Monthly Survey of Manufacturing: National Level CVs by Characteristic - October 2022

National Level CVs by Characteristic
Table summary
This table displays the results of Monthly Survey of Manufacturing: National Level CVs by Characteristic. The information is grouped by Month (appearing as row headers), and Sales of goods manufactured, Raw materials and components inventories, Goods / work in process inventories, Finished goods manufactured inventories and Unfilled Orders, calculated in percentage (appearing as column headers).
Month Sales of goods manufactured Raw materials and components inventories Goods / work in process inventories Finished goods manufactured inventories Unfilled Orders
%
October 2021 0.76 1.03 1.52 1.73 1.46
November 2021 0.73 1.00 1.62 1.57 1.34
December 2021 0.75 1.01 1.81 1.56 1.46
January 2022 0.78 1.12 1.82 1.85 1.43
February 2022 0.73 1.14 1.64 1.77 1.38
March 2022 0.71 1.13 1.52 1.66 1.44
April 2022 0.69 1.19 1.51 1.62 1.49
May 2022 0.67 1.16 1.54 1.68 1.41
June 2022 0.69 1.15 1.55 1.75 1.44
July 2022 0.70 1.13 1.68 1.47 1.36
August 2022 0.70 1.15 1.79 1.57 1.39
September 2022 0.68 1.11 1.84 1.57 1.39
October 2022 0.69 1.13 1.86 1.54 1.49

Monthly Survey of Manufacturing: National Weighted Rates by Source and Characteristic - October 2022

National Weighted Rates by Source and Characteristic - October 2022
Table summary
The information is grouped by Sales of goods manufactured, Raw materials and components, Goods / work in process, Finished goods manufactured, Unfilled Orders, Capacity utilization rates (appearing as row headers), and Data source as the first row of column headers, then Response or edited, and Imputed as the second row of column headers, calculated by percentage.
  Data source
Response or edited Imputed
%
Sales of goods manufactured 86.0 14.0
Raw materials and components 76.1 23.9
Goods / work in process 80.1 19.9
Finished goods manufactured 77.4 22.6
Unfilled Orders 79.1 20.9
Capacity utilization rates 68.8 31.2

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Canadian Spring Wheat varieties - December 2022

Wheat, Canada Western Red Spring (CWRS)

The Canadian Grain Commission establishes the class Wheat, Canada Western Red Spring (CWRS) and designates the varieties of wheat listed below to be in the CWRS class:

  • AAC Alida
  • AAC Bailey
  • AAC Brandon
  • AAC Broadacres
  • AAC Cameron
  • AAC Connery
  • AAC Elie
  • AAC Hockley
  • AAC Hodge
  • AAC Jatharia
  • AAC LeRoy
  • AAC Magnet
  • AAC Prevail
  • AAC Redberry
  • AAC Redstar
  • AAC Russell
  • AAC Starbuck
  • AAC Tisdale
  • AAC Viewfield
  • AAC W1876
  • AAC Warman
  • AAC Wheatland
  • AC Barrie
  • AC Cadillac
  • AC Elsa
  • AC Intrepid
  • AC Splendor
  • Bolles
  • Carberry
  • Cardale
  • CDC Abound
  • CDC Adamant
  • CDC Alsask
  • CDC Bounty
  • CDC Bradwell
  • CDC Go
  • CDC Hughes
  • CDC Imagine
  • CDC Kernen
  • CDC Landmark
  • CDC Ortona
  • CDC Pilar CLPlus
  • CDC Plentiful
  • CDC Silas
  • CDC Skrush
  • CDC Stanley
  • CDC Succession CLPlus
  • CDC Teal
  • CDC Thrive
  • CDC Titanium
  • CDC Utmost
  • CDC VR Morris
  • Coleman
  • Daybreak
  • Donalda
  • Ellerslie
  • Fieldstar
  • Glenn
  • Go Early
  • Goodeve
  • Helios
  • Infinity
  • Jake
  • Journey
  • Laura
  • Lovitt
  • Noor
  • Parata
  • Peace
  • Prodigy
  • Redcliff
  • Rednet
  • Resolve
  • Roblin
  • Shaw
  • Sheba
  • Somerset
  • Stettler
  • Superb
  • SY Brawn
  • SY Cast
  • SY Chert
  • SY Crossite
  • SY Donald
  • SY Gabbro
  • SY Manness
  • SY Natron
  • SY Obsidian
  • SY Slate
  • SY Sovite
  • SY Torach
  • SY 433
  • SY479 VB
  • SY637
  • Thorsby
  • Tracker
  • Waskada
  • WR859 CL
  • Zealand
  • 5500HR
  • 5600HR
  • 5601HR
  • 5602HR
  • 5604HR CL

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Northern Hard Red (CNHR)

The varieties of wheat listed below are designated to be in the CNHR class:

  • AAC Concord
  • AAC Redwater
  • AAC Tradition
  • AC Abbey
  • AC Cora
  • AC Crystal
  • AC Domain
  • AC Eatonia
  • AC Foremost
  • AC Majestic
  • AC Michael
  • AC Minto
  • AC Taber
  • Alikat
  • Alvena
  • CDC Cordon CLPlus
  • CDC Makwa
  • CDC Osler
  • Columbus
  • Conquer
  • Conway
  • Elgin ND
  • Faller
  • Harvest
  • Kane
  • Katepwa
  • Leader
  • Lillian
  • McKenzie
  • Muchmore
  • Neepawa
  • Oslo
  • Park
  • Pasqua
  • Pembina
  • Prosper
  • Shelly
  • Thatcher
  • Unity
  • Vesper
  • 5603HR
  • 5605HR CL

