Editor's note: The following is an edited version of an article originally featured in Simon Fraser University (SFU)'s The Co-op Close-up series. The article was modified and translated by the Data Science Network for the Federal Public Service, and reproduced here with permission from SFU.
The article features Mihir Gajjar, a co-op student working in the Data Science Division at Statistics Canada. He completed a Bachelor of Technology in Information and Communication Technology at Ahmedabad University, India. He recently completed the Professional Master's program in Computer Science at SFU. The article also features his previous supervisor at Statistics Canada, Meredith Thomas.
SFU: Can you tell us about Statistics Canada? What is it like working there?
Mihir Gajjar: I have been working in the amazing Data Science Division at Statistics Canada. In this division, data scientists work with subject-matter analysts, methodologists, and IT specialists to develop big data-processing, machine-learning, and AI (artificial intelligence) strategies.
For me, there are several highlights about the work culture at Statistics Canada, such as the daily scrum meetings with the supervisor and team members where we prioritize the day's work and discuss other important issues. I also like the agile development approach for most of the projects so that each project has a lifespan of four months, and then the project is ready for deployment. We also have weekly machine-learning technical seminars where we learn about advancements in the field and discuss relevant research papers.
SFU: Can you tell us a bit about the project(s) you are working on in your co-op position?
Mihir Gajjar, student at Simon Fraser University (Master's in Computer Science program) and co-op student with Data Science Division.
Photo: D. Taiwo.
Mihir Gajjar: At Statistics Canada, analysts spend a lot of time searching for information about enterprises. With the amount of news growing exponentially, it becomes difficult to manually track all the published information. The project I am working on seeks to automate the tasks of detecting events of interest from news articles and extracting their attributes.
For example, events of interest that are related to enterprises might include mergers and acquisitions, equity markets, and branch openings, whereas event attributes are things like dates and locations of said events. Ultimately, my work allows economic analysts to spend less time on information searches and devote more time to analysis. This multidisciplinary work is a collaboration between teams, including portfolio and accounts managers, methodologists, and other data scientists.
The main technical tasks include finding similarities between articles for ranking, removing duplicates, and text summarization. The goal is to provide subject-matter experts with a dashboard to support the detection and tracking of desired events over a specified time span.
The data for our models consist of 1.5 million news articles from the Dow Jones Data News and Analytics Platform and NewsDesk, a shared governmental system. Exploratory data analysis and basic text pre-processing were used to train various machine-learning models.
SFU: How did the Big Data program prepare you for your co-op position?
Mihir Gajjar: SFU's Big Data program provided me with theoretical as well as practical hands-on experience through lectures and a project-based learning environment. Subjects like machine learning helped me to develop a solid theoretical base while the practical assignments and group projects allowed me to implement the concepts and try out new tools and technologies.
Along with sound technical knowledge, the program equipped me with essential skills, such as working in a team, communicating and sharing ideas with other people, giving presentations, critical thinking, technical writing, and time management.
SFU: What are your most valuable takeaways from this co-op experience?
Mihir Gajjar: Through the project I have been working on, I learned a lot about the practical aspects of working as a data scientist. Part of the project involved extracting data using an external company's Application Programming Interface, which meant weekly meetings with its development team. This helped me learn how to think analytically and design questions which aid in understanding the quality and the depth of the data. I also learned about the importance of fully understanding the user's needs in order to develop a product that meets those requirements.
Working at Statistics Canada gave me exposure to real-world data science projects and taught me how to create and execute a technical plan to achieve the desired goals. This is my first time working as a data scientist and this experience has improved my skills and made me feel confident about working in this role moving forward in my career.
SFU: What do employers say about our students?
Meredith Thomas, Chief, Data Science Division: Mihir is a great fit for this work environment, as he is always open to learning new approaches in technology, and works well independently or in a team setting. Partnered with a senior data scientist, Mihir continues to grow in his time here at Statistics Canada, moving from Natural Language Processing projects to image processing projects with enthusiasm and focus. He is a valued member of our team.
The COVID-19 cloud platform for advanced analytics
By: Allie MacIsaac, Statistics Canada
As Canadians grew increasingly concerned about the impact of COVID-19 on our society and our economy in March 2020, Statistics Canada set to work collecting vital information to support citizens and critical government operations during unprecedented times.
At the same time, analysts, researchers and data scientists across the Government of Canada were faced with another pressing concern…how could they provide much-needed information quickly and securely, while working remotely with limited access to their usual tools and computing infrastructure?
Fast-tracking modernization
As the need for analytical capabilities became increasingly urgent, a team of experts at Statistics Canada came together to fast-track the Data Analytics as a Service (DAaaS) project and explore open source data solutions. The aim was to equip data scientists with the work environment they need to conduct deeper analysis and to provide insights on the impact of COVID-19 in Canada.
The result is the COVID-19 cloud platform for advanced analytics: a virtual data science workspace that integrates data from reliable StatCan sources, extracts information and presents it in a central platform that includes robust presentation and dissemination options.
Not only does this solution meet the needs of data scientists, but it also drives forward modernization at the national statistical agency by helping meet the strategic objectives of the Statistics Canada Data Strategy—including an enhanced focus on data science—at an expedited pace.
A multi-disciplinary tiger team creating a "dream" data science environment
The analytical platform is the result of a collaboration between Statistics Canada's Data Science Division, the IT DAaaS team, the Cloud Team and partners at Microsoft.
Each group had an important role to play. The cloud team laid the foundation for the work, providing a robust containerized foundation using Kubernetes and the underlying Azure infrastructure as a service (IaaS) base. The DAaaS team worked on integrating service components, including the portal, using the underlying services. The Data Science team worked with the other teams to identify open source software to be installed and worked to define pipelines and data flows. By having data science experts working with cloud and platform experts, the team was able to deliver a scalable, accessible platform that met data science needs. The result is an environment with a variety of advanced tools for satellite image processing, natural language processing and automation.
