEAR
    • LANINT
    • DDAY
    • PCODE
    • FEDCODE
    • ERCODE
    • CDCODE
    • CCSCODE
    • CSDCODE
    • DACODE
    • DPLCODE
    • DBCODE
    • MET_NMET
    • SACFLAG
    • CT_PCT
    • POPCTR
    • POPCTR_T
    • LUC_RST
    • SEX
    • GENDER
    • GENPR
    • NOC21W
    • NOC21Y
    • NAICS22W
    • NAICS22Y
    • IM_05B2
    • BPR_20B1
    • BPR_20B2
    • BPR_20C2
    • BPP_01A2
    • RELIGCDH
    • IM_01A2
    • IM_02
    • LGBTQ2
    GSS 2022 – Episode file
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    GSS2022EPI GSS2022EPI 1000 WGHT_EPI  
    Health Services Access Survey (HSAS)
    Survey details
    HSAS 2002
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    HSAS2002 HSAS2002 1000 FINWGHT
    • GEOADFED
    • GEOADUR1
    • GEOADEA
    Households and the Environment Survey (HES)
    Survey details
    HES 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    HES2013 HES 250 WTHM
    • MASTERID
    • FSA
    • CMA
    • CMACA
    • CD
    • CSD
    • ER
    • PS_Q02
    HES 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    HES2015 HES 250 WTHM
    • MASTERID
    • PS_Q02
    • CMACA
    • CMA
    • CD
    • CSD
    Indigenous Peoples Survey (IPS)
    Survey details
    IPS 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    IPS2022
    • IPS2022
    50 WGHT
    • VERDATE
    • PRCDDA
    • SGC
    • CSDTYPE
    • CMACA
    • CMACAT
    • PCD
    • POPCTRRA
    • DPL
    • DPLTYPE
    • PR_HRUID
    • PCD1
    • PCD5
    • PCSD1
    • PCSD5
    • PWCD
    • PWSGC
    • PWCMA
    • CMACAST
    • POPCTRSZ
    • PWDIST2
    • PWDUR
    • CMA1
    • CMA5
    • CO1
    • CO5
    • CSDTYPE1
    • CSDTYPE5
    • LOCSTUDY
    • DIDENTGM
    • DANCESG
    • DIDGM91
    • DMETORG
    • NAIC22_2
    • NAIC22_3
    • NOC21_2
    • NOC21_3
    • NOC21_4
    • NOC21_5
    • DNOC21CG
    • DNOC21NE
    • HC_05
    • NAIC17SS
    • NAIC2017
    • NOC21MAJ
    • NOC21MIN
    • NOC2021
    • DWSUB
    • DWSUBRD
    • EMPINPT
    • CFHH
    • CFNM
    • CFCNT_PP
    • CFKIDNUM
    • CFK0T4
    • CFK5T9
    • CFK10T14
    • CFK15T17
    • CFK18T24
    • CFKGE25
    • EFCNT_PP
    • BEDRM
    • ROOMS
    • HOURS
    • WEEKS
    • HH_NEARN
    • CF_NEARN
    • EF_NEARN
    • VIC_35AJ
    • VIC_35AK
    • VIC_35AP
    • VIC_35BJ
    • VIC_35BK
    • VIC_35BP
    • VIC_35CJ
    • VIC_35CK
    • VIC_35CP
    Labour Force Survey (LFS)
    Survey details
    LFS 1997-1999
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS199799 LFS199799 250 FINALWT LANDIMM
    LANDYR
    LANDMTH
    INDGSTAT
    INDGNAI
    INDGMET
    INDGINU
    IVMWT
    SPECWT
    CLUSTWT
    STABILWT
    THEORWT
    BALFACT
    SUBWT
    RUFAC
    URSTAT
    CDCSD
    VISMIN
    VISMINFL
    LFS 2000-2005
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS200005 LFS200005 250 FINALWT LANDIMM
    LANDYR
    LANDMTH
    INDGSTAT
    INDGNAI
    INDGMET
    INDGINU
    IVMWT
    SPECWT
    CLUSTWT
    STABILWT
    THEORWT
    BALFACT
    SUBWT
    RUFAC
    URSTAT
    CDCSD
    VISMIN
    VISMINFL
    LFS 2006-2010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS200610 LFS200610 250 FINALWT LANDIMM
    LANDYR
    LANDMTH
    INDGSTAT
    INDGNAI
    INDGMET
    INDGINU
    IVMWT
    SPECWT
    CLUSTWT
    STABILWT
    THEORWT
    BALFACT
    SUBWT
    RUFAC
    URSTAT
    CDCSD
    VISMIN
    VISMINFL
    LFS 2011-2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS201115 LFS201115 250 FINALWT LANDIMM
    LANDYR
    LANDMTH
    INDGSTAT
    INDGNAI
    INDGMET
    INDGINU
    IVMWT
    SPECWT
    CLUSTWT
    STABILWT
    THEORWT
    BALFACT
    SUBWT
    RUFAC
    URSTAT
    CDCSD
    VISMIN
    VISMINFL
    LFS 2016-2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS201620 LFS201620 250 FINALWT LANDIMM
    LANDYR
    LANDMTH
    INDGSTAT
    INDGNAI
    INDGMET
    INDGINU
    IVMWT
    SPECWT
    CLUSTWT
    STABILWT
    THEORWT
    BALFACT
    SUBWT
    RUFAC
    URSTAT
    CDCSD
    VISMIN
    VISMINFL
    LFS 2021-2025
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LFS202125 LFS202125 250 FINALWT
    • LANDIMM
      LANDYR
      LANDMTH
      INDGSTAT
      INDGNAI
      INDGMET
      INDGINU
      IVMWT
      SPECWT
      CLUSTWT
      STABILWT
      THEORWT
      BALFACT
      SUBWT
      RUFAC
      URSTAT
      CDCSD
      VISMIN
      VISMINFL
    Life After Service Survey (LASS)
    Survey details
    LASS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LASS2013 LASS 20 WTPM
    • HUI1_07A
    • HUI1_07B
    Longitudinal Survey of Immigrants to Canada (LSIC)
    Survey details
    LSICW1
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LSICW1 LSICW1 20 WT1L
    • LR1Z052
    • HS1D007
    LSICW2
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LSICW2 LSICW2 20 WT2L
    • LR1Z052
    • LR1Z064
    • HS1D123
    • HS1D124
    • HS1D125
    • HS1D126
    • HS2Q127
    • HS2L124
    LSICW3
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    LSICW3 LSICW3 20 WT3L
    • HS1D125
    • HS1D126
    • HS1D184
    • LR1Z052
    • LR1Z064
    • HS1D123
    • HS1D124
    • HS1D183
    Maternity Experiences Survey (MES)
    Survey details
    MES 2006
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    MES2006 MES2006 15 WTPS
    • FSA
    • CMACA
    National Apprenticeship Survey (NAS)
    Survey details
    NAS 2007
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NAS2007 NAS2007 10 WEIGHT
    • POSTCODE
    • CMA_Q01
    • CMA2PC
    • CUR_PC
    • CMA2Prov
    • CMA2Proa
    NAS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NAS2015 NAS 10 WTPM
    • POSTCODE
    • VERDATE
    • CNTRYCOD
    • LF5_I60
    • LF5_I62
    • LF5_I63
    • LF5_I64
    • LF5_I66
    • LF5_I67
    • LF5_I68
    • LF5_I69
    • LFALL_I
    • LFIND3
    • LFOCC3
    • LFTIME_I
    • LFWAGE_I
    • MR4_I60
    • MR4_I62
    • MR4_I63
    • MR4_I64
    • MR4_I66
    • MR4_I67
    • MR4_I68
    • MR4_I69
    • MRALL_I
    • MRIND3
    • MROCC3
    • MRTIME_I
    • MRWAGE_I
    • RESPFLAG
    • WEIND3
    • WEOCC3
    • MASTERID
    • ABQUE_11
    • ABQUE_12
    • ABQUE_13
    • ABQUE_14
    • AFTNC_11
    • AFTNC_12
    • AFTNC_13
    • AFTNC_14
    • BNET_11
    • BNET_12
    • BNET_13
    • BNET_14
    • CMNET_11
    • CMNET_12
    • CMNET_13
    • CMNET_14
    • CQPP_11
    • CQPP_12
    • CQPP_13
    • CQPP_14
    • CTBI_11
    • CTBI_12
    • CTBI_13
    • CTBI_14
    • EINS_11
    • EINS_12
    • EINS_13
    • EINS_14
    • EXIND_11
    • EXIND_12
    • EXIND_13
    • EXIND_14
    • FABEN_11
    • FABEN_12
    • FABEN_13
    • FABEN_14
    • FMNET_11
    • FMNET_12
    • FMNET_13
    • FMNET_14
    • FSNET_11
    • FSNET_12
    • FSNET_13
    • FSNET_14
    • GHSTC_11
    • GHSTC_12
    • GHSTC_13
    • GHSTC_14
    • INVI_11
    • INVI_12
    • INVI_13
    • INVI_14
    • LTPI_11
    • LTPI_12
    • LTPI_13
    • LTPI_14
    • NFSL_11
    • NFSL_12
    • NFSL_13
    • NFSL_14
    • NFTXC_11
    • NFTXC_12
    • NFTXC_13
    • NFTXC_14
    • NPTXC_11
    • NPTXC_12
    • NPTXC_13
    • NPTXC_14
    • OASP_11
    • OASP_12
    • OASP_13
    • OASP_14
    • OEI_11
    • OEI_12
    • OEI_13
    • OEI_14
    • OI_11
    • OI_12
    • OI_13
    • OI_14
    • PFNET_11
    • PFNET_12
    • PFNET_13
    • PFNET_14
    • PTXCL_11
    • PTXCL_12
    • PTXCL_13
    • PTXCL_14
    • RNET_11
    • RNET_12
    • RNET_13
    • RNET_14
    • RRSPO_11
    • RRSPO_12
    • RRSPO_13
    • RRSPO_14
    • SASPY_11
    • SASPY_12
    • SASPY_13
    • SASPY_14
    • SOP4A_11
    • SOP4A_12
    • SOP4A_13
    • SOP4A_14
    • T4E_11
    • T4E_12
    • T4E_13
    • T4E_14
    • TALIR_11
    • TALIR_12
    • TALIR_13
    • TALIR_14
    • UCCB_11
    • UCCB_12
    • UCCB_13
    • UCCB_14
    • WITB_11
    • WITB_12
    • WITB_13
    • WITB_14
    • WKCPY_11
    • WKCPY_12
    • WKCPY_13
    • WKCPY_14
    • XDIV_11
    • XDIV_12
    • XDIV_13
    • XDIV_14
    • XTIRC_11
    • XTIRC_12
    • XTIRC_13
    • XTIRC_14
    • LFCIND
    • MRCIND