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Prairie Spring Red (CPSR)

The Canadian Grain Commission establishes the class Wheat, Canada Prairie Spring Red (CPSR) and designates the varieties of wheat listed below to be in the CPSR class:

  • AAC Castle
  • AAC Crossfield
  • AAC Crusader
  • AAC Entice
  • AAC Foray
  • AAC Goodwin
  • AAC Penhold
  • AAC Perform
  • AAC Rimbey
  • AAC Ryley
  • AAC Tenacious
  • AAC Westlock
  • Accelerate
  • CDC Reign
  • CDC Terrain
  • Cutler
  • Enchant
  • Forefront
  • SY Rorke
  • SY Rowyn
  • SY985
  • SY995
  • 5700PR
  • 5701PR
  • 5702PR

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Prairie Spring White (CPSW)

The varieties of wheat listed below are designated to be in the CPSW class:

  • AC Karma
  • AC Vista

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Western Extra Strong (CWES)

The varieties of wheat listed below are designated to be in the CWES class:

  • AC Corinne
  • Amazon
  • Bluesky
  • Burnside
  • CDC Rama
  • CDC Walrus
  • CDN Bison
  • Glenavon
  • Glencross
  • Glenlea
  • Laser
  • Wildcat

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Western Hard White Spring (CWHWS)

The varieties of wheat listed below are designated to be in the CWHWS class:

  • AAC Cirrus
  • AAC Iceberg
  • AAC Tomkins
  • AAC Whitefox
  • AAC Whitehead
  • CDC Whitewood
  • Kanata
  • Snowbird
  • Snowstar
  • Whitehawk

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Western Soft White Spring (CWSWS)

The varieties of wheat listed below are designated to be in the CWSWS class:

  • AAC Chiffon
  • AAC Indus
  • AAC Paramount
  • AC Andrew
  • AC Meena
  • AC Nanda
  • AC Phil
  • AC Reed
  • Bhishaj
  • Sadash

This order comes into effect on the later of the crop year commencing August 1, 2022 or the signing date, and is in effect until July 31, 2023, unless revoked earlier.

Wheat, Canada Eastern Red Spring (CERS)

The Canadian Grain Commission establishes the class Wheat, Canada Eastern Red Spring (CERS) and designates the varieties of wheat listed below to be in the CERS class:

This order comes into effect on the later of the crop year commencing July 1, 2022, or the signing date, and is in effect until June 30, 2023, unless amended or revoked earlier.

Why are we conducting this survey?

This survey is conducted by Statistics Canada in order to collect the necessary information to support the Integrated Business Statistics Program (IBSP). This program combines various survey and administrative data to develop comprehensive measures of the Canadian economy.

The purpose of this survey is to obtain information on the volume of refined petroleum products distributed by secondary distributors in Canada. It supplements energy consumption data collected from the refineries in the Annual Survey of End Use of Refined Petroleum Products.

Your information may also be used by Statistics Canada for other statistical and research purposes.

Your participation in this survey is required under the authority of the Statistics Act.

Other important information

Authorization to collect this information

Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

Record linkages

To enhance the data from this survey and to reduce the reporting burden, Statistics Canada may combine the acquired data with information from other surveys or from administrative sources.

Data-sharing agreements

To reduce respondent burden, Statistics Canada has entered into data-sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.

Section 11 of the Statistics Act provides for the sharing of information with provincial and territorial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and businesses may not object to the sharing of the data.

For this survey, there are Section 11 agreements with the provincial and territorial statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Québec, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia and the Yukon. The shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory. Section 12 of the Statistics Act provides for the sharing of information with federal, provincial or territorial government organizations.

Under Section 12, you may refuse to share your information with any of these organizations by writing a letter of objection to the Chief Statistician, specifying the organizations with which you do not want Statistics Canada to share your data and mailing it to the following address:

Chief Statistician of Canada
Statistics Canada
Attention of Director, Enterprise Statistics Division
150 Tunney's Pasture Driveway
Ottawa, Ontario
K1A 0T6

You may also contact us by email at Statistics Canada Help Desk or by fax at 613-951-6583.

For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut as well as with the Newfoundland and Labrador Department of Natural Resources, New Brunswick Department of Environment and Local Government, the ministère des Finances du Québec, the ministère de l'Environnement et de la Lutte contre les changements climatiques du Québec, the ministère de l'Énergie et des Ressources naturelles du Québec, the Manitoba Department of Mineral Resources, the British Columbia Ministry of Energy, Mines and Low Carbon Innovation, the British Columbia Ministry of Natural Gas Development, Canada Energy Regulator, Natural Resources Canada and Environment and Climate Change Canada.

For agreements with provincial and territorial government organizations, the shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory.

Business or organization and contact information

1. Verify or provide the business or organization's legal and operating name and correct where needed.

Note: Legal name modifications should only be done to correct a spelling error or typo.

Note: Press the help button (?) for additional information.

Legal Name
The legal name is one recognized by law, thus it is the name liable for pursuit or for debts incurred by the business or organization. In the case of a corporation, it is the legal name as fixed by its charter or the statute by which the corporation was created.