By breaking down barriers internally and externally, the team was able to create a cohesive workbench in a matter of weeks—all while working securely from home. This was done with a user-centric approach to modernize the experience for data users and better meet their rapidly-evolving needs, while providing end-to-end data science support.
"The platform has had a major, positive impact on the way we work. We are able to get better results, work in an agile way and see the benefits of modernization in action," explains Sarah MacKinnon, Assistant Director of the Information Technology Project Delivery team at Statistics Canada.
Inside the workbench you will find a state-of-the-art platform, a "dream data science environment," says Sevgui Erman, Director of the Data Science Division at Statistics Canada. "This environment addresses the high-capacity computing needs of data scientists and meets our needs for collaborative workspaces and tools. The workbench is equipped with tools for continuous integration and continuous development that allow for scalable and reproducible data pipelines, as well as advanced data and model management capabilities."
"You can also build out your workflows using GitHub Actions and Kubeflow Pipelines. With templates for training, validation, preprocessing, and RESTful model serving, and with integrations with Platform as a service offerings like Databricks or managed Data Lakes, the advanced analytics workspace gives you the freedom to harness whatever tools you want, and it gives you a unified layer to use them from," adds Blair Drummond, an analyst with StatCan's Data Science Division and a member of the tiger team.
Peek inside the workbench
The team gathered the best available open source tools to create a workbench that allows users to remotely access data loaded by Statistics Canada—with a focus on COVID-19. This powerful environment employs a full suite of data science and analytics tools, including
Jupyter Notebooks for R and Python
Linux remote desktop
Power BI
QGIS
R Shiny
Pachyderm (data lineage and pipelines)
Kubeflow Pipelines
MLflow for model tracking, custom web applications
self-serve sharable storage
and more.
The platform also includes support channels for user feedback and guidance.
The result is that data users are better equipped to analyze the impacts of COVID-19 and share their findings in a secure, confidential manner.
Why open source software? As Blair explains, "Open source software tools give users more flexibility and autonomy over their own work. These tools are accessible and crowd-sourced, meaning that users can also get support and help with analysis." Furthermore, results are reproducible by colleagues in other departments. An approach that incorporates open source software supports collaboration between data scientists that benefits all users.
The platform in action
By leveraging the resource functionality of the platform, data scientists at StatCan have been hard at work as they put the platform to use.
One example is the work done by Kenneth Chu, a Senior Methodologist with StatCan's Data Science Division, who was one of the early adopters of the new platform and tested it's capabilities by performing a massively parallelized statistical analysis that otherwise would not have been feasible with pre-existing computing infrastructure.
Kenneth fitted a hierarchical Bayesian model (to provincial COVID-19 death count time series) that estimated the effects of social distancing measures on COVID-19 transmissibility. There were, however, certain crucial but unknown input parameters, namely, the provincial COVID-19 infection fatality rates (IFR, defined as the conditional probability of dying of COVID-19 given that one is infected with it). Their theoretically straightforward estimates are simply the provincial ratios of the number of COVID-19 deaths to the true number of COVID-19 infections. Unfortunately, the near-complete lack of knowledge of the latter, especially during the early phase of the pandemic, rendered the IFRs highly uncertain.
The parallelized sensitivity analysis involved simply executing the Bayesian analysis independently a reasonably large number of times (200, to be precise), each time sampling the provincial IFRs randomly from the full range of plausible values. Each independent execution required approximately eight hours to complete, using two computing cores. The full sensitivity analysis, executed on DAaaS, thus required 3,200 CPU core hours in total, which would have been impossible with pre-existing infrastructure.
The capacity to execute distributed/massively parallel workflows contributes to StatCan's Big Data infrastructure. In addition, such computing capacity also enables the use of many distribution-free statistical methods (e.g. resampling-, permutation-based ones), which are highly computationally intensive but complement modern complex analytical techniques from machine learning or Bayesian statistics.
Overall, the increased computing capabilities support the agency's mission to provide timely, critical information to Canadians during the unprecedented challenges of the COVID-19 pandemic.
A secure, phased approach
Currently, the COVID-19 analytical platform is accessible to Statistics Canada employees, and to other Government of Canada departments who have research data partnerships with the agency. If you are a data scientist interested in this platform, please reach out to get involved and experience the platform by emailing statcan.analyticalplatform-platformeanalytique.statcan@statcan.gc.ca.
This is part of Statistics Canada's phased approach to grant access to the platform in a secure manner. For the first phase, access to the platform was limited to internal StatCan employees working with publicly available data only. The second phase featured access to unclassified data (publicly available data only) and access to the platform was made available to select Government of Canada employees by invitation. The third phase will feature protected data and use a mix of public and other data sets. Access to this platform will be promoted externally on the StatCan website. Each phase will include the necessary safeguards to ensure a secure environment is maintained at all times, including regular security assessments.
As this project continues to progress, Statistics Canada looks forward to engaging with the data science community and continuing to provide vital information to all Canadians.