    • WECIND
    • LFCOCC
    • MRCOCC
    • WECOCC
    • SL_R01
    • DVAGE15
    • DVDATY15
    • LF5_69
    • MR4_69
    • HRLYWMR
    • HRLYWLF
    • JOBINCMR
    • JOBINCLF
    • DH14DV
    • EDUCREG
    • POSTCODE
    • CMACA
    • SACFLAG
    • CMA
    • CD
    • CSD
    National Cannabis Survey (NCS)
    Survey details
    NCS 2018 (WAVE 1)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NCS2018W1 NCS2018W1 500 WTMP
    • MASTERID
    • DEM_30
    • VERDATE
    • DEM_25
    • CAN_40AA
    • CAN_40BA
    • CAN_40CA
    • CAN_40DA
    • CAN_40EA
    • CAN_40FA
    • CAN_40GA
    • CAN_40HA
    NCS 2018 (WAVE 2 NORTH)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NCS2018W2N NCS2018W2North 30 WTMP
    • MASTERID
    • DEM_30
    • VERDATE
    • DEM_25
    • CAN_40AA
    • CAN_40BA
    • CAN_40CA
    • CAN_40DA
    • CAN_40EA
    • CAN_40FA
    • CAN_40GA
    • CAN_40HA
    NCS 2018 (WAVE 2 SOUTH)
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NCS2018W2S NCS2018W2South 500 WTMP
    • MASTERID
    • DEM_30
    • VERDATE
    • DEM_25
    • CAN_40AA
    • CAN_40BA
    • CAN_40CA
    • CAN_40DA
    • CAN_40EA
    • CAN_40FA
    • CAN_40GA
    • CAN_40HA
    National Graduates Survey (NGS)
    Survey details
    NGS 1986
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS1986 NGS881 20 WGT
    • POPADJ
    • NGSID
    NGS 1990
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS1990 NGS1990 20 WEIGHT
    • INSTRO
    NGS 1990 FOG
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS1990FOG NGS1990FOG 20 WEIGHT
    • INSTRO
    NGS 1995
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS1995 NGS1995 20 S95GWGT
    • USNEW2
    • FQ5
    NGS 1995 FOG
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS1995FOG NGS1995FOG 20 FOGWTM
    • USNEW2
    • FQ5
    NGS 2000
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2000 NGS2000 20 WTPM
    •  
    NGS 2000 FOG
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2000FOG NGS2000FOG 20 FWTPM
    • SEQID
    • INTDATE
    • PRCCIP
    • ABCCIP
    • LFCCIP
    • EPCCIPa
    • EPCCIPb
    • EPCCIPc
    • EPCCIPd
    • EPCCIPe
    • EPCCIPf
    • EPCCIPg
    • ABCIND
    • LFCIND
    • EMNCINDa
    • EMNCINDb
    • EMNCINDc
    • EMNCINDd
    • EMNCINDe
    • EMNCINDf
    • ABCOCC
    • LFCOCC
    • EMNCOCCa
    • EMNCOCCb
    • EMNCOCCc
    • EMNCOCCd
    • EMNCOCCe
    • EMNCOCCf
    • FLFCIP1
    • FEPCIP1
    • FEPCIP2
    • FEPCIP3
    • FEPCIP4
    • FEPCIP5
    • FEPCIP6
    • FEPCIP7
    • FLFIND
    • FLFOCC
    • FLFOCCUS
    • AB_I28
    • LF_I85
    • LF_I88
    • LF_I89
    • E_I49a
    • E_I53a
    • E_I54a
    • E_I49b
    • E_I53b
    • E_I54b
    • E_I49c
    • E_I53c
    • E_I54c
    • E_I49d
    • E_I54d
    • E_I49e
    • E_I54e
    • SL_I07
    • SL_I11
    • SL_I14
    • SL_I15
    • SL_I23A
    • SL_I24A
    • SL_I26
    • SL_I28
    • DE_I34
    • DE_I36
    NGS 2005
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2005 NGS2005 20 WTPM  
    NGS 2010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2010 NGS2010 20 WTPM  
    NGS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2015 NGS2015 10 WTMF
    • LFCIND
    • LFCOCC
    • DEM_C040
    • PGMCIP
    • EDUCIP1
    • BEFCIP1
    NGS 2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGS2020 NGS2020 10 WTMF
    • PGMCIP21
    • EDUCIP21
    • EDUCIP4
    • LFCIND
    • LFCOCC
    • Gender
    • IM_01
    Nunavut Government Employee Survey (NGES)
    Survey details
    NGES 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGES2016 NGES 10 WTPM
    • MASTERID
    • NOC_2011
    • GEN_08
    • GEN_09
    • VERDATE
    NGES 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    NGES2021 NGES_2021 10 WTPM
    • REL_01
    • REL_02
    • NOC_2016
    • DDEPT
    • CUR_02
    Participation and Activity Limitation Survey (PALS)
    Survey details
    PALS: 2001
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PALS2001
    • ADULTS
    • CHILDREN
    • NONDISABLED
    100 WEIGHT DAYB
    PALS: pns2006
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PALS2006
    • PALS2006_ADULT
    • PALS2006_CHILD
    • PALS2006_NO_DISABILITY
    100 WEIGHT
    • CMA
    • CMA1
    • CMA5
    • CO1
    • CO5
    • CSDTYPEH
    • CSDTYPE1
    • CSDTYPE5
    • PCD1
    • PCD5
    • PCSD1
    • PCSD5
    • POB
    • POP1
    • POP5
    • PRCDDA
    • CSDCODE
    Portrait of Canadian Society (PCS)
    Survey details
    PCS 2021 Wave 1
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PCS2021W1
    • PCS2021W1
    500 WTMP
    • VERDATE
    • SACFLAG
    • CMA_FLAG
    • SEX
    PCS 2021 Wave 2
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PCS2021W2
    • PCS2021W2
    500 WTMP
    • VERDATE
    • SACFLAG
    • CMA_FLAG
    • SEX
    PCS 2021 Wave 3
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PCS2021W3
    • PCS2021W3
    500 WTMP
    • VERDATE
    • SACFLAG
    • CMA_FLAG
    • SEX
    Post-Secondary Education Participation Survey (PEPS)
    Survey details
    PEPS 2002
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PEPS2002 PEPS2002 500 FINWT
    • FRAME
    • CMATAB
    • STRAFRAM
    • TYPE
    • LISTLINE
    • URSTAT
    Public Service Employee Survey (PSES)
    Survey details
    PSES 2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2008 PSES2008 10
    • WTP_DEPT
    • WTP_PSL
    J_Q097
    PSES 2011
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2011 PSES2011 10 WT_PSL
    • MASTERID
    • L_Q90
    PSES 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2014 PSES 10 WT_PSL  
    PSES 2017
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2017 PSES2017 100 WT_PSL
    • MASTERID
    • UNITID
    • COLLMODE
    • LANG
    • VERDATE
    • M_Q112
    • FOL_REGN
    • FOLDV2
    • FOLDV3
    • FOLDV4
    • M_Q105B
    • M_Q106B
    PSES 2022 – Demographic File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2022DM PSES2022DM 10 WTPM
    • D105
    • IMPUTEF1
    • IMPUTEF2
    • IMPUTEF3
    • LINKFLAG
    • VERDATE
    • FOL_REGN
    • FOLDV2
    • FOLDV3
    • FOLDV4
    • Q109
    • Q114
    • Q115
    • Q105B
    • DEPTDV
    • DPTSIZE
    • OCCLEVEL
    • ORGUNIT
    • RCMP_Q45
    • RCMP_Q50
    • RCMP_Q55
    • RCMP_Q57
    • LEVEL2ID
    • LEVEL3ID
    • LEVEL4ID
    • LEVEL5ID
    • UNITID
    PSES 2022 – Organization File
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    PSES2022OG PSES2022OG 10 WTPM
    • IMPUTEF1
    • IMPUTEF2
    • IMPUTEF3
    • LINKFLAG
    • VERDATE
    • FOL_REGN
    • FOLDV2
    • FOLDV3
    • FOLDV4
    • Q115
    • FOLDV1
    • FOLDV5
    • FOLDV6
    • FOLDV9
    • FOLDV10
    • FOLDV11
    • FOLDV12
    • FOLDV13
    • FOLDV14
    • ORGUNIT
    • M_D105X1
    • M_D105X2
    • M_D105X3
    • UNITID
    • Q105A
    • OCCLEVEL
    • RCMP_Q55
    • RCMP_Q57
    • Q119A
    • Q119BA
    • Q119BB
    • Q119BC
    • Q119BD
    • DEPTDV
    • D122J
    • D122I
    • D122H
    • D122G
    • D122F
    • D122E
    • D122D
    • D122C
    • D122B
    • D122A
    • D122
    • D121
    • D120_2
    • D120_1
    • D119C
    • D119B
    • D119A
    • D119
    • D118K
    • D118J
    • D118I
    • D118H
    • D118G
    • D118F
    • D118E
    • D118D
    • D118C
    • D118B
    • D118A
    • D118
    • D117
    • Q122
    • Q122BA
    • Q122BB
    • Q122BC
    • Q122BD
    • Q122BE
    • Q122BF
    • Q122BG
    • Q122BH
    • Q122BI
    • Q122BJ
    • Q122BK
    • Q120A
    • Q120B
    • Q120C
    • Q120D
    • Q120E
    • Q120F
    • Q120G
    • Q120H
    • Q121A
    • Q121B
    • Q121C
    • Q121D
    • Q121E
    • Q121F
    • Q121G
    • Q121H
    • Q121I
    • Q121J
    • Q121K
    • Q121L
    • Q121M
    • Q121N
    • Q121O
    • Q121P
    • Q121Q
    • Q121R
    • Q121S
    • Q121T
    • Q121U
    • Q118BA
    • Q118BB
    • Q118BC
    • Q118BD
    • Q118BE
    • Q118BF
    • Q118BG
    • Q118BH
    • Q118BI
    • Q118BJ
    • Q118BK
    • Q118BL
    • Q118A
    • Q117
    • Q112
    • Q105B
    • Q106
    • D105