Modifications to the legal name should only be done to correct a spelling error or typo.

To indicate a legal name of another legal entity you should instead indicate it in question 3 by selecting 'Not currently operational' and then choosing the applicable reason and providing the legal name of this other entity along with any other requested information.

Operating Name
The operating name is a name the business or organization is commonly known as if different from its legal name. The operating name is synonymous with trade name.

Legal name

Operating name (if applicable)

2. Verify or provide the contact information of the designated business or organization contact person for this questionnaire and correct where needed.

Note: The designated contact person is the person who should receive this questionnaire. The designated contact person may not always be the one who actually completes the questionnaire.

  • First name
  • Last name
  • Title
  • Preferred language of communication
    • English
    • French
  • Mailing address (number and street)
  • City
  • Province, territory or state
  • Postal code or ZIP code
  • Country
    • Canada
    • United States
  • Email address
  • Telephone number (including area code)
  • Extension number (if applicable)
  • The maximum number of characters is 10.
  • Fax number (including area code)

3. Verify or provide the current operational status of the business or organization identified by the legal and operating name above.

  • Operational
  • Not currently operational

Why is this business or organization not currently operational?

  • Seasonal operations
  • Ceased operations
  • Sold operations
  • Amalgamated with other businesses or organizations
  • Temporarily inactive but will re-open
  • No longer operating due to other reasons

When did this business or organization close for the season?
Date

When does this business or organization expect to resume operations?
Date

When did this business or organization cease operations?
Date

Why did this business or organization cease operations?

  • Bankruptcy
  • Liquidation
  • Dissolution
  • Other

Specify the other reasons why the operations ceased

When was this business or organization sold?
Date

What is the legal name of the buyer?

When did this business or organization amalgamate?
Date

What is the legal name of the resulting or continuing business or organization?

What are the legal names of the other amalgamated businesses or organizations?

When did this business or organization become temporarily inactive?
Date

When does this business or organization expect to resume operations?
Date

Why is this business or organization temporarily inactive?

When did this business or organization cease operations?
Date

Why did this business or organization cease operations?

4. Verify or provide the current main activity of the business or organization identified by the legal and operating name above.

Note: The described activity was assigned using the North American Industry Classification System (NAICS).

Note: Press the help button (?) for additional information, including a detailed description of this activity complete with example activities and any applicable exclusions.

This question verifies the business or organization's current main activity as classified by the North American Industry Classification System (NAICS). The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.

The target entity for which NAICS is designed are businesses and other organizations engaged in the production of goods and services. They include farms, incorporated and unincorporated businesses and government business enterprises. They also include government institutions and agencies engaged in the production of marketed and non-marketed services, as well as organizations such as professional associations and unions and charitable or non-profit organizations and the employees of households.

The associated NAICS should reflect those activities conducted by the business or organizational units targeted by this questionnaire only, as identified in the 'Answering this questionnaire' section and which can be identified by the specified legal and operating name. The main activity is the activity which most defines the targeted business or organization's main purpose or reason for existence. For a business or organization that is for-profit, it is normally the activity that generates the majority of the revenue for the entity.

The NAICS classification contains a limited number of activity classifications; the associated classification might be applicable for this business or organization even if it is not exactly how you would describe this business or organization's main activity.

Please note that any modifications to the main activity through your response to this question might not necessarily be reflected prior to the transmitting of subsequent questionnaires and as a result they may not contain this updated information.

The following is the detailed description including any applicable examples or exclusions for the classification currently associated with this business or organization.

Description and examples

  • This is the current main activity
  • This is not the current main activity

Provide a brief but precise description of this business or organization's main activity

e.g., breakfast cereal manufacturing, shoe store, software development

Main activity

5. You indicated that is not the current main activity.

Was this business or organization's main activity ever classified as: ?

  • Yes
  • No

When did the main activity change?
Date

6. Search and select the industry classification code that best corresponds to this business or organization's main activity.

How to search:

  • if desired, you can filter the search results by first selecting this business or organization's activity sector
  • enter keywords or a brief description that best describes this business or organization main activity
  • press the Search button to search the database for an activity that best matches the keywords or description you provided
  • then select an activity from the list.

Select this business or organization's activity sector (optional)

  • Farming or logging operation
  • Construction company or general contractor
  • Manufacturer
  • Wholesaler
  • Retailer
  • Provider of passenger or freight transportation
  • Provider of investment, savings or insurance products
  • Real estate agency, real estate brokerage or leasing company
  • Provider of professional, scientific or technical services
  • Provider of health care or social services
  • Restaurant, bar, hotel, motel or other lodging establishment
  • Other sector

Enter keywords or a brief description, then press the Search button

7. You have indicated that the current main activity of this business or organization is:

Main activity

Are there any other activities that contribute significantly (at least 10%) to this business or organization's revenue?

  • Yes, there are other activities
  • No, that is the only significant activity

Provide a brief but precise description of this business or organization's secondary activity

e.g., breakfast cereal manufacturing, shoe store, software development

8. Approximately what percentage of this business or organization's revenue is generated by each of the following activities?

When precise figures are not available, provide your best estimates.

  Percentage of revenue
Main activity  
Secondary activity  
All other activities  
Total percentage  

Products sold

1. In 2022 , which of the following refined petroleum products were sold or distributed by this business?

Select all that apply.