Project team and contributors:
Christian Ritter, Statistic Canada; Blair Drummond, Statistics Canada
Ninth Canadian Statistics Advisory Council (CSAC) Meeting
Date: August 20 2020, 1:00pm to 4:00pm
Location: Virtual meeting
CSAC members
Dr. Teresa Scassa (Chairperson), Anil Arora, Gurmeet Ahluwalia, David Chaundy, Annette Hester, Jan Kestle, Dr. Céline Le Bourdais, Gail Mc Donald, Dr. Howard Ramos, Dr. Michael Wolfson
Statistics Canada guests/support
Melanie Forsberg, Lynn Barr-Telford, Marc Lachance, Jean-Pierre Corbeil
Meeting agenda
Meeting agenda
Time
Agenda Item
Lead Participant(s)
12:50 - 13:00
Virtual Arrival
CSAC Members
13:00 - 13:05
Chairperson introductory remarks
Teresa Scassa: Chairperson
13:05 - 14:10
Update from the Chief Statistician of Canada
Anil Arora: Chief Statistician of Canada
14:10 - 14:15
Review Annual Report content In camera discussion
CSAC members and Rosemary Bender
14:15 - 14:25
Health Break
14:25 - 15:10
Review Annual Report content continued In camera discussion
CSAC members and Rosemary Bender
15:10 - 15:40
Next steps for the Annual Report In camera discussion
Eighth Canadian Statistics Advisory Council (CSAC) Meeting
Date: July 24 2020, 1:00pm to 4:00pm
Location: Virtual meeting
CSAC members
Dr. Teresa Scassa (Chairperson), Anil Arora, Gurmeet Ahluwalia, David Chaundy, Annette Hester, Jan Kestle, Dr. Céline Le Bourdais, Gail Mc Donald, Dr. Howard Ramos, Dr. Michael Wolfson
Meeting agenda
Meeting agenda
Time
Agenda Item
Lead Participant(s)
12:50 - 13:00
Virtual Arrival
CSAC Members
13:00 - 13:05
Chairperson introductory remarks
Teresa Scassa: Chairperson
13:05 - 13:10
Update from the Chief Statistician of Canada
Anil Arora: Chief Statistician of Canada
13:10 - 13:55
Discussion with the Chair of the Advisory Committee on Ethnocultural and Immigration Statistics In camera discussion
Morton Weinfeld: Chair of the Advisory Committee on Ethnocultural and immigration statistics
Lynn Barr-Telford: Assistant Chief Statistician
Marc Lachance: Acting, Director General
Jean-Pierre Corbeil: Assistant Director
Canadian dollar equivalent of outstanding debt denominated in foreign currency
Canadian Dollar
Foreign Currency *
(Par-value - thousands of dollars)
Outstanding treasury bills of which:
$
(Var. # 7071)
$
(Var. # 7081)
sold directly to chartered banks
$
(Var. # 7072)
$
(Var. # 7082)
sold directly to provincial govt. accounts
$
(Var. # 7073)
$
(Var. # 7083)
Outstanding short-term paper of which:
$
(Var. # 7074)
$
(Var. # 7084)
sold directly to chartered banks
$
(Var. # 7075)
$
(Var. # 7085)
sold directly to provincial govt. accounts
$
(Var. # 7076)
$
(Var. # 7086)
Signature/Name:
*Enter Canadian dollar equivalent of outstanding debt denominated in foreign currency.
This survey covers short-term treasury bill and paper borrowings, not investment in such paper.
Include only treasury bills and paper with an original term of one year or less.
Please file a report each month whether or not you have paper outstanding at the particular month-end.
Reports should be submitted immediately, addressed to:
Statistics Canada
Operations and Integration Division
Jean Talon Building, 2nd floor, B-19
170 Tunney's Pasture
Ottawa, Ontario
K1A OT6
Participation is mandatory under the authority of the Statistics Act, which ensures that all information will be kept confidential and used only for statistical purposes. We do not release any information that could identify an organization, unless consent has been given, or as permitted by the act.
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 information with those organizations that have demonstrated a requirement to use the data.
Today, the Canadian Statistics Advisory Council (CSAC) issued its first report (CSAC 2020 Annual Report - Towards a Stronger National Statistical System) on the state of the country’s statistical system to the Minister of Innovation, Science and Industry. The release of this report coincides with World Statistics Day. “Our report recognizes how, in response to the COVID-19 pandemic, Statistics Canada’s modernization efforts have helped the agency pivot to meet many of the country’s statistical needs,” says CSAC member Dr. Howard Ramos. It also highlights the importance of accelerating those efforts to bridge crucial data gaps to overcome the statistical challenges that are facing both Statistics Canada as an agency and Canada as a nation.
Decision makers were hampered by a lack of timely, consistent and disaggregated data in areas such as health care and on racialized Canadians and Indigenous people. This situation served to highlight the broader need for high-quality statistical information to address nationwide health issues and socioeconomic inequities. Collecting these data while respecting the privacy of Canadians’ personal information remains of key importance.
The council’s mandate is to advise the Minister of Innovation, Science and Industry and the Chief Statistician of Canada on any number of issues concerning the relevance, accuracy, accessibility, timeliness, and privacy and confidentiality of the agency’s data.
The report includes five core recommendations: (1) including statistical data requirements in planning federal government programs, (2) addressing critical data gaps, (3) rectifying serious imbalances in funding national statistical programs, (4) ensuring the privacy of Canadians and the need for Canadians to provide data to Statistics Canada, and (5) modernizing microdata access.
Through the course of its work, the council found that, as shown by the pandemic, Statistics Canada’s central role as an independent national statistical organization has never been more critical to meet the country’s needs for timely and high-quality statistics. The pandemic has shown that nationwide data are key for decision makers, governments and the general public to understand and address important social, health, economic, environmental and energy issues facing Canadians. CSAC member Jan Kestle notes, “Bringing together data from different levels of government, and private sources, is necessary to get a complete and up-to-date picture of the social and economic well-being of Canadians. Collaboration across jurisdictions is complicated. But this challenge must be met head-on for Canada to fill data gaps and ensure a strong foundation for decision making.
Serious shortcomings in the timeliness, completeness and quality of Canadian health care and health outcome data have greatly impaired the ability of governments at all levels to monitor and assess the evolution of the pandemic, let alone address serious health issues in Canada. The council also saw that the ability to address barriers faced by racialized groups and Indigenous peoples in Canada is seriously hampered by the lack of timely, consistent and disaggregated data. As CSAC member Gail Mc Donald explains, “The year 2020 has brought the issue of systemic racism to the forefront. By truly addressing Indigenous data gaps on the impacts of racism within our society, only then can we harness the power of data to effect change and make a difference.”
To overcome these gaps, stable core funding for Statistics Canada’s programs is essential to having high-quality data and statistical information that represent all regions of Canada and the full range of circumstances of individual Canadians.