    Statistics Canada recommends that, whenever possible, all estimates of percentages (or proportions) from the PSES be assessed for fitness of use by reference to their confidence intervals (CIs). Intervals that are too wide, or that are based on too few responses, are less reliable - as are their associated estimates. As a rule of thumb, when approximately two-thirds of the employees in a group have responded to a question then the limit for confidentiality (10 respondents) is also a good limit for quality of the CI. When fewer than one-third have responded, 30 or more respondents to a question are recommended to have a reliable CI that will properly indicate the relative quality of the estimate.

    Residential Telephone Service Survey (RTSS)
    Survey details
    RTSS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    RTSS2013 RTSS 500 WTHM
    • CMA1
    • CMA34
    • CMATAB
    • ERTAB
    Survey of Approaches to Educational Planning (SAEP)
    Survey details
    SAEP 2002
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SAEP2002 SAEP2002 500 WTPM
    • URSTAT
    SAEP 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SAEP2013 SAEP 500 WTPM
    • CMATAB
    • ERTAB
    • UIRTAB
    Survey of Emergency Preparedness and Resilience in Canada (SEPR)
    Survey details
    SEPR 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SEPR2014 SEPR 250 WTPM
    • IMMDV01
    • REMDV01
    • DV2LANGA
    • DV2LANGB
    • DV2LANGC
    • DV3LANGA
    • DV3LANGB
    • DV3LANGC
    • CURLANG
    • INTVLANG
    • INTVDATE
    • CMA_ORIG
    • PR_CMACA
    • VERDATE
    • MASTERID
    Survey of Employees under Federal Jurisdiction (SEFJ)
    Survey details
    SEFJ 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SEFJ2022 SEFJ2022 20 WTMP
    • FJE_15A
    • FJE_20A
    • GDR_05
    • DEM_60_2
    • DEM_90
    • DV_IM01
    Survey of Financial Security (SFS)
    Survey details
    SFS 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Person File: SFS2012 SFS_PERSON 500 WEIGHT DOB
    Family File: SFS2012 SFS_FAMILY 500 WEIGHT DOB
    SFS 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Person File: SFS2016 SFS_PERSON 500 WEIGHT
    • MOB
    • DOB
    • AGE_I
    • DOB_I
    • MOB_I
    • YOB_I
    • LFCDPS_I
    • LFCESP_I
    • LFCHRS_I
    • LFCNW_I
    • LFCPD_I
    • LFCRSP_I
    • LFCSLF_I
    • LFCSTM_I
    • LFCSTY_I
    • LFCUNC_I
    • LFCUNM_I
    • LFCWK_I
    • NAICS_EE
    • NAICS_I
    • NOCS_EE
    • NOCS_I
    • PPCPMM_I
    • PPCPMY_I
    • PPCPPA_I
    • EDUC_I
    • EVERWA_I
    • EVERW_I
    • LFPFPT_I
    • LFPWKW_I
    • NAICS_HH
    • PNPERN_I
    • PNPEXM_I
    • PNPEXY_I
    • PNPMEM_I
    • PNPPAY_I
    • PNPSPD_I
    • PNPTM1_I
    • PNPTM2_I
    • PNPTM3_I
    • PNPTM4_I
    • PNPTM5_I
    • EFAMID
    • MASTERID
    • PERSONID
    • P_IALIM
    • P_IALIP
    • P_ICAPG
    • P_ICPQDS
    • P_ICPQP
    • P_IEIBE
    • P_IFMSE
    • P_IINVA
    • P_IINVT
    • P_IMPST
    • P_INFMS
    • P_IOTTX
    • P_IPENGV
    • P_IPENRC
    • P_IPRPEN
    • P_IRDSP
    • P_IRPPC
    • P_IRSPW
    • P_ISAPI
    • P_IUCCB
    • P_IUDPD
    • P_IWGSA
    • P_IWKRC
    • PIPAMT_I
    • PIPBRG_I
    • PIPID2_I
    • PIPID4_I
    • PIPIDX_I
    • PIPNET_I
    • PIPORP_I
    • PIPRCV_I
    • PIPTYP_I
    • RETAGE_I
    • RETIRE_I
    • MARST_I
    • SEX_I
    • CNTYCODE
    • DV1_CODE
    • DV2_CODE
    • DV3_CODE
    • DV2_LNGA
    • DV2_LNGB
    • DV2_LNGC
    • DV3_LNGA
    • DV3_LNGB
    • DV3_LNGC
    Family File: SFS2016 SFS_FAMILY 500 WEIGHT
    • ASRDWN_I
    • CDRES
    • CDRES11
    • CMA1G
    • CMA1G11
    • CMA2G
    • CMA2G11
    • CMACA
    • CMACA11
    • CMAPO
    • CMAPO11
    • CSDRES
    • CSDRES11
    • DARES
    • DARES11
    • DARES_I
    • ERRES
    • ERRES11
    • FEDRES
    • LATRES
    • LATRES11
    • LATRES_I
    • LNGRES
    • LNGRES_I
    • POSTCD
    • EFAMID
    • ATTBNK_I
    • ATTBUD_I
    • ATTCRC_I
    • ATTCRC_I
    • ATTCRL_I
    • ATTCRN_I
    • ATTCRR_I
    • ATTCRU_I
    • ATTDIF_I
    • ATTLCP_I
    • ATTLCR_I
    • ATTPAY_I
    • ATTRSA_I
    • ATTRSH_I
    • ATTRSL_I
    • ATTRSP_I
    • ATTRSR_I
    • ATTSIT_I
    • ATTSKP_I
    • ASR1MFAI
    • ASR1MF_I
    • ASR1MO_I
    • ASR1MR1I
    • ASR1MR2I
    • ASR1MR3I
    • ASR1MR4I
    • ASR1MR5I
    • ASR1MR6I
    • ASR1MR7I
    • ASR1MRAI
    • ASR1MR_I
    • ASR2MOYI
    • ASR2MO_I
    • ASR2MP1I
    • ASR2MP2I
    • ASR2MP3I
    • ASR2MP4I
    • ASR2MP5I
    • ASR2MP6I
    • ASR2MP7I
    • ASR2MP8I
    • ASR2M_I
    • ASRBUY_I
    • ASRCON_I
    • ASRCST_I
    • ASRCUR_I
    • ASRDIF_I
    • ASRDP01I
    • ASRDP02I
    • ASRDP03I
    • ASRDP04I
    • ASRDP05I
    • ASRDP06I
    • ASRDP07I
    • ASRDP08I
    • ASRDP09I
    • ASRDP10I
    • ASRDPA_I
    • ASRDPB_I
    • ASRDPP_I
    • ASRDP_I
    • ASRFRM_I
    • ASRFSL_I
    • ASRINH_I
    • ASRINTRI
    • ASRINT_I
    • ASRMM_I
    • ASRMPF_I
    • ASRMTG_I
    • ASRMY_I
    • ASROWN_I
    • ASRPCT_I
    • ASRSEL_I
    • ASRSHR_I
    • ASRSKP_I
    • EXMG1A_I
    • EXMG1F_I
    • EXMG1I_I
    • AS1RECTI
    • AS1REC_I
    • AS1REFTI
    • AS1REF_I
    • AS2RECTI
    • AS2REC_I
    • AS2REFTI
    • AS2REF_I
    • AS3RECTI
    • AS3REC_I
    • AS3REFTI
    • AS3REF_I
    • AS4RECTI
    • AS4REC_I
    • AS4REFTI
    • AS4REF_I
    • DB1MGC_I
    • DB1MGF_I
    • DB2MGC_I
    • DB2MGF_I
    • DB3MGC_I
    • DB3MGF_I
    • DB4MGC_I
    • DB4MGF_I
    • DBT1MGCI
    • DBT1MGFI
    • DBT2MGCI
    • DBT2MGFI
    • DBT3MGCI
    • DBT3MGFI
    • DBT4MGCI
    • DBT4MGFI
    • ASSRECNI
    • ASSREC_I
    • ASSREFNI
    • ASSREF_I
    • ASSVEH_I
    • ASSVNM_I
    • ASSVOTNI
    • ASSVOT_I
    • AS1VVL_I
    • AS2VVL_I
    • AS3VVL_I
    • AS4VVL_I
    • DB1CAR_I
    • DB2CAR_I
    • DB3CAR_I
    • DB4CAR_I
    • DBT1CARI
    • DBT2CARI
    • DBT3CARI
    • DBT4CARI
    • AS1VOT_I
    • AS1VTT_I
    • AS2VOT_I
    • AS2VTT_I
    • AS3VOT_I
    • AS3VTT_I
    • AS4VOT_I
    • AS4VTT_I
    • DB1VEH_I
    • DB2VEH_I
    • DB3VEH_I
    • DB4VEH_I
    • DBT1VEHI
    • DBT2VEHI
    • DBT3VEHI
    • DBT4VEHI
    • ASS401TI
    • ASS401_I
    • ASSANNTI
    • ASSANN_I
    • ASSBNDTI
    • ASSBND_I
    • ASSCSBTI
    • ASSCSB_I
    • ASSDPSTI
    • ASSDPS_I
    • ASSESPTI
    • ASSESP_I
    • ASSGICTI
    • ASSGIC_I
    • ASSITTI
    • ASSIT_I
    • ASSLIFTI
    • ASSLIF_I
    • ASSLIRTI
    • ASSLIR_I
    • ASSMNMTI
    • ASSMNM_I
    • ASSMUTTI
    • ASSMUT_I
    • ASSOIVTI
    • ASSOIV_I
    • ASSRIFOI
    • ASSRIF_I
    • ASSRSPTI
    • ASSRSP_I
    • ASSSAVTI
    • ASSSAV_I
    • ASSSHRTI
    • ASSSHR_I
    • ASSSTKTI
    • ASSSTK_I
    • ASSSTPI
    • ASSTBLTI
    • ASSTBL_I
    • ASSTFSTI
    • ASSTFS_I
    • ASSCOLTI
    • ASSCOL_I
    • ASSCON_I
    • ASSOTHTI
    • ASSOTH_I
    • DBTCRCTI
    • DBTCRC_I
    • DBTDEFTI
    • DBTDEF_I
    • DBTLCHTI
    • DBTLCH_I
    • DBTLCOTI
    • DBTLCO_I
    • DBTLNOTI
    • DBTLNO_I
    • DBTMNOTI
    • DBTMNO_I
    • DBTOCCTI
    • DBTOCC_I
    • STLAMT_I
    • STLOANNI
    • STLOAN_I
    • STLOWA_I
    • BUSINDNI
    • BUSIND_I