Propane

i.e., all propane types including those extracted from natural gas or refinery gas steams

Motor gasoline

i.e., all gasoline-type fuels for internal combustion engines other than aircraft; this includes any ethanol/methanol and other similar additives blended

Diesel fuel oil

i.e., all grades of distillate fuel used for diesel engines (dyed/marked or clear); this includes any biodiesel blended with fuel

Light fuel oil

i.e., all distillate type fuels used for power burners

Include fuel oil number 1, fuel oil number 2, fuel oil number 3, stove oil, furnace fuel oil, gas oils and light industrial fuel; this includes any biofuel blended.

Residual and heavy fuel oil

i.e., all grades of residual type fuels including low sulphur used for steam and electric power generation and steam and diesel motors installed on large marine vessels

Include fuel oil numbers 4, 5 and 6. Sometimes referred to as bunker fuel B or C.

Business's own use

2. How many litres of refined petroleum products did this business consume for its own use?

Report all amounts of refined petroleum products purchased that were used in company operations (that is used for your vehicles or heating).

Total number of litres used for own consumption

Litres

Sales by type of customer

3. To which types of customers did this business sell?

Select all that apply.

  • Residential
    • Wholesalers and dealers of refined petroleum products
    • Retail pump sales
  • Transportation
    • Railways
    • Road transport and urban transit
    • Canadian marine
    • Foreign marine
  • Manufacturing
    • Food, beverage, tobacco manufacturing
    • Pulp and paper manufacturing
    • Iron and steel manufacturing
    • Aluminum and non-ferrous metals manufacturing
    • Cement manufacturing
    • Refined petroleum products manufacturing
    • Chemical manufacturing
    • All other manufacturing
  • Mining and oil and gas extraction
    • Iron mines
    • Oil and gas extraction
    • Other mining
  • Other customer types
    • Forestry, logging, and support activities
    • Agriculture, fishing, hunting and trapping
    • Construction
    • Public administration
    • Electric power generation and distribution
    • Commercial and other institutional

Sales by location

4. In which of the following provinces and territories did this business sell?

Select all that apply.

  • Newfoundland and Labrador
  • Prince Edward Island
  • Nova Scotia
  • New Brunswick
  • Quebec
  • Ontario
  • Manitoba
  • Saskatchewan
  • Alberta
  • British Columbia
  • Yukon
  • Northwest Territories
  • Nunavut

Sales in Newfoundland and Labrador

5. How many litres of refined petroleum products were sold to the following types of customers in Newfoundland and Labrador?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Newfoundland and Labrador  

Sales in Prince Edward Island

6. How many litres of refined petroleum products were sold to the following types of customers in Prince Edward Island?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Prince Edward Island  

Sales in Nova Scotia

7. How many litres of refined petroleum products were sold to the following types of customers in Nova Scotia?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Nova Scotia  

Sales in New Brunswick

8. How many litres of refined petroleum products were sold to the following types of customers in New Brunswick?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in New Brunswick  

Sales in Quebec

9. How many litres of refined petroleum products were sold to the following types of customers in Quebec?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Quebec  

Sales in Ontario

10. How many litres of refined petroleum products were sold to the following types of customers in Ontario?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Ontario  

Sales in Manitoba

11. How many litres of refined petroleum products were sold to the following types of customers in Manitoba?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Manitoba  

Sales in Saskatchewan

12. How many litres of refined petroleum products were sold to the following types of customers in Saskatchewan?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Saskatchewan  

Sales in Alberta

13. How many litres of refined petroleum products were sold to the following types of customers in Alberta?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Alberta  

Sales in British Columbia

14. How many litres of refined petroleum products were sold to the following types of customers in British Columbia?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in British Columbia  

Sales in Yukon

15. How many litres of refined petroleum products were sold to the following types of customers in Yukon?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Yukon  

Sales in Northwest Territories

16. How many litres of refined petroleum products were sold to the following types of customers in Northwest Territories?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Northwest Territories  

Sales in Nunavut

17. How many litres of refined petroleum products were sold to the following types of customers in Nunavut?

  Litres
Residential  
Wholesalers and dealers of refined petroleum products  
Retail pump sales  
Railways  
Road transport and urban transit  
Canadian marine  
Foreign marine  
Food, beverage, tobacco manufacturing  
Pulp and paper manufacturing  
Iron and steel manufacturing  
Aluminum and non-ferrous metals manufacturing  
Cement manufacturing  
Refined petroleum products manufacturing  
Chemical manufacturing  
All other manufacturing  
Iron mines  
Oil and gas extraction  
Other mining  
Forestry, logging, and support activities  
Agriculture, fishing, hunting and trapping  
Construction  
Public administration  
Electric power generation and distribution  
Commercial and other institutional  
Total litres of sold in Nunavut  

Summary of sold by province and territory

18. This is a summary of refined petroleum products sold by province and territory.

Note: You cannot make changes to this page.
Please review the values and, if needed press the Previous button at the bottom of the page to navigate to the previous pages to make any modifications.

  Total Number of Litres
Summary by Province  
Newfoundland and Labrador  
Prince Edward Island  
Nova Scotia  
New Brunswick  
Quebec  
Ontario  
Manitoba  
Saskatchewan  
Alberta  
British Columbia  
Yukon  
Northwest Territories  
Nunavut  
Total litres of sold  

Changes or events

1. Indicate any changes or events that affected the reported values for this business or organization, compared with the last reporting period.