The council also found that, going forward, it is important for researchers, decision makers and communities to be able to access the data they provide to the agency. The modernization of Statistics Canada’s microdata access infrastructure is a long-awaited initiative that will greatly improve the quality and depth of research and analysis in Canada across all sectors. However, its timeline for full implementation is too long and should be accelerated. As CSAC member Dr. Céline Le Bourdais observes, “The COVID-19 pandemic has reinforced the need for Statistics Canada to continue to modernize its infrastructure and rapidly move toward new distributed modes of data access. This will ensure that duly authorized researchers are able to pursue timely analyses on the pressing challenges faced by society.”
Canadians have provided personal data to Statistics Canada for over 100 years, and there should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada. The council found that this is also key to ensuring a robust statistical system and a stronger country.
Contact info and expertise of CSAC spokespeople
Dr. Howard Ramos
Media release CSAC facilitator
Mobile: 902-402-9893
Email: howard.ramos@uwo.ca
English/français
Availability on October 20, 2020: 8:00 a.m. to 4:00 p.m. EDT
Expertise: General insight on the report, focus on race and ethnic data, data access, balance of privacy and need for data
Jan Kestle
Mobile: 647-988-2834
Email: jan.kestle@environicsanalytics.com
Availability on October 20, 2020: 8:00 a.m. to 6:00 p.m. EDT
Expertise: The importance of high-quality data and evidence-driven decision making, modernizing methods for the production of official statistics, national data strategy, privacy and security of data
Dr. Céline Le Bourdais
Mobile: 514-770-3714
Email: celine.lebourdais@mcgill.ca
Français/English
Availability on October 20, 2020: 8:00 a.m. to 2:30 p.m. EDT
Expertise: General insight on the report, focus on data access and addressing data gaps and imbalances in funding
Gail Mc Donald
Mobile: 514-970-8254
Email: gail.mcd@sympatico.ca
English
Availability on October 20, 2020: 11:00 a.m. to 3:00 p.m.
Expertise: General insight on the report, focus on Indigenous data, capacity development and governance
Post-production and other motion picture and video industries: CVs for operating revenue - 2019
Table summary
This table displays the results of CVs for operating revenue - Post-production and other motion picture and video industries. The information is grouped by Regions (appearing as row headers), CVs for operating revenue, calculated using percent units of measure (appearing as column headers).
Message from the Canadian Statistics Advisory Council
The Canadian Statistics Advisory Council (CSAC) was created as part of a suite of amendments to the Statistics Act in 2017 designed to enhance the independence of Statistics Canada, Canada's national statistical organization. In June 2019, the first slate of Council members was appointed by the Governor in Council.
As with any newly created body, part of our first year has involved establishing ourselves as a group, defining our agenda and finding our voice. CSAC's statutory mandate includes providing advice to the Minister of Innovation, Science and Industry and to the Chief Statistician of Canada. It also requires us to produce an annual report on the state of Canada's statistical system. Our mission is to provide impartial and independent advice to ensure the quality, relevance and accessibility of the national statistical system.
We are grateful to Statistics Canada, the Chief Statistician of Canada who is an ex-officio member of the Council, and his excellent team for responding to our many requests for information with both written and oral presentations. We would like to offer our very particular thanks to Melanie Forsberg, Robert Andrew Smith and Kacie Ha of the CSAC Secretariat for their advice and assistance. We are also especially grateful for the work of Dr. Teresa Scassa, the Council's initial chairperson, who shaped and guided the work of the committee.
The COVID-19 pandemic altered the course of our work, as it did for all Canadians and people around the world. The pandemic brought into stark relief many of the statistical challenges that Statistics Canada has faced as an agency and Canada has faced as a nation. Decision makers were hampered by a lack of timely, consistent and disaggregated data in areas such as health care and on racialized Canadians and Indigenous peoples. This situation highlighted the broader need for high-quality statistical information to address nationwide health issues and socioeconomic inequities. Collecting these data while respecting the privacy of Canadians' personal information remains of key importance.
We trust that our report and recommendations will be accepted by the Minister on behalf of the Government of Canada, and will provide Canadians with a better understanding of the need to strengthen Canada's national statistical system, and ensure more evidence-based decision making, resulting in benefits to all Canadians.
Signed: The Canadian Statistics Advisory Council
Annette Hester
Dr. Céline Le Bourdais
David Chaundy
Gail Mc Donald
Gurmeet Ahluwalia
Dr. Howard Ramos
Jan Kestle
Dr. Michael C. Wolfson
Executive summary
Statistics Canada's central role as an independent national statistical organization has never been more critical to meeting the need for timely and high-quality statistics in Canada. Having an independent and trusted source of official statistics provides a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors for the benefit of all Canadians.
The fast pace of social and economic change is affecting the kinds of data and analyses Canadians need. There has also been a dramatic shift in how Canadians receive information, with a proliferation of information from new sources, such as social media. New tools are being used to collect, process, transform and visualize information. For Canada to succeed in this dynamic digital economy, Statistics Canada must play a central leadership role, coordinating with governments and organizations to produce coherent and trusted national statistical information.
Canadians have provided personal data to Statistics Canada for over 100 years. The confidentiality of their information is protected under the Statistics Act, and, under federal data protection laws, Statistics Canada must respect the privacy of Canadians. There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.
Recommendation 1: Including statistical data requirements in planning federal government programs
There is presently no standard or coordinated way to assess priority data requirements within the federal government. There needs to be a fundamental shift in how statistical data needs in Canada are assessed. This includes greater consideration of how social, health, economic, environmental and energy factors collectively contribute to the well-being of Canadians and Canadian society.
It is recommended that the Minister of Innovation, Science and Industry
1.1 Ensure that statistical data requirements and funding are explicitly included in the planning for all federal government programs.