    • BUSBVL1I
    • BUSBVL2I
    • BUSBVL3I
    • BUSDBT1I
    • BUSDBT2I
    • BUSDBT3I
    • BUSFAR1I
    • BUSFAR2I
    • BUSFAR3I
    • BUSFIB1I
    • BUSFIB2I
    • BUSFIB3I
    • BUSFIM1I
    • BUSFIM2I
    • BUSFIM3I
    • BUSINC1I
    • BUSINC2I
    • BUSINC3I
    • BUSMKT1I
    • BUSMKT2I
    • BUSMKT3I
    • BUSMVT1I
    • BUSMVT2I
    • BUSMVT3I
    • BUSPCT1I
    • BUSPCT2I
    • BUSPCT3I
    • BUSSEC1I
    • BUSSEC2I
    • BUSSEC3I
    • NAICS_S1
    • NAICS_S2
    • NAICS_S3
    • FPLINH_I
    • FPLINS_I
    • FPLINV_I
    • INHERT_I
    SFS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Person File: SFS2019PER SFS2019PER 500 WEIGHT
    • DOB
    • MOB
    • CNTYCODE
    • DV1_CODE
    • DV2_CODE
    • DV3_CODE
    • DV2_LNGA
    • DV2_LNGB
    • DV2_LNGC
    Family File: SFS2019FAM SFS2019FAM 500 WEIGHT
    • CDRES
    • CMA1G
    • CMACA
    • CMAPO
    • DARES
    • CSDRES
    • ERRES
    • FEDRES
    • LATRES
    • LNRES
    • POSTCD
    • SACTYPE
    • BUSYR1
    • BUSYR2
    • BUSYR3
    • NAICS_S1
    • NAICS_S2
    • NAICS_S3
    SFS 2023
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    Person File: SFS2023PER SFS2023PER 500 WEIGHT
    • VERDATE
    • DOB
    • MOB
    • GENDER
    • SEXAB
    • CNTYCODE
    • NAICS_EE
    • NAICS_HH
    • NOCLMA
    Family File: SFS2023FAM SFS2023FAM 500 WEIGHT
    • CDRES
    • CMA1G
    • CMACA
    • CMAPO
    • DARES
    • CSDRES
    • ERRES
    • FEDRES
    • LATRES
    • LNGRES
    • POSTCD
    • SACTYPE
    • BUSYR1
    • BUSYR2
    • BUSYR3
    • NAICS_S1
    • NAICS_S2
    • NAICS_S3
    • SEXABMIE
    Survey of Household Spending (SHS)
    Survey details
    SHS 2004
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2004 SHS2004 200 WEIGHT
    • CASEID
    • METRO
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • HHSZD31
    • P04D31
    • P514D31
    • P1519D31
    • P2024D31
    • A2564D31
    • SE65D31
    • F413D31
    • F14D31
    • M413D31
    • M14D31
    • P015D31
    • P16D31
    • C04YE
    • C514YE
    • Y1519YE
    • P2024YE
    • P2564YE
    • P65YE
    • C015TOT
    • A16TOT
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMWKS
    • HHSZTOT
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • HHSIZYE
    • NUMVEHON
    • VEHLEASD
    • RPAGE
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2005 North
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2005N SHS2005N 100 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • HHSZD31
    • P04D31
    • P514D31
    • P1519D31
    • P2024D31
    • A2564D31
    • SE65D31
    • F413D31
    • F14D31
    • M413D31
    • M14D31
    • P015D31
    • P16D31
    • C04YE
    • C514YE
    • Y1519YE
    • P2024YE
    • P2564YE
    • P65YE
    • C015TOT
    • A16TOT
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMWKS
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • HHSIZYE
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2005 South
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS 2005S SHS 2005S 200 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • HHSZD31
    • P04D31
    • P514D31
    • P1519D31
    • P2024D31
    • A2564D31
    • SE65D31
    • F413D31
    • F14D31
    • M413D31
    • M14D31
    • P015D31
    • P16D31
    • C04YE
    • C514YE
    • Y1519YE
    • P2024YE
    • P2564YE
    • P65YE
    • C015TOT
    • A16TOT
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMWKS
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • HHSIZYE
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2006
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2006 SHS2006 200 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • HHSZTOT
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPAGE
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2007 North
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2007N SHS2007N 100 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2007 South
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2007S SHS2007S 200 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2008 SHS2008 200 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • HHSZTOT
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPAGE
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2009 North
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2009N SHS2009N 100 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2009 South
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHS2009S SHS2009S 200 WEIGHT
    • CASEID
    • METRO
    • ER
    • CD
    • CSD
    • STRATUM
    • TYPE
    • CLUSTER
    • P04TOI
    • P514TOI
    • P1519TOI
    • P2024TOI
    • A2564TOI
    • SE65TOI
    • F413TOI
    • F14TOI
    • M413TOI
    • M14TOI
    • P015TOI
    • P16TOI
    • AGEYOUNG
    • AgeHusbandOrRefPers
    • AgeHusband
    • AgeWife
    • NUMFT
    • NUMPT
    • YRMOVED
    • V138
    • NumDwgOwnOcc
    • NumMonthsOwnOcc
    • NumMonthsOccRentDwg
    • RQNUMBED
    • NUMVEHON
    • VEHLEASD
    • RPWEEKFT
    • RPWEEKPT
    • SPAGE
    • SPWEEKFT
    • SPWEEKPT
    • URBSIZE
    SHS 2010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2010C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    Diary File: SHS2010D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    SHS 2011
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2011C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    Diary File: SHS2011D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    SHS 2012
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2012C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    Diary File: SHS2012D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    • RVNUM
    • VEHNUM
    SHS 2013
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2013C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    Diary File: SHS2013D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • PERSONNO
    SHS 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2014C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    Diary File: SHS2014D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    SHS 2015
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2015C SHS_CAPI 500 WEIGHTC
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    Diary File: SHS2015D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CSDuid
    SHS 2016
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2016C SHS_CAPI 500 WEIGHTC
    • CollMth
    • CASEID
    • DATE_Q02
    • Personno
    • UrbanSize
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDuid
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    Diary File: SHS2016D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    SHS 2017 Rebased Files
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2017C SHS_CAPI 500 WEIGHTC
    • CollMth
    • CASEID
    • CMACA
    • UrbanSize
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDuid
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    Diary File: SHS2017D SHS_DIARY 1000 WEIGHTD
    • CASEID
    • CollMth
    • CSDuid
    • UrbanSize
    • CMACA
    • CITY