Select all that apply.

  • Strike or lock-out
  • Exchange rate impact
  • Price changes in goods or services sold
  • Contracting out
  • Organizational change
  • Price changes in labour or raw materials
  • Natural disaster
  • Recession
  • Change in product line
  • Sold business or business units
  • Expansion
  • New or lost contract
  • Plant closures
  • Acquisition of business or business units
  • Other
    Specify the other changes or events:
  • No changes or events

Contact person

1. Statistics Canada may need to contact the person who completed this questionnaire for further information.

Is the provided given names and the provided family name the best person to contact?

  • Yes
  • No

Who is the best person to contact about this questionnaire?

  • First name:
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  • Title:
  • Email address:
  • Telephone number (including area code):
  • Extension number (if applicable):
    The maximum number of characters is 5.
  • Fax number (including area code):

Feedback

1. How long did it take to complete this questionnaire?

Include the time spent gathering the necessary information.

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2. Do you have any comments about this questionnaire?

Municipal Land Use and Regulation Reporting guide

Purpose

Statistics Canada is conducting a new survey on behalf of Canada Mortgage and Housing Corporation (CMHC) called the Municipal Land Use and Regulation survey which will measure the degree of local land use restrictions across municipalities in Canada.

How data will be used

Survey data will be used to create an index of Land Use Regulation. This index will serve as a ranking system for municipalities on planning policies that could potentially incent the provision of affordable housing.

In addition, the data will be used by CMHC as an empirical basis for promoting policies aimed at increasing affordability and inclusion in the housing supply as part of their 2030 vision for creating affordable housing.

Your information may also be used by Statistics Canada for other statistical research purposes.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

How to submit

An email invitation is sent to respondents to complete an electronic questionnaire.

Correspondence

Do you have questions regarding the survey?

Do you need help in completing the form?

Contact us

Telephone

If you use an operator-assisted relay service, you can call us during regular business hours. You do not need to authorize the operator to contact us.

1-877-949-9492 (TTY : 1-800-363-7629)

Monday to Friday (except holidays), from 8:00 a.m. to 7:00 p.m. (Eastern Time)

If you use an operator-assisted relay service, you can call us during regular business hours. You do not need to authorize the operator to contact us.

Email

infostats@statcan.gc.ca

If you choose to transmit the questionnaire or information to Statistics Canada by facsimile or e-mail communication, please be advised that there could be a risk of disclosure during the communication process. However, upon receipt of your communication, Statistics Canada will provide the guaranteed level of protection afforded to all information collected under the authority of the Statistics Act.

Instructions

Reporting the jurisdiction

The jurisdiction will prefill in question 1. Verify that the jurisdiction you are reporting for is correctly listed if not, select "No, this is not the current jurisdiction", and write-in the correct jurisdiction. After selecting "Next" and "Finish" a follow-up email will be made to confirm your jurisdiction.

Size of jurisdiction

When reporting the size of the jurisdiction round to the nearest square kilometre.

Reporting weeks

Respondents must report weeks by rounding up to the nearest whole week.

Reporting hours

Respondents must report hours using exact hours and a decimal, eg., 37.25.

Reporting percentages

Respondents must report percentages in whole numbers, without decimals.

Reporting figures when precise number not available

If respondents do not have access to precise figures, provide your best estimate.

Reporting if no values available

If respondents do not have a value to report, enter "0."

Information for Questions:

Question 4

Please respond to parts a-i by selecting the level of involvement each organization has in affecting residential building activities and growth management.

Question 5

Please respond to parts a-e by selecting how the supply of land compares to the demand for each zoning type.

Question 6

Please respond to parts a-d by indicating the total number of applications submitted and approved for each type of zoning change.

Question 7A

Please respond to parts a-j by indicating if approval is required by the options listed when rezoning is required.

Question 7C

Please respond to parts a-j by indicating if approval is required by the options listed when rezoning is not required.

Question 11

Please respond to parts a-c by indicating if there are annual limits on the total number of new construction building permits allowed for each building type.

Question 12

Please respond to parts a-c by indicating if there are annual limits on the total number of new dwellings or units that can be built for each building type.

Question 13

Please respond to parts a-g by indicating if developers have to follow each listed requirement.

Question 15

Please respond to parts a-e by indicating how fees levied on developers have changed in the past five years for each development type listed.

Note: The response should indicate how fees levied on developers have changed from the beginning of the indicated time period compared to the current time period. The answer should not be an average of the past five years, but instead comparing the lengths of time from the first to second point.

Question 16

Please respond to parts a-e by indicating the typical length of time required to complete the review of a development project which requires a change in zoning for each building type.

In some cases not all municipalities issue development permits, instead they may issue a building permit which would indicate the end of the review period. Respondents should answer the question given their own knowledge of their jurisdictions review process.

Question 17

Please respond to parts a-e by indicating the typical length of time required to complete the review of a development project which does not require a change in zoning for each building type.

In some cases not all municipalities issue development permits, instead they may issue a building permit which would indicate the end of the review period. Respondents should answer the question given their own knowledge of their jurisdictions review process.

Question 18

Please respond to parts a-d by indicating how the length of time required to complete the review and approval of the residential projects changes in the past five years for each residential type.