Recommendation 2: Addressing critical data gaps
Critical data gaps and a lack of coordinated data in Canada seriously undermine the ability of decision makers and governments at all levels, as well as the general public, to understand and address key social, health, economic, environmental and energy issues facing Canadians.
Two priority areas are gaps in health and health care data in Canada, and gaps in data by race and Indigenous peoples—while respecting existing and future processes with Indigenous jurisdictions—on topics including gender, disabilities, education, employment, health, income, justice, safety, the environment, energy, community infrastructure and social well-being.
It is recommended that the Minister of Innovation, Science and Industry
2.1 invest in coordinating data collection across federal, provincial, territorial and other levels of government and organizations to build a truly national data infrastructure (including, in accordance with Recommendation 1, providing Statistics Canada with the necessary funds to develop modern real-time software and communications technologies to collect these data)
2.2 implement in the various fiscal arrangements with the provinces and territories adequate and effective mechanisms (which could include funding, incentives and penalties) to ensure that nationally consistent data can and do flow to Statistics Canada, pursuant to its mandate.
Recommendation 3: Rectifying serious imbalances in funding national statistical programs
Statistics Canada is given the resources to produce economic indicators for about 20 key areas of economic activity. There are imbalances and inefficiencies in how data needs in other domains are addressed. Many of the agency's key social statistics programs, and certain economic, environmental and energy programs, are largely dependent on ad hoc funding and cost-recovery transfers from federal departments. Stable core funding for these programs is essential to support a national data strategy that includes all factors affecting society and the economy.
It is recommended that the Minister of Innovation, Science and Industry
3.1 consider options to ensure that Statistics Canada's core funding includes resources for social, economic, environmental and energy statistics programs, including the long-form census questionnaire, household surveys, administrative data, research and analysis, without having to rely on ad hoc cost-recovery transfers from departments.
Recommendation 4: Ensuring the privacy of Canadians and the need for Canadians to provide data to Statistics Canada
Statistics Canada has the legal authority to collect federal, provincial and territorial data under the Statistics Act. Most jurisdictions include provisions in their data protection laws to permit data sharing for statistical purposes. The act also gives the agency the authority to collect data from private sector sources, in conjunction with government data, to provide a multifaceted statistical portrait of the country. The confidentiality of this information is protected under the Statistics Act.
There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.
It is recommended that
4.1 Statistics Canada and the Minister of Innovation, Science and Industry work with the Minister of Justice, informed by the Privacy Commissioner of Canada and by Indigenous jurisdictions, to ensure that federal, provincial and territorial data protection laws and policies are attentive to the imperative of data sharing for statistical purposes, and to ensure that there are no legislative ambiguities with regard to Statistics Canada's authority under the Statistics Act to collect data from federal, provincial and territorial jurisdictions
4.2 Statistics Canada and the Minister of Innovation, Science and Industry start a dialogue with Canadians on the importance of data for evidence-based decision making, and on how the collection of these data must respect data protection laws and the confidentiality of Canadians' personal information
4.3 Statistics Canada proceed, with support from the Minister of Innovation, Science and Industry, with its projects to develop new data sources from financial and credit institutions, in accordance with the agency's methodological framework on necessity and proportionality, and inform Canadians why these data are needed and how they will be collected and stored.
Recommendation 5: Modernizing microdata access
The need for a modern infrastructure to access Statistics Canada's microdata, including secure remote access, has never been greater, as duly authorized researchers undertake statistical analysis to inform governments and Canadians.
It is recommended that the Chief Statistician
5.1 give high priority to and accelerate the modernization of the Microdata Access Program, including providing secure remote access by duly authorized researchers to its anonymized microdata and streamlining the current authentication process for granting secure access to Statistics Canada's microdata.
1. Introduction
Statistics Canada's central role as an independent national statistical organization has never been more critical to meeting the need for timely and high-quality statistics in Canada. Having an independent and trusted source of official statistics provides a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors for the benefit of all Canadians. These decisions affect everybody's daily lives, including their health, where they live, where they work and their wages.
Fundamental to public trust is the clear independence of the country's national statistical office, where high-quality statistics and pertinent statistical analyses are produced with objective methods and with outputs that are accessible to everyone. The requirement that statistical information not be subject to political pressure and not serve special interests must be well recognized. This way, even people who may not trust their government can trust the statistical results and, just as importantly, entrust their information to Statistics Canada.
Canadians have provided personal data to Statistics Canada for over 100 years. The confidentiality of their information is protected under the Statistics Act, and, under federal data protection laws, Statistics Canada must also respect the privacy of Canadians. There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.
"Statistics Canada's central role as an independent national statistical organization has never been more critical to meeting the need for timely and high-quality statistics in Canada."
The fast pace of social and economic change is affecting the kinds of data and analyses Canadians need. For example, with the growth of online shopping, Statistics Canada requires new methods to measure consumer spending. Data on consumer spending are used to produce the Consumer Price Index, which Canadians depend on as a measure of inflation that affects wages, pensions, the cost of goods and interest rates. There has also been a dramatic shift in how Canadians receive information, with a proliferation of information from new sources, such as social media. New tools are being used to transform and visualize information, with significant increases in the flows of information, the extent of interconnectedness, and the development of increasingly powerful artificial intelligence software.
Not all available data sources are of good quality, nor do they all take measures to protect the privacy of personal information. Big datasets (usually characterized by their high volumes of data, speed of updates and variety of formats) and web-scraped data (data extracted from websites) are important new sources of data. However, their value for statistical analysis often has significant limitations, such as the underrepresentation of people with certain social or economic characteristics.
For Canada to succeed in this dynamic digital economy, Statistics Canada's role is key. The agency not only has the mandate to produce high-quality national social and economic measures, as well as more disaggregated statistical portraits, it also must play a central leadership role in coordinating data collection and integration with governments and organizations to produce coherent national statistical information for the benefit of all Canadians. This includes supporting leading-edge analysis of this statistical information.