    • ECONOMICREGION
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    SHS 2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File Household: SHS2019CH HHLD_C 500 WEIGHTC
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CMACA
    • CASEID
    • TE_Q060
    Diary Household File: SHS2019DH HHLD_D 1000 WEIGHTD
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CMACA
    • CASEID
    • TE_Q060
    SHS 2010 to 2013 Pooled Files
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS201013C SHS_CAPI 50 WEIGHTC
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    Diary File: SHS201013D SHS_DIARY 100 WEIGHTD
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    SHS 2012 to 2015 Pooled Files
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS201215C SHS_CAPI 50 WEIGHTC
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    Diary File: SHS201215D SHS_DIARY 100 WEIGHTD
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    SHS 2014 to 2017 Pooled Files
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS201417C SHS_CAPI 50 WEIGHTC
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    Diary File: SHS201417D SHS_DIARY 150 WEIGHTD
    • COLLMTH
    • CVR_HHLDSTRATUM
    • CVR_HHLDTYPE
    • CVR_HHLDCLUSTER
    • CITY
    • URBANSIZE
    • CENSUSDIVISION
    • CENSUSSUBDIVISION
    • CSDUID
    • ECONOMICREGION
    • CASEID
    SHS 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    CAPI File: SHS2021CH SHS2021CH 500 WEIGHTC
    • CASEID
    • COLLMTH
    • STRATUM
    • TYPE
    • CLUSTER
    • CITY
    • URBSIZE
    • CD
    • CSD
    • CSDUID
    • ECREGION
    • CMACA
    • DA
    • TE_Q060
    Diary File: SHS2021DH SHS2021DH 1000 WEIGHTD
    • CASEID
    • COLLMTH
    • STRATUM
    • TYPE
    • CLUSTER
    • CITY
    • URBSIZE
    • CD
    • CSD
    • CSDUID
    • ECREGION
    • CMACA
    • DA
    • TE_Q060
    Survey of Labour and Income Dynamics (SLID)
    Survey details
    SLID
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SLIDQRY SLIDQRY 1000 RTRAVAR
    • CA
    • CMA
    Survey of Older Workers (SOW)
    Survey details
    SOW 2008
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SOW2008 SOW2008 500 WTPM
    • CMATAB
    • CMA
    • GCMA
    • ERTAB
    Survey of Young Canadians (SYC)
    Survey details
    SYC 2010
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SYC2010 SYC_CHILD 250 WTPM
    • PSTRAT
    • NOCP4
    • NOCS4
    • NAICSP4
    • NAICSS4
    • INTVDATE
    • PCODE
    • DAUID
    • CMACA
    Survey on Access to Health Care and Pharmaceuticals During the Pandemic (SAHCPDP)
    Survey details
    SAHCPDP 2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SAHCPDP21 SAHCPDP21 100 WTS_M  
    Survey on Before and After School Care in Canada (SBASCC)
    Survey details
    SBASCC 2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SBASCC2022 SBASCC2022 100 WTMP
    • VERDATE
      AGE_01C
      PMK_35C
    Survey on Early Learning and Child Care Arrangements (SELCCA)
    Survey details
    SELCCA2019
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SELCCA2019 SELCCA 1000 WTPM
    • MASTERID
    • PMK_35C
    • AGE_01C
    • VERDATE
    • AGE_01A
    • PMK_AGE
    SELCCA2020
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SELCCA2020 SELCCA_2020 100 WTMP
    • VERDATE
    • MASTERID
    • PMK_AGE
    • AGE_01A
    • AGE_01C
    • PMK_35C
    SELCCA2022
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SELCCA2022 SELCCA_2022 100 WTMP
    • VERDATE
    • MASTERID
    • PMK_AGE
    • AGE_01A
    • AGE_01C
    • PMK_35C
    Survey on Health Care Workers’ Experiences During the Pandemic (SHCWEP)
    Survey details
    SHCWEP2021
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SHCWEP2021 SHCWEP2021 50 WTS_M  
    Survey on Living with Chronic Diseases in Canada (SLCDC): Arthritis
    Survey details
    SLCDC 2009A
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SLCDC2009A SLCDC2009A 500 WTSX_S
    • GEODPC
    • GEODHR4
    • GEODLHN
    • GEODDA06
    • GEODDA01
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • GEODCMA1
    • GEODPRG
    • GEOXDREG
    • GEODUR
    • GEODUR2
    • GEODPSZ
    Survey on Living with Chronic Diseases in Canada (SLCDC): Diabetes and Respiratory Conditions
    Survey details
    SLCDC 2011
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SLCDC2011
    • DIAB
    • RESP
    500 WTSX_S
    • SAMPLEID
    • ADMX_N12
    • ADMX_LHH
    • ADMX_YOI
    • ADMX_MOI
    • ADMX_DOI
    • ADMX_01
    • ADMX_02
    • ADMX_03
    • ADMX_06
    • ADMX_11
    • ADMX_12
    • ADMX_13
    • ADMX_14
    • SAMDSHR
    • SAMDLNK
    • VERDATE
    • REFPER
    • GEODPC
    • GEODDA06
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • SAM_CP
    • SAM_TYP
    • ADM_STA
    • ADM_PRX
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • ADM_LHH
    • DHH_DOB
    • INWCSIC
    • INWCSOC
    • LBSCSIC
    • LBSCSOC
    • SDC_1
    • SDCCCB
    • INCDADR
    Survey on Living with Chronic Diseases in Canada (SLCDC): Hypertension
    Survey details
    SLCDC 2009H
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SLCDC2009H SLCDC2009H 500 WTSX_S
    • GEODPC
    • GEODHR4
    • GEODLHN
    • GEODDA06
    • GEODDA01
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODCMA6
    • GEODCMA1
    • GEODPRG
    • GEODUR
    • GEODUR2
    • GEODPSZ
    Survey on Living with Chronic Diseases in Canada (SLCDC): Mood and Anxiety Disorders
    Survey details
    SLCDC 2014
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SLCDC2014 SLCDC 500 WTSX_S
    • VERXDATE
    • ADMX_N12
    • ADMX_LHH
    • INTXDATE
    • ADMX_Y01
    • ADMX_M01
    • ADMX_D01
    • ADMX_02
    • ADMX_03
    • ADMX_04
    • VERDATE
    • REFPER
    • PERSONID
    • GEODCMAA
    • GEODDA11
    • GEODPC
    • GEODDA06
    • GEODFED
    • GEODCSD
    • GEODCD
    • GEODSAT
    • GEODSUBZ
    • SAMP_CP
    • SAM_TYP
    • CASETYPE
    • SAMDSHR
    • SAMDLNK
    • ADM_STA
    • ADM_PRX
    • ADM_YOI
    • ADM_MOI
    • ADM_DOI
    • ADM_N09
    • ADM_N10
    • ADM_N11
    • ADM_N12
    • DHH_DOB
    • SDCCCB13
    • SDCC5B1
    • SDCC5B2
    • SDCC5B3
    • SDCC61
    • SDCC62
    • SDCC63
    • INWCSIC
    • INWCSOC
    • INCFIMP4
    • INCDADR
    • LBSCSIC
    • LBSCSOC
    Survey on Maternal Health (SMH)
    Survey details
    SMH 2018
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SMH2018 SMH 10 WTPM
    • COL_MODE
    • COL_LANG
    • COL_DATE
    • VERDATE
    • MASTERID
    • DEM1_15
    • DEM1_20
    • EXPDAGEC
    Survey Series on First Nations People, Métis and Inuit (SSFNPMI)
    Survey details
    SSFNPMI 2024 – Wave 1
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SSFNPMI SSFNPMI 100 WGT
    • SEX
    • GENDER3
    • DHLOS
    • SOR_01
    SSFNPMI 2024 – Wave 2
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SSFNPMI2 SSFNPMI2 100 WGT
    • PINCFL_I
    • DHLOS
    • SOR_01
    SSFNPMI 2024 – Wave 3
    Tag Name Dataset Name Rounding Base Weight Name Deleted Variables
    SSFNPMI3 SSFNPMI3 100 WGT
    • PINCFL_I
    • DHLOS
    • SOR_01