Note: The response should indicate how the length of time required to complete the review and approval of the residential project has changed since the beginning of indicated time period compared to the current length of time. The answer should not be an average of the past five years, but instead comparing the lengths of time from the first to second point.

Question 19

Please respond to parts a-d by indicating the amount of time between application for rezoning and the issuance of a development permit for the listed building types.

Question 20

Please respond to parts a-d by indicating the amount of time between the initial application for a building permit and the issuance of the permit for the listed building types.

Question 21

Please respond to parts a-m by indicating the impact the listed factors have in acting as a constraint to residential development for single detached homes.

Question 22

Please respond to parts a-m by indicating the impact the listed factors have in acting as a constraint to residential development for multi-unit buildings.

Question 27

Please respond to parts a and b by indicating the total number of single detached and multi-units targeted for development for each affordable housing type.

Respondents should report the number of units targeted for developed from their official plan or other affordable housing plan.

Respondents cannot report a range, if your target is a range then please report the lower bound.

Question 28

Please respond to parts a and b by indicating the percentage of single detached and multi-units targeted for development for each affordable housing type.

Please report your objective for new affordable housing units developed in 2022, out of the total number of units developed.

Respondents must report one percentage, ranges are not accepted. If your target is a range then please report the lower bound.

Glossary of Terms

Administrative overhead

Administrative overhead may include salaries and wages, rent, utilities, and office expenses, etc.

Affordable housing

Affordable housing includes non-market housing which is subsidized as well as market housing costing less than 30% of local median before-tax income.

Fees levied on developers

Include development charges and other associated fees with meeting the regulatory burden for zoning, permits, etc.

Greenbelt

Greenbelts are reserved lands surrounding the jurisdiction that include the objective of restricting urban sprawl. Other commonly used terms include; Urban Containment Boundary, Urban Growth Boundary and/or Growth Containment Boundary.

Impact fees or exactions

Impact fees and other types of exactions are assessed on developments as a condition of approval of a proposed project and paid to the municipality.

Official Plan

An official plan describes a jurisdictions upper, lower or single tier municipal council or planning board's policies on how land should be used. It is prepared with input from the community and helps to ensure that future planning and development will meet its specific needs.

Redevelopment

Redevelopment includes infill, conversions and other forms of intensification on brownfield lands which have been repurposed for redevelopment of residential dwellings.

Supply of Land

Supply of land includes land whether held publicly or privately, that is vacant and zoned for development "by right" for the type of building indicated.

Building Types – non-residential

Building categories are defined as follows:

  • Industrial Buildings
    Buildings used in transformation of goods or related to transportation and communication.
  • Commercial Buildings
    Buildings used in the trade or distribution of goods and services, including office buildings
  • Institutional and Government Buildings
    Buildings used to house public and semi-public services such as those related to health and welfare, education, or public administration, as well as buildings used for religious services.

Building Types - residential

Single-detached

This type of dwelling is commonly called a "single house". It comprises a one-dwelling unit completely separated on all sides from any other dwelling or structure and includes homes linked below ground as well as mobile homes and cottages.

  • Mobile Home
    A dwelling designed and constructed to be transported on its own chassis and capable of being moved on short notice.
  • Cottage
    Refers to a dwelling which is unsuitable for year-round occupancy, since the structure does not have sufficient facilities to provide comfortable accommodation throughout the year.

Semi-detached

This type includes each of two dwellings separated by a common wall or by a garage, but not attached to any other building and surrounded on all other sides by open space.

Row house

One of three or more dwellings joined side by side but not having any other dwellings either above or below.

Apartments
This category includes dwelling units found in a wide range of structures such as duplexes, triplexes, row-duplexes, apartments proper and dwelling units over or at the rear of a store or other non-residential structure.

Mixed-use Residential

One or more dwelling units attached to commercial units or other non-residential space together in a single building.

Available samples in the Biobank

The Biobank stores whole blood, plasma, serum, buffy coat, urine, and DNA from consenting Canadians between the ages of 1 to 79 years, on an ongoing basis. Each survey may have multiple collection timeframes and these are called cycles.

Available samples at a glance

259,000

Serum

97,000

Plasma

34,900

Whole blood

121,700

Urine

10,000

Dry blood spot cards

10,800

DNA

Coming soon

Saliva

Coming soon

Buffy coat

Sample Matrix by Survey, Cycles, Age Range and Available Samples
Sample matrix SurveyFootnote 1 Cycles Age range Available samples
Serum CHMS 1-6 3-79 259,000
Plasma CHMS 1-6 3-79 97,000
Whole blood CHMS 2-6 6-79 34,900
Urine CHMS 1-6 3-79 121,700
Dry blood spot cards CCAHS 1 1-79 10,000
DNA CHMS 1-4 14-79 10,800
Saliva CCAHS Coming soon 18-79 Coming soon
Buffy coat CHMS Coming soon 3-79 5700
Footnote 1

Additional information on the surveys is on the Source surveys page.

Return to footnote 1 referrer

  • CHMS: Canadian Health Measures Survey
  • CCAHS: Canadian COVID-19 Antibody Health Survey

Biobank samples

  • Please contact us to request the current status of Biobank samples or request additional details about the samples.
How do persons with disabilities spend their time?

Video - How do persons with disabilities spend their time?