Statistics Canada is responding to these challenges by developing, piloting and deploying new data sources, collection techniques and modelling to add depth and agility to its statistical programs. It has also engaged with Canadians in new ways—for example, using social media to encourage participation in web panel surveys and crowdsourcing surveys. At the same time, the federal government needs to seriously commit to starting a dialogue to address persistent, systemic data gaps. In some key sectors, fragmented data and an unwillingness to share data across jurisdictions have hampered Statistics Canada's ability to create needed nationwide datasets on a timely basis to address the country's most complex and dynamic challenges.
2. National data strategy
Recommendation 1: Including statistical data requirements in planning federal government programs
There is presently no standard or coordinated way to assess priority data requirements within the federal government. There needs to be a fundamental shift in how statistical data needs in Canada are assessed. This includes greater consideration of how social, health, economic, environmental and energy factors collectively contribute to the well-being of Canadians and Canadian society.
It is recommended that the Minister of Innovation, Science and Industry
1.1 Ensure that statistical data requirements and funding are explicitly included in the planning for all federal government programs.
Nationwide data are a key strong foundation for decision makers and governments at all levels, as well as the general public, to understand and address important social, health, economic, environmental and energy issues facing Canadians.
Canada does not have a proactive national data strategy that considers the information needs of both today and the future and that puts in place new data sources to inform and anticipate emerging issues and concerns. Throughout its history, Statistics Canada has continually modernized its statistical programs to provide Canadians with the nationwide data and statistical information they need.
Its current modernization initiative is in response to a rapidly evolving digital economy and society. However, there are important data gaps in sectors such as health, energy and the environment, and a lack of sociodemographic detail, including about racialized and Indigenous groups, in social and economic indicators.
New governance mechanisms are required to formally open new dialogues on national data needs and how to best collect and share this information. This must be led by Statistics Canada, in accordance with its mandate, with the full support and funding of the federal government. It must also include all levels of government and statistical organizations. Without a national data strategy, bureaucratic inertia and other hindrances to collecting and sharing statistical information across jurisdictions will continue to outweigh efforts to develop needed nationwide data accessible to all Canadians.
A national data strategy could include First Nations, Inuit and Métis organizations that are planning, implementing and exercising control over the delivery of services to their communities. The nature of the data and analytical skills they require is changing and is more specific to regional and local issues that affect their peoples. Collection for new data needs could be done in partnership with Statistics Canada and other departments. This includes, for example, the need for data to support indicators of well-being, resiliency, understanding, and measurable progress on reconciliation and economic measures.
Statistics Canada is well positioned to lead the various dialogues on national data and information needs. Its proven operational infrastructure provides an essential foundation, given that the agency has developed statistical data from hundreds of federal, provincial and territorial administrative data files. Its expertise in developing high-quality data using standardized concepts and classifications is recognized internationally. Statistics Canada also has the ability, with the required confidentiality protections in place, to combine and link these data with data from other sources to produce the statistical information needed to address national data gaps.
"Nationwide data are a key strong foundation for decision makers, governments and the general public to understand and address important social, health, economic, environmental and energy issues facing Canadians."
Statistics Canada must build on the new avenues of collaboration created as governments and experts came together in response to the COVID-19 pandemic. This involves working with governments at all levels, other organizations, and new public and private sector partners to produce nationally comparable data that are representative of all Canadians. It also involves developing a close relationship with Canadians to better understand how to maintain their trust as an independent national statistical office and being transparent with regard to the privacy and confidentiality of Canadians' personal information.
Statistical data requirements and funding should be explicitly included in the planning for all federal government programs. There is presently no standard or coordinated way to assess priority data requirements within the federal government. Statistics Canada works closely with most federal departments and organizations in reviewing their data needs. However, these discussions tend to involve only one or two departments at a time, reducing the scope and richness of the information collected. Statistics Canada is also often not actively consulted in the planning of new federal programs, limiting the statistical measures that should be produced.
The federal government should enable Statistics Canada to work collectively with all departments to establish, maintain and act upon a national data strategy that recognizes the interactions between economic, social, health, environmental and energy issues. Data and statistical information should be formally integrated in federal planning processes to more aptly measure, monitor and evaluate federal program outcomes.
2.1 Critical data gaps
Recommendation 2: Addressing critical data gaps
Critical data gaps and a lack of coordinated data in Canada seriously undermine the ability of decision makers and governments at all levels, as well as the general public, to understand and address key social, health, economic, environmental and energy issues facing Canadians.
Two priority areas are gaps in health and health care data in Canada, and gaps in data by race and Indigenous peoples—while respecting existing and future processes with Indigenous jurisdictions—on topics including gender, disabilities, education, employment, health, income, justice, safety, the environment, energy, community infrastructure and social well-being.
It is recommended that the Minister of Innovation, Science and Industry
2.1 invest in coordinating data collection across federal, provincial, territorial and other levels of government and organizations to build a truly national data infrastructure (including, in accordance with Recommendation 1, providing Statistics Canada with the necessary funds to develop modern real-time software and communications technologies to collect these data)
2.2 implement in the various fiscal arrangements with the provinces and territories adequate and effective mechanisms (which could include funding, incentives and penalties) to ensure that nationally consistent data can and do flow to Statistics Canada, pursuant to its mandate.
It is essential that the country's decision makers have high-quality data and statistical information that represent all regions of Canada and the full range of experiences of individual Canadians. Statistics Canada's current statistical output is vast. Users can access statistical tables, data files and analyses on just about any topic of interest.
At the same time, these data do not always tell the whole story. Information that spans the social, economic and geographic spectrum is often not available. The rapid rise of the digital economy and the impacts of climate change on the environment are examples of areas where new types of data are required to measure impacts on Canadian society and on the Canadian economy. Understanding the barriers faced by racialized groups and Indigenous Peoples also requires more detailed and disaggregated data on employment, income, health and justice.
This year's report focuses on two areas where critical data gaps have long existed. These have become especially evident recently, with the COVID-19 pandemic and increased global awareness of racial inequities.