    Application process and guidelines- DLI

    The form “DLI Program Membership” must be completed to apply for the Data Liberation Initiative (DLI) program.

    If you wish to access Postal Code Conversion File (PCCF), the Social Policy Simulation Database and Model (SPSD/M) or the Discharge Abstract Database (DAD), please complete the Section 1, Section 2 and Section 3 forms.

    Supporting documents for application

    To access the program Membership Form and Licences, please select from the links below:

    Fees - DLI

    Institutions belonging to the Canadian Association of Research Libraries (CARL) pay $12,000 per year. The non-CARL institutions pay $3,000 per year.

    A Data Liberation Initiative (DLI) annual membership runs from April 1st to March 31st. Institutions can join at any time of the year at a prorated fee.

    Training and events - DLI

    Calendar of events

    List of upcoming Data Liberation Initiative (DLI) regional training sessions, webinars and events.

    Meetings and regional training

    The next External Advisory Committee Members meeting dates will be held on: 

    • May 13th, 2024
    • October 7th, 2024
    • December 2nd, 2024
    •  February 10th, 2025

    The next DLI Training event will be held during the week of May 27, 2024.

    Let us know what you'd like to see at the next DLI Training! Get in touch with your regional training coordinator with your ideas.

    Check out the Event Archive for details about past DLI Training events.

    Training materials

    DLI Survival Guide
    This Guide serves as a reference document for DLI contacts at participating institutions across Canada.

    DLI Training Repository
    The Training Repository contains presentations from DLI training sessions and workshops. The Repository also contains other related presentations and workshops, both national and international.

    Governance - DLI

    Governance structure

    • 1. Program definition

      1. Program definition

      This program is a partnership between Statistics Canada and registered Canadian post-secondary educational institutions to promote and facilitate the availability of Statistics Canada and other Canadian data for educational and academic research purposes.

    • 2. Objectives

      2. Objectives

      1. To promote a culture of data use in Canadian post-secondary educational institutions.
      2. To facilitate access to Canadian public data in support of teaching and academic research.

      The Data Liberation Initiative (DLI) program will undertake many initiatives to achieve these objectives. The initiatives are outlined in the DLI Strategic Plan for discussion at the External Advisory Committee (EAC) Meetings.

    • 3. Governance structure

      3. Governance structure

      There will be a body known as the Data Liberation Initiative External Advisory Committee (DLI-EAC) whose roles and membership are outlined below.

    • 4. Terms of reference of the External Advisory Committee:

      4. Terms of reference of the External Advisory Committee:

      1. The External Advisory Committee shall:
        1. identify and respond to the needs and priorities of post-secondary educational institutions for appropriate data, metadata and dissemination;
        2. advise Statistics Canada on appropriate initiatives and ways of implementing them to meet the objectives of the DLI;
        3. advise Statistics Canada on the development and distribution of new products and formats and services in support of data, metadata and dissemination activities;
        4. suggest and promote initiatives for Statistics Canada to increase accessibility to services and standard data products;
        5. promote and communicate the activities of the EAC to DLI institutions;
        6. form a standing sub-committee on training and education responsible for the ongoing development of a data services curriculum for post-secondary staff supporting the DLI. This sub-committee will consist of nine (9) academic members made up of the two Regional Training Co-ordinators, or designate, from each of the four regions, and a Chair who shall serve as an ex-officio member of the EAC. Regional Training Co-ordinators shall be appointed for a term of four (4) years. These terms may be extended. The Committee will also contain appropriate members from the DLI area of Statistics Canada. This Committee will normally convene at least once a year;
        7. form other sub-committees as needed;
        8. pricing will be on the agenda of the EAC at every meeting.
      2. Statistics Canada shall endeavour to respond to the advice and guidance of the EAC to the extent possible.
    • 5. Membership

      5. Membership

      1. There will be two (2) types of members, voting members and ex-officio (non-voting) members.
      2. Up to nine (9) voting members from outside of Statistics Canada shall be appointed based on the following criteria, see Appendix 1 for additional information:
        1. these members will be either practicing data librarians, researchers or administrators of DLI member institutions;
        2. administrators of post-secondary educational institutions may come from either the research and/or the library streams;
        3. members will be drawn from both large and small institutions;
        4. up to two (2) representatives will be drawn from each of the four (4) DLI regions of Canada: Atlantic, Quebec and Nunavut, Ontario and the West (Prairie, Pacific, Yukon and North West Territories);
        5. one (1) member shall be the senior library administrator of a DLI member institution
      3. Voting members from inside of Statistics Canada will consist of:
        1. the Director responsible for the DLI;
        2. the Chief or Manager responsible for the DLI Section;
        3. up to three (3) members from data producing or other divisions.
      4. Ex-officio (non-voting) members will include:
        1. other members of the DLI Section;
        2. the Executive Director of the Canadian Research Data Centre Network (CRDCN) or delegate;
        3. the Chair of the Professional Development Committee;
        4. research data management representative.
      5. Statistics Canada may, upon the advice of the EAC, invite additional members to committee meetings to act as principal or fiduciary advisors from additional educational institutions and/or data producers.
    • 6. Modus Operandi

      6. Modus Operandi

      1. The EAC will normally meet annually in the fall in person and by teleconference in the spring;
      2. The EAC will elect Co-Chair(s) to serve two years terms who have as responsibility to preside over the EAC meetings. Elections will take place on alternating years as the term for the Co-Chair(s) end;
      3. The academic members of the EAC shall be invited to serve four year terms. Affected membership will be reviewed regularly;
      4. An Executive Committee comprised of the Chair(s), the Director, the Assistant Director and the Manager responsible for the DLI will identify and invite new members to serve as required;
      5. Statistics Canada will provide the secretarial support for the committee;
      6. The DLI Status reports will be prepared for each of the EAC meetings. The report will be disseminated through the Listserv and made available on the DLI repository for the information of the data user community;
      7. The EAC and Statistics Canada shall review these terms of reference as required;
      8. Reviewing the DLI Strategic Plan;
        1. the Cornerstone Principles of the DLI will be reviewed every 3 years by the EAC;
        2. the Project Roadmap and reporting:
          1. current projects will be reported on through status reports presented to the EAC:
            1. a formal report is to be presented at the fall EAC in-person meeting;
            2. status reports are to be shared with the EAC mid-year via a teleconference;
          2. strategic opportunities and upcoming projects section will be introduced at each meeting to get feedback from the EAC on potential projects for the DLI program to pursue.
    • 7. Appendix 1

      7. Appendix 1

      Committee member selection criteria for voting members

      External Advisory Committee
      • All nominees for EAC members must be from an institution member in good standing;
      • Candidates must be willing to commit to attending one face-to-face board meeting per year, plus a minimum of one committee conference call per year;
      • Candidates who serve on the EAC must also be willing to commit to participating in EAC sanctioned Working Group activities;
      • Candidates are expected to be ethical, strategic thinkers who understand the DLI partnership and the committee process;
      • Candidates for Co-Chair(s) must have had at least one (1) year, but preferably one full term, of prior experience on the EAC.

      In order to fill gaps left by departing members, the committee terms of reference are applied, current expertise needs are evaluated and the gaps filled accordingly keeping in mind the need for language capabilities, geographical distribution of members, gender balance, minimizing Conflicts of Interest (COI), etc.

      The EAC Executive retains the final word on EAC membership but does extensively consult as required.

    • 8. External Advisory Committee Members

      8. External Advisory Committee Members

      Co-chair
      Siobhan Hanratty
      Data/GIS Librarian
      University of New Brunswick
      506-451-6803
      hanratty@unb.ca

      Co-chair
      Elizabeth Hill
      Data Librarian
      Western University
      519-661-2111 ext. 85049
      ethill@uwo.ca

      Senior Library Administrator
      Vacant

      Atlantic region

      Martin Chandler
      GIS and Data Services Librarian
      Cape Breton University
      902-563-1996
      martin_chandler@cbu.ca

      Quebec region

      Alex Guindon
      GIS and Data Services Librarian
      Concordia University
      514-848-2424 ext. 7754
      alex.guindon@concordia.ca

      Nathalie Vachon
      Data Librarian
      Institut national de la recherche scientifique
      514-499-4079
      nathalie.vachon@inrs.ca

      Ontario region

      Jane Fry
      Data Services Librarian
      Carleton University
      613-520-2600 ext. 1121
      jane.fry@carleton.ca

      Western region

      Carla Graebner
      Librarian for Data Services and Government Information
      Simon Fraser University
      778-782-6881
      cgraebne@SFU.ca

      Sarah Rutley
      Data & GIS Librarian
      University of Saskatchewan
      306-966-5988
      sarah.rutley@usask.ca

      Non-academic members

      Geneviève Jourdain
      Director, Data Access Division
      Statistics Canada
      613-889-1941
      genevieve.jourdain@statcan.gc.ca

      Nicole Huard
      Chief Data Access Division
      Statistics Canada
      nicole.huard@statcan.gc.ca

      Mariane Bien-Aimé
      Assistant Director, Consumer Prices Division
      Statistics Canada
      343-998-3438
      mariane.bien-aime@statcan.gc.ca

      Glen Hohlmann
      Assistant Director, Census Operations Division
      Statistics Canada
      613-325-7866
      glen.hohlmann@statcan.gc.ca

      Cory Chobanik
      Assistant Director, Office of Privacy Management and Information Coordination
      Statistics Canada
      613-697-2974
      cory.chobanik@statcan.gc.ca

      Ex-officio members

      Johanne Provençal
      Research Program Director, Canadian Research Data Centre Network
      McMaster University
      905-525-9140 ext. 23661
      johanne.provencal@crdcn.ca

      Arden Kayzak
      Unit Head, Data Access Division
      Statistics Canada
      613-854-4251
      arden.kayzak@statcan.gc.ca

      Sara Tumpane
      Unit Head, Data Access Division
      Statistics Canada
      416-970-0453
      sara.tumpane@statcan.gc.ca

      Alexandra Cooper
      Chair, Professional Development Committee
      Queen's University
      613-533-6000 ext. 77481
      coopera@queensu.ca

    Education and training structure

    • 1. Committee definition

      1. Committee definition

      The Professional Development (PD) Committee is a standing committee on training and education for post-secondary staff supporting the DLI.