This American Sign Language video examines how persons with disabilities spend their days on selected activities. Analysis of time use opens a window into the experiences of persons with disabilities, particularly their perceptions of time.

Statistics Canada: Road to Accessibility, 2023-2025

Release date: December 23, 2022 Updated: February 6, 2024

Catalogue no. 13-26-00042023001
ISSN 2817-0903

Alternative formats

To request an alternate format (such as large font, braille, American Sign Language [ASL] and langue des signes québécoise [LSQ]) you can send a request to the Project Coordinator, Accessibility Secretariat, by

Executive summary

An Executive summary of Statistics Canada: Road to Accessibility, 2023-2025 is available in American Sign Language (ASL), audio and text formats.

Table of contents

© His Majesty the King in Right of Canada, as represented by the Minister of Innovation, Science and Industry, 2022

Privacy enhancing technologies: An overview of federated learning

By: Julian Templeton, Statistics Canada

Introduction

National statistical offices (NSOs) use collected data to provide insights on various topics for public good. Despite their access to large amounts of data, there are limitations on what can be collected or shared, regardless of the benefits. NSOs must ensure that personal information remain private, including any releases that involve data. In Canada, there are laws that mandate the protection of confidential data, of which Statistics Canada must abide. When sensitive data is collected, not everyone will trust it will remain private and protected and can lead some people to be hesitant in sharing their data.

To enhance data privacy throughout the public sector and to enable new opportunities for data collection, data sharing, and data use, various NSOs are actively exploring innovative ways to use and collect data privately. An emerging set of techniques currently being investigated are called privacy enhancing technologies (PETs) or privacy preserving technologies (PPTs) (see: A Brief Survey of Privacy Preserving Technologies).

There are many different types of PETs, some include:

  • Federated learning (FL): Helps build machine learning (ML) models from distributed data, which stays on a client's device and is not collected. Clients use their data and device to train local ML models which are then collected and compiled into a central model. This is a subset of distributed ML and we will discuss this in greater detail in this article.
  • Homomorphic encryption: Allows mathematical operations to be made on encrypted data to maintain privacy while the data is in use. For more information on this, see a recent DSN article – Privacy Preserving Technologies Part Two: Introduction to Homomorphic Encryption.
  • Trusted execution environments: Isolated virtual environments, also named secure enclaves, which can run code without being accessible anywhere else.
  • Differential privacy: Adds noise to data so occasional changes can be made to the data. This helps to protect the data and provides plausible deniability such that a single data entry may have been modified from its original state. Removing a single training sample from the training set should not impact the overall results.
  • Secure multiparty computation: Allows two or more parties to securely and jointly perform functions on their data.

All PETs listed above offer a unique method of enhancing privacy, however, each PET has its own drawbacks and must be selected based on the use case being derived. While no single PET is a universal solution to privacy issues, different PETs can be used in conjunction with one another to provide better overall privacy. Statistics Canada is in the research phase for PETs. It's becoming clear that widespread adoption of PETs in the public and private sectors will be required as data privacy becomes more common and as more data privacy laws are passed.

One method of exploring statistics is through the use of ML models, which aim to learn patterns through data and provide some target output. Different NSOs are already using or are beginning to use ML to support internal processes, ease the burden on analysts, and improve overall efficiencies. A challenge with ML is that the quality of the data used is important in achieving a well-performing model. A common saying in the field of artificial intelligence, and even other data science fields, is “garbage in, garbage out”. Fortunately, NSOs hold high-quality data that can be appropriately and ethically used to train high quality ML models (though, this article will speak solely on data privacy). However, it can be challenging to acquire quality data on sensitive topics as well as legally protected data to explore statistics on specific domains.

Of all the PETs presented above, FL is the approach that can generate ML models with sensitive or legally protected data, assuming the clients or collaborators agree. This article will discuss FL and potential cases for its use in the public sector after more research is conducted.

Background on federated learning

FL is a distributed learning technique which aims to build a central ML model from distributed data sources, without collecting the data. The distributed data used for training the centralized ML model which a central authority will hold remains on the client devices and does not leave. Neural networks are used for FL since they use layers of numerical weights for learning which are easy to aggregate and share. Within the scope of this article, a client will refer to an individual or organization that holds relevant data they agree to use within the FL process in collaboration with the central authority. Examples of clients include crowdsourcing participants who use their laptops, phones, or tablets and organizations holding relevant data. A central authority refers to the individual or organization (such as NSOs or private companies) responsible for holding, updating, and potentially distributing the central ML model, trained on client devices before the collection of model weights from clients are sent over to be aggregated.

To use FL to train a ML model held and initialized by the central authority, without viewing the client's training data, the initial model should first be trained with data stored by the central authority. Next, the central authority will submit requests to a subset of the clients to train the model. If the client can train the model, they're sent the model and instructions for their device to perform the training. The clients will then train the provided ML model using the data stored on the clients' device.

After the models are locally trained, the client devices will return only the weights of the updated ML model, without the data used for training. These weights are numbers adjusted during training to learn from the data. The central authority then receives these weights from the clients and aggregates them to be used as updated weights for the centralized model. This results in a trained ML model held by the central authority without collecting or learning the data held by its clients. This article will not cover all technical aspects of this process or the different options available, however I highlight the process in the figure below.