Data gaps on health and health care
Experts have been saying for years that national health data in Canada are seriously deficient, resulting in inadequate measures of the population's health status and the functioning of the health care sector. Rectifying this situation must be a top national statistics priority. Federally, health data are collected primarily by Statistics Canada (health status and health care) and the Canadian Institute for Health Information (health system performance).
A substantial amount of health data presently exists within provincial and territorial jurisdictions, and it is increasing as hospitals and community clinics adopt new technologies to collect and use health information. This information has tremendous potential for national research on health care and population health. Yet Canada-wide health data are largely fragmented, often unavailable and inconsistent.
This became quickly apparent during the COVID-19 pandemic, when key health data were seriously lacking and inadequate for providing decision makers with the statistical indicators they needed. For example, basic information on COVID-19 confirmed cases and deaths, as well as more detailed information such as that found in hospital records, suffered from delays, incomplete and missing data, and inconsistent definitions across jurisdictions.
These data gaps and inconsistencies have led to serious shortcomings in the timeliness, completeness and quality of Canadian health care and health outcome data. In turn, this has greatly impaired the ability of governments at all levels to monitor and assess the evolution of the pandemic, let alone address serious health issues in Canada.
Barriers to national health data
Provincial, territorial and regional health authorities collect institution-specific health data primarily to administer health care services within their own jurisdictions. Consistency across regions in concepts, definitions, specific data elements collected and completeness of records is often not a priority. It takes months and sometimes longer for information as basic as that from death certificates to become part of the nationwide data that are needed to track deaths related to the pandemic. The methods used to collect medical records from hospitals and community clinics also range widely, from faxed documents to electronic records transferred directly to centralized health care databases. As well, the various software systems designed to collect and retain information such as medical records are often incompatible, limiting the information public health agencies have on important areas.
"Serious shortcomings in the timeliness, completeness and quality of Canadian health care and health outcome data have greatly impaired the ability of governments at all levels to monitor and assess the evolution of the pandemic, let alone address serious health issues in Canada."
Some health authorities have invoked provincial data protection laws as barriers to sharing certain information outside their borders. However, the sharing of identifiable data with Statistics Canada is permitted under their data protection laws, in accordance with the Statistics Act. There is also a strong reticence on the part of many provincial and territorial health organizations and communities to share data across health care systems within Canada. Some health officials do not feel that their programs should be subject to scrutiny outside their jurisdiction.
A national health data infrastructure is essential both for supporting health policies and the health care Canadians receive and, more specifically, for managing emergencies such as the current pandemic. The federal government transfers billions of dollars annually to the provinces and territories to help fund health care services, with increases likely in the future for long-term care and possibly pharmacare. The funding of these services must include a provision for nationally comparable health data to measure the state of health and health care in Canada, and the functioning of the health care sector.
Data gaps on racialized groups and Indigenous peoples
The ability to address barriers faced by racialized groups and Indigenous peoples in Canada is seriously hampered by the lack of timely, consistent and disaggregated data.
While the data gaps are not new, recent events in Canada and the United States have brought them to the forefront. For example, the data needed to properly examine the impact of the COVID-19 pandemic on the health and well-being of racialized groups, particularly Black Canadians, and Indigenous communities have not been available. Public outcry has increased following the deaths of Black people at the hands of police officers in the United States and Canada. Supporters of movements such as Black Lives Matter and Indigenous Lives Matter are demanding reforms to address systemic discrimination in areas such as health, employment, housing and justice.
Canada is among the world's most ethnically diverse countries. More than one-fifth of Canadians identify as belonging to a visible minority group. This proportion is projected to increase, as they represent a large majority of new immigrants to Canada, particularly in large cities.
Despite their growing numbers, there have been relatively few national studies of how these groups are faring in Canada. With the census as the main source of information, reports tend to be descriptive profiles of immigrants, visible minorities and Indigenous groups, including general analyses of changes in housing, employment and income. Much of the information available to decision makers is highly aggregated, partial and anecdotal.
"The ability to address barriers faced by racialized groups and Indigenous peoples in Canada is seriously hampered by the lack of timely, consistent and disaggregated data."
Canada needs much more comprehensive data to inform the current debates on the barriers many Canadians face to fully engage in all aspects of society and the economy. It is essential to look beyond the census for high-quality statistical information disaggregated by racialized and Indigenous groups that integrate elements such as family, housing, education, employment, income and well-being.
Surveys generally do not have a large enough sample size to produce detailed disaggregated data, though the Canadian Community Health Survey, the Indigenous Peoples Survey, and more recently, the Labour Force Survey do provide general trends for visible minorities and for Indigenous people living off reserve.
To make inroads in developing a national infrastructure for data by race and by Indigenous group, the focus must include governments' administrative data in areas such as labour, education, health, housing and justice. While a large number of federal, provincial and territorial government departments and organizations already share their administrative data with Statistics Canada, few of these sources include data by racialized and Indigenous groups.
There is pressure from many Canadians and decision makers for government departments to begin incorporating information on race and on Indigenous peoples into their datasets for statistical purposes. Some Canadians may hesitate to share this information with government authorities, but, at the same time, many within these groups have long called for authorities such as police forces to collect this information.
There have been encouraging initiatives. Statistics Canada is presently in discussions with the Public Health Agency of Canada and the Canadian Institute for Health Information on how nationally standardized concepts and definitions must be applied to their planned collection of race-based health data. Also, Statistics Canada and the country's police chiefs have agreed to collect this information when compiling information on victims and accused people to address data gaps for Indigenous peoples and other sociodemographic groups. Statistics Canada has also created the Advisory Committee on Ethnocultural and Immigration Statistics and the Working Group on Black Communities in Canada to counsel the agency.