      The Committee is accountable to the External Advisory Committee (EAC) and will bring all of its deliberations and recommendations to the EAC for approval.

    • 2. Objectives

      2. Objectives

      The Professional Development Committee will be responsible for the ongoing development of a data services curriculum for post-secondary staff supporting the DLI at their institution and for the support of national and regional DLI training activities. The Committee will monitor all aspects of the DLI Training Program including: frequency of training workshops, budget allocations, curriculum, trainers, special training requirements, etc.

      The Committee supports the promotion of statistical and data literacy to the wider community in which the DLI exists, namely library directors, data users, Statistics Canada survey managers and other groups within the data realm. This includes promoting the DLI Program as well as fostering a deeper understanding of the substance of DLI as well as of data, and statistical and quantitative reasoning.

    • 3. Membership

      3. Membership

      The Professional Development Committee will consist of nine academic members including the two Regional Training Coordinators (RTCs) from each of the four regions and a Chair who will serve as an ex-officio member of the EAC. The Committee will also contain appropriate members from the Microdata Access Division of Statistics Canada.

      The academic members of the PD Committee will be invited to serve a four year term. After one term, the member may be asked if he/she would like to continue as a member. If yes, the member's application will be presented to the EAC to be reappointed to the PD committee. After two terms (eight years), a call out should be made to see if someone else from the represented region would like to become a member. If there is no interest and the current member wishes to continue, it will be recommended to the EAC that the person be appointed for another four year term.

      The Committee will nominate a Chair to the EAC Executive taking into consideration the principles of inclusiveness, regionality and collegiality. This person can be anyone from a DLI member institution.The EAC Executive will present this nomination to the EAC for final approval. In the absence of the PD Committee identifying someone, the EAC Executive will nominate someone as Chair for final approval by the EAC. The Chair will be invited to serve a four year term, with the possibility of renewal.

      The Committee will identify potential candidates and make recommendations to the EAC Executive for the positions of RTCs. This Committee will normally convene at least once every year. Proposals for a PD Committee meeting may come from a Regional Training Coordinator or from the Chair. The Professional Development Committee will form other sub-committees as required.

    • 4. Training roles

      4. Training roles

      Regional training co-ordinators

      The PD Committee will recommend two academic representatives from each of the four regions, Atlantic, Quebec, Ontario and the West to serve as RTCs. The responsibilities of these training coordinators are:

      • To identify the training needs within their region;
      • To communicate these needs to the Professional Development Committee both for the purpose of budgeting for training and for coordinating national training activities;
      • To arrange local training events;
      • To design their local region's training program.

      DLI trainers

      Whenever possible, trainers will be recruited from the existing Canadian data library community with the expectation that those who are trained may be called upon to train others. This principle is founded on the understanding that as one learns, one will teach.

      Trainers for a regional training workshop may be RTCs but they may also be other individuals in the region or from other regions where the required expertise exists. Since the RTCs are primarily responsible for local arrangements, planning the program of training events, and communicating training needs to the PD Committee, they may call upon other members to do the actual hands-on training at the workshops.

    • 5. Professional Development Committee members

      5. Professional Development Committee members

      Chair: Alexandra Cooper
      Data Services coordinator
      Queen's University
      613-533-6000 ext. 77481
      coopera@queensu.ca

      Atlantic region

      Sandra Sawchuk
      Liaison Librarian
      Mount Saint Vincent University
      902-457-6526
      sandra.sawchuk@msvu.ca

      Margaret Vail
      Liaison Librarian
      St. Francis Xavier University
      902-867-4869
      mvail@stfx.ca

      Québec region

      Vacant

      Giovanna Badia
      Assessment & Data Librarian
      McGill University
      514-398-7504
      giovanna.badia@mcgill.ca

      Ontario region

      Vivek Jadon
      Data Specialist
      McMaster University
      905-525-9140 ext. 23848
      vivek@mcmaster.ca

      Chantal Ripp
      Data Librarian
      University of Ottawa
      613-562-5800 ext. 3881
      chantal.ripp@uottawa.ca

      West region

      Robyn Stobbs
      Research Data Management Librarian
      Athabasca University
      780-213-2011
      stobbs@athabascau.ca

      Tara Stieglitz
      Data Services and Science Librarian
      MacEwan University
      780-497-5850
      StieglitzT@macewan.ca

      College member

      Caleb Domsy
      Librarian
      Humber College
      416-675-6622 ext. 4501
      Caleb.Domsy@humber.ca

      Non-academic members

      Nicole Huard
      Chief, Data Access Division (DAD)
      Statistics Canada
      nicole.huard@statcan.gc.ca

      Arden Kayzak
      Unit Head, Data Access Division (DAD)
      Statistics Canada
      613-854-4251
      arden.kayzak@statcan.gc.ca

    Training principles

    The pedagogical foundations of the Data Liberation Initiative Training Program

    • Principle 1

      Principle 1

      Training under this program is being conducted specifically for:

      1. DLI Contacts and/or DLI Alternates at participating post-secondary institutions;
      2. Staff who will provide services for DLI data at these institutions;
      3. Statistics Canada staff directly involved in the support of DLI, and;
      4. Students from library schools, when possible.

      Notes:

      • Others may benefit from DLI workshops, but these above mentioned groups remain the focus in the design and delivery of DLI training.
      • Each year one person from each institution is eligible to receive a financial subsidy, but a member institution can send as many staff as they wish to DLI training workshops subject to local circumstances.
      • Depending on the availability of seats, institutions considering membership in DLI are welcome to send participants at their own expense.
    • Principle 2

      Principle 2

      Training will be provided to all of those eligible under the first principle through a variety of formats, including subsidized workshops that are delivered regionally.

      Notes:

      • This principle recognizes the importance of existing regional cooperation within the academic library community and specifically contributes to inter-institutional partnerships in the area of statistical and data resources.
      • Conducting workshops regionally strengthens the network of data services providers by bringing them together at least annually face-to-face.
      • Organizing training regionally helps overcome the vast geography of Canada and to address specific needs and interests of the institutions and DLI Contact in Canadian regions.
      • The DLI training program will:
        • Accommodate different learning styles.
        • Increase access to workshops by providing some financial assistance.
        • Employ a variety of training formats, including in-person and remote.
        • Provide a repository of training materials.
    • Principle 3

      Principle 3

      The first training priority is to establish core competencies for basic level of data service skills for DLI Contacts and Alternates (Appendix 1). This training shall be considered the entry level required to work with DLI data. More advanced training will build upon previous levels. Priorities for advanced levels will be determined by the needs of those supporting data services and by the evolution of DLI.

      Notes:

      • An established baseline of skill competencies in working with DLI resources is a first priority.
      • Skills that go beyond the baseline competencies will also be provided through DLI workshops.
      • The advanced skills will reflect both the needs of those providing data services support and new skills required to support changes in DLI products.
    • Principle 4

      Principle 4

      All training will be conducted from a 'service' perspective, that is, from a point of view that focuses on the clientele using DLI data. The purpose of this training is to prepare data services staff to assist their clients with DLI data.

      Notes:

      • A "service perspective" is important because it keeps training focused on knowing how to support DLI resources.
      • DLI training is intended to transfer the skills needed by those individuals who will be assisting the end-users of DLI resources. The data service providers are not usually seen as the end-users.
      • DLI training will teach some statistical and research skills to enhance understanding in providing data services but it is not intended to teach trainees how to become statisticians or social researchers.
    • Principle 5

      Principle 5

      The training matrix (Appendix 2) will guide the course content that is offered through this program. The DLI External Advisory Committee (EAC), through its Professional Development Committee, will be responsible for maintaining this plan and for periodically reviewing its content and direction.

      Notes:

      • The EAC has an on-going Professional Development Committee to recommend changes to the training matrix and to present other training policies and procedures for the EAC's consideration and approval.
      • Training will take place based on Appendix 1 and 2 which should assist Regional Training Coordinators in structuring regional workshops.
    • Principle 6

      Principle 6

      Training will address concerns appropriate both to small and large institutions.