 
Figure 1: An overview of the federated learning process
Figure 1: An overview of the federated learning process

An overview of the federated learning process. (1) The central authority has a model that needs to be trained. A request for training is provided to two clients who accept the request and receive the model. (2) The client devices use their local data to train the received model on their device. (3) After training, each client sends their weights back to the central authority for processing without the data. (4) The central authority takes the updated weights and computes the aggregate to update the model. w1,1 represents the first weight for layer one and wn,n represents the n¬th weight for the nth layer. (5) The central authority uses the updated weights to update the central model. (6) The updated model is broadcast to the clients to be held for use or further training. This process is repeated as needed.

Similar to other PETs, FL has libraries available so the technique can be used for research and production. However, there is still much to be implemented in these libraries before a fully robust open-source library is available for production. Other libraries are being developed on an ongoing basis, but even the most prominent libraries are not sophisticated enough to work with complex problems without strong programming skills to supplement the functionalities.

Use of federated learning for organizations

Since FL allows neural networks to be trained in a distributed environment without accessing the data, projects that were once impossible can now be considered. An example of a collaborative proof-of-concept (PoC) project was presented at the United Nations PET Lab from various NSOs. This PoC explained how to learn from distributed physical activity data using FL. This project used and distributed an open dataset on physical activity data among each NSO, where each NSO considers this data to be private within the scope of their project. Statistics Canada aims to learn from physical activity data of other NSOs as well as their own private physical activity data, by building a model with distributed data without collecting it (mitigating the legal and privacy concerns held by each NSO). Each NSO can then use the generated model for their own statistical purposes.

This project was successful in replicating a variety of FL scenarios where the distributed data generated a model held by the central authority without accessing or collecting any of the data. Furthermore, experiments involving the use of homomorphic encryption in addition to FL, by encrypting a subset of the model weights to keep them private, have also been successful within the project's scope.

This highlights a clear use regarding FL -- organizations that can't typically share sensitive data can still generate models to use for statistical purposes without disclosing the data. This can provide opportunity for projects to be performed with domains that are sensitive in nature or legally protected and would not otherwise happen, such as some interagency collaborations. Of course, NSOs and other government organizations are carefully researching and experimenting with PETs and their weaknesses before making any moves to operationalize the techniques. We'll get to those later.

Another potential use for PETs within the scope of an NSO is for crowdsourcing activities. However, for certain topics, participants may be reluctant to provide information regardless of the incentive. Therefore, by providing a secure application or webpage where users can participate without sharing the data, fewer users may be hesitant to participate. Still, there are challenges to identify and anticipate before this can be implemented, such as possible attacks and communication strategies.

Federated learning challenges

While FL and other PETs can seem like magical tools that can tackle any major privacy issue, there are challenges that must be considered. One single PET does not provide a complete mitigation of all privacy risks but will provide additional mitigations allowing endeavors that are otherwise impossible. The PET(s) to be used and the communication strategy that explains how a client's data is kept private are critical and will vary for each use case.

PETs are actively researched, and there are many attacks against and defenses for PETs that are being investigated. Traditional ML model attacks can still be implemented against certain PETs and still require defenses, making the PET act as an additional privacy measure which still requires defenses against the attacks. For example, a membership inference attack can be performed to determine whether data has been used to train a model. Since FL combines the collected model weights from clients, there's a degree of added defense against some attacks, but there are scenarios where the attacks can still be effective against the centralized model. NSOs are investigating these to help determine how to mitigate attacks and be prepared to safely operationalize PETs in the future.

While there are programming libraries available to use FL, not all are ready to be used in production systems without facing challenges or by using paid software (which still may not include all the features needed for a use case). Therefore, a major challenge for the PET community to overcome will be to continue developing open-source software for individuals or organizations to use with ease and confidence, beyond simulation settings.

The final core challenge to discuss is the communication strategies surrounding the use of FL. When organizations collaborate with FL, they can audit the codebase and collaborate on its development to ensure it's properly implemented and safe to use with their data. This makes it easier to use within professional collaborations where experts are available to evaluate and develop the systems. However, in a public setting the story is quite different. Each client will need to be convinced that the approach works and that their data will never actually leave their device. Given the general difficulties surrounding trust between users and organizations, this is a significant hurdle that PET communities and organizations will need to address.

Conclusions

FL is an important tool that can lead to opportunities that are not otherwise possible. By generating ML models without accessing the data used for training, NSOs can provide insights to the public that are otherwise impossible to provide. This technique is currently in use by private organizations and is actively being researched. NSOs are investigating PETs with the intention of fostering collaborations at a global level that can provide an overall benefit to society. This research can also extend to other public organizations and allow more interagency collaborations within the public service. While there is still a lot of work to be done at Statistics Canada before it can be operationalized, our continued research will lead to improved privacy and for more statistics to be generated.

There are many challenges with FL that need to be overcome, however, NSOs and international PET communities will continue to collaborate and use the technique in safe and effective ways, keeping privacy at the forefront of all initiatives. Each PET will undergo analysis on attacks so they're proven as strong privacy methods. All of this will need to be clearly communicated to the public and other organizations.

Meet the Data Scientist

Register for the Data Science Network's Meet the Data Scientist Presentation

If you have any questions about my article or would like to discuss this further, I invite you to Meet the Data Scientist, an event where authors meet the readers, present their topic and discuss their findings.

Thursday, December 15
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