      Notes:

      • DLI was established to provide affordable and equitable access to Statistics Canada's data products to all member institutions regardless of the size of institution, geographic location of the institution, or the instructional or research mandate of the institution. Therefore, training must be relevant to all institutional sizes, locations, and mandates.
    • Principle 7

      Principle 7

      Training will be regionally based with regular national and international exposure when the opportunities arise.

      Notes:

      • Workshops provide an opportunity to network with colleagues in data services and help to create community among those providing support for DLI products. The strength of DLI training will remain with the regional delivery of its workshops.
      • Data services also takes place within an international context. Therefore when the opportunity presents itself, DLI training will also be scheduled to allow those providing support for DLI to participate in an international data event (such as approximately every four years in conjunction with the IASSIST conference in Canada).
    • Principle 8

      Principle 8

      Whenever possible, trainers will be recruited from the existing Canadian data library community with the expectation that those who are trained may someday be called upon to train others. This principle is founded on the understanding that as one learns, one will teach.

      Notes:

      • DLI training is based on peer-to-peer instruction because a peer not only is more likely to know what trainees face in their work, but will also be able to communicate more clearly the information and skills needed for the job.
    • Principle 9

      Principle 9

      DLI contacts at their respective institutions have the responsibility to inform Library Directors, the user community, and other general public to communicate the importance of statistical and data literacy and the importance of publicly available datasets to foster higher education and research.

      Notes:

      • The prospect of a healthy data culture in Canada is dependent on communicating information about DLI and data services to sectors related to our work. This includes the powers that fund and support our local data services, such as Library Directors, and the powers who create data in Statistics Canada and who determine its levels of access.
      • It is also important to communicate this information to the potential end-users on DLI campuses.
      • The importance of data and statistical literacy needs to be communicated to the general public because a society that practices evidence-based decision-making requires access to the data that constitutes the evidence.
    • Appendix 1 - Core competencies

      Appendix 1 - Core competencies

      Core competencies for supporting DLI data outline the basic level of data service skills desired for incumbents serving in the capacity of either DLI Contact or DLI Alternate. Core competencies in this context are defined as the knowledge and skills that can be developed to deliver a DLI data service program within a post-secondary institution.

      In the context of this document, knowledge refers to having a familiarity with or awareness of; understanding refers to comprehension or possessing the skill to deal with; and ability refers to competence or capacity to do.

      There are specific skills that are core competencies for supporting data services and there are competencies that may be acquired through participation in the DLI Community (accessing official documents, exploring the training repository, staying updated via the DLI List and attending DLI training events).

      Knowledge of (refers to familiarity with or awareness of)

      • Basic data literacy, such as measures of central tendencies, descriptive statistics;
      • Data documentation and how that will inform which dataset(s) to recommend to a researcher;
      • Data lifecycle, which refers to the context in which data are produced and reused
      • Various tools for accessing data (including portals such as Statistics Canada's website DLI EFT, ODESI, Survey Documentation and Analysis (SDA), Web Data Server (WDS), as well as open data catalogues, such as open.canada.ca, and provincial or other open data portals;
      • Various software packages for statistical analysis (B2020, Dataverse, Excel, R, SAS, SPSS, STATA);
      • Statistics Canada's standard geographical classification and geography products.

      Understanding of (refers to comprehension or possessing the skill to deal with)

      • How to recognize a data/statistical/metadata/geospatial question (data reference);
      • Continuum of access for Statistics Canada products and services;
      • Extent and contents of DLI collection including open data sources;
      • How to access appropriate data sources to answer questions;
      • How to direct users to data resources.

      Ability to (refers to competence or capacity to do)

      • Use various tools for accessing data (including portals such as Statistics Canada's website, DLI EFT, ODESI, Statistics Canada Web Data Server (WDS));
      • Design or maintain a data service appropriate for their institution;
      • Promote local data services and the DLI collection;
      • Interpret the DLI licence, or find information on how to interpret the licence;
      • Develop a knowledge of data and statistics external to the DLI collection.
    • Appendix 2 - Training matrix (Revised – March 2018)

      Appendix 2 - Training matrix (Revised – March 2018)

      Appendix 2 - Training matrix (Revised – March 2018)
        Knowledge Skills Attitudes
      Statistics and data literacy
      • Research lifecycle (Framework – statistics and data)
      • Continuum of access
      • What is unique about data?
      • Different ways data are gathered
      • Recognizing a data/statistics/metadata/ geospatial question
      • Data interpretation
      • Data analysis
      • Overcoming the fear
      • Nurture sharing and open access
      • Nurture preservation
      Content
      • Where and how are statistics gathered (STC)
      • The collection (DLI)
      • Other data collections
      • Spatial representation of statistics
      • Finding
      • Accessing
      • Using
      • Sharing
      • Re-purposing (creating new: integrating existing)
      • Advocacy
      • Keep digging
      • Creative and bold
      Tools
      • Understanding the options: data, software, statistical/GIS packages, output file types, post processing
      • Selecting appropriate tools
      • Knowledge of access tools
      • Using statistical packages
      • Using tools for accessing data
      • Search tools
      • Format translation tools
      • Lifelong learning (re-learning tools)
      • Try it - be bold (you won't break it)
      • Positive attitude towards change
      Services
      • Options for service models
      • Adopt a service model responsive to internal and external changes
      • Understand the audience
      • Awareness of funding sources
      • Administer the service and DLI license
      • How to do an environmental scan
      • Grant writing
      • Interpret license
      • Service oriented
      • Data champion - proactive promotion of data service
      • Data reference means more time with each question
      • Developing a data culture

    Funding policy and procedures for training workshops

    • Policies and procedures

      Policies and procedures

      The DLI External Advisory Committee has adopted the following policies and procedures for DLI Training support:

      • Formal DLI training is offered annually in each of the four regions (Atlantic, Quebec, Ontario and West). It is financially supported by the DLI with a purpose to ensure that all DLI Contacts are provided with the opportunity to acquire base-level competencies essential for carrying out their responsibilities as noted in the training document.
      • Two regional training coordinators, appointed in each of the four regions, plan and implement the training workshops in their regions.
      • Each fiscal year, the EAC votes on a budgetary item for regional training support. The regional training coordinators independently determine how to manage the funds provided to them. The annual amount budgeted is $15,000 per region.

      The DLI will financially support regional training in the following manner:

      • Travel expenses such as transportation, accommodation and meal allowances, in whole or in part which is determined by the role the traveler. Such expenses will be paid by the DLI to individual participants, contingent upon a Travel Authority Request being submitted, travel being pre-approved and an expense claim being submitted.
      • Full travel expenses (transportation, accommodating and meals allowances expenses) are offered to the Coordinators (host) and Presenters.
      • Participants are offered funding for transportation only. More than one participant from an institution can attend the training, however, only one participant can request DLI funding. In the case where two individuals from the same institution are attending and one is a Presenter (full travel expense), an Alternate participant from the same institution can qualify for funding as a participant.
      • Limits for local arrangement costs based on a set budget, such as overhead expenses, will be provided by DLI staff prior to training sessions. Professional expenditures include professional services, audiovisuals services, room rental, and hospitality expenditures. These expenditures will be paid to the hosting institution in accordance with Treasury Board guidelines and the available budget.
      • Per diems and transportation costs for Coordinators.

      Normally, financial support is offered for a DLI Contact to attend at only one training session per Government of Canada fiscal year. The level of support is based on economy transportation rates. DLI Contacts are welcome and encouraged to attend additional training sessions at their own expense.

      The DLI Program does not pay consultant fees or honour. Training is based on a peer-to-peer model.

      Participation by Statistics Canada subject matter specialists is key and encouraged. Funding is budgeted through the DLI Section's operational budget.

      Representatives from regional Statistics Canada offices and staff from the Research Data Centres are to attend sessions in their region. However, the DLI does not provide any financial support to them.

      Occasionally, special training initiatives may be required. Proposals for these extraordinary initiatives must be submitted to the EAC for budgetary consideration.
      Regional Training Coordinators will post online a training proposal at a minimum of 3 weeks, in advance of any proposed training workshop. The proposal will include:

      • What training is being provided
      • Location and date(s) of the Workshop
      • Detailed outline of the expenses to be covered by the DLI funding
      • Overview of the curriculum as it pertains to regional needs
      • Number of spaces available
      • Names of trainers.

      Following the training session, regional coordinators and/or the DLI team in accordance with the rules and regulations governing Statistics Canada, will:

      • Provide instructions to participants to complete their expense claims. Participants are responsible for submitting their own expense claims, including receipts, directly to the DLI section.
      • Instruct the host institution on how to submit an invoice to the designated Statistics Canada Financial Officer and/or the DLI Section.

      The DLI should be credited in publicity and program notes for support provided.

    Data - DLI

    The Data Liberation Initiative (DLI) collection is composed of standard products produced by Statistics Canada.

    • All DLI products
      DLI products is a list of survey titles, acronyms and links to data and metadata available on the web.

    Tentative release dates

    • Labour Force Survey (LFS) – Monthly
    • Discharge Abstract Database (DAD) – Annual (August)