Statistics Canada is engaging with national Indigenous organizations to provide statistical capacity building that is grounded in the needs of Indigenous peoples. Efforts are being made to identify where data gaps exist and how Statistics Canada data sources and expertise can help improve data quality and access, and support decision making. Statistics Canada's "Statistics on Indigenous peoples" web portal enables users to access data on Indigenous communities on topics such as children and families, health and well-being, education, and work.
Nevertheless, critical data gaps remain, and more needs to be done to address them.
2.2 Serious imbalances in funding statistical programs
Recommendation 3: Rectifying serious imbalances in funding national statistical programs
Statistics Canada is given the resources to produce economic indicators for about 20 key areas of economic activity. There are imbalances and inefficiencies in how data needs in other domains are addressed. Many of the agency's key social statistics programs, and certain economic, environmental and energy programs, are largely dependent on ad hoc funding and cost-recovery transfers from federal departments. Stable core funding for these programs is essential to support a national data strategy that includes all factors affecting society and the economy.
It is recommended that the Minister of Innovation, Science and Industry
3.1 consider options to ensure that Statistics Canada's core funding includes resources for social, economic, environmental and energy statistics programs, including the long-form census questionnaire, household surveys, administrative data, research and analysis, without having to rely on ad hoc cost-recovery transfers from departments.
It is important that public and private sector decision makers have high-quality data and statistical information that represent all regions of Canada and the full range of circumstances of individual Canadians. Stable core funding for Statistics Canada's programs is essential to having this information. Statistics Canada is given the resources to produce economic indicators for about 20 key areas of economic activity, such as the gross domestic product (GDP), consumer prices and employment. During the COVID-19 pandemic, the agency has been able to continue producing these data, which are critical for assessing the economic impact of the crisis. However, there is an increasing focus on social and environmental data, which measure other important contributors to well-being, beyond the traditional economic measures. This is reflected in a growing international consensus on the need to go beyond the GDP, recognizing that social, health, economic and environmental factors all affect people's well-being. How these various factors interact and affect each other also has significant impacts on individuals, as well as on national and regional economies.
Many of Statistics Canada's key social statistics programs, and certain economic, environmental and energy programs, are largely dependent on ad hoc funding and cost-recovery transfers from federal departments. Support for these programs is often based on the siloed needs of one or two departments. These programs' vulnerability to cuts can significantly affect important and more comprehensive data needs and areas of research. Stable core funding for these programs is essential to support a national data strategy that includes all factors affecting society and the economy.
"Stable core funding for Statistics Canada's programs is essential to having high-quality data and statistical information that represent all regions of Canada and the full range of circumstances of individual Canadians."
3. Privacy and data sharing
Recommendation 4: Ensuring the privacy of Canadians and the need for Canadians to provide data to Statistics Canada
Statistics Canada has the legal authority to collect federal, provincial and territorial data under the Statistics Act. Most jurisdictions include provisions in their data protection laws to permit data sharing for statistical purposes. The act also gives the agency the authority to collect data from private sector sources, in conjunction with government data, to provide a multifaceted statistical portrait of the country. The confidentiality of this information is protected under the Statistics Act.
There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada.
It is recommended that
4.1 Statistics Canada and the Minister of Innovation, Science and Industry work with the Minister of Justice, informed by the Privacy Commissioner of Canada and by Indigenous jurisdictions, to ensure that federal, provincial and territorial data protection laws and policies are attentive to the imperative of data sharing for statistical purposes, and to ensure that there are no legislative ambiguities with regard to Statistics Canada's authority under the Statistics Act to collect data from federal, provincial and territorial jurisdictions
4.2 Statistics Canada and the Minister of Innovation, Science and Industry start a dialogue with Canadians on the importance of data for evidence-based decision making, and on how the collection of these data must respect data protection laws and the confidentiality of Canadians' personal information
4.3 Statistics Canada proceed, with support from the Minister of Innovation, Science and Industry, with its projects to develop new data sources from financial and credit institutions, in accordance with the agency's methodological framework on necessity and proportionality, and inform Canadians why these data are needed and how they will be collected and stored.
Statistics Canada has the authority under the Statistics Act to collect personal data to produce the social and economic statistical information that forms the foundation for data-driven decision making for the well-being of all Canadians. For over 100 years, Canadians have provided this information to Statistics Canada, which has maintained the confidentiality of these data and produced statistics without revealing identifiable information about individuals, in accordance with the Statistics Act.
It is essential that citizens understand the importance of evidence-based decision making for Canada to succeed in the new data economy. Governments also need to recognize that traditional ways of collecting information are no longer sufficient. They must support Statistics Canada in its work to provide the key statistical information needed by governments and Canadians to address the increasingly complex and dynamic challenges they face.
There should be a more extensive conversation with Canadians about the alignment between privacy and the need for data for effective decision making. This discussion would facilitate mutual understanding by Canadians and governments of the issues at hand and provide a forum for the exchanges that need to occur for Canada to truly benefit from an independent and trusted source of official statistics. The country needs a solid foundation for government accountability and evidence-based decision making by both the public and the private sectors.
"There should be no conflict between respect for the privacy of Canadians and the need for Canadians to provide data to Statistics Canada."
Statistics Canada has been working with expert groups in Canada and with national statistical offices from around the world to explore the possibility of producing high-quality statistics from digital administrative data—both data from governments (e.g., tax files, health care encounters, property tax assessments, driver's licences) and big data from the private sector (e.g., retail transactions, credit card transactions, mortgages, other debt). Being able to use these new, primarily electronic, sources of data will enable Statistics Canada to address the critical needs for new and more disaggregated data in Canada—data that are integrated across the social, health, economic, environmental and energy domains.
Many countries are reviewing their data protection laws, given both the dramatic increase in the prevalence and use of personal information from administrative data, and growing concerns about the data holdings of multinational social media companies. In doing so, they recognize the importance of collecting personal information for specific legitimate purposes, when done under the country's legal authority and in a transparent manner. For example, the European Union's General Data Protection Regulation recognizes the need for national statistical offices to access personal information, permitting the flow of the information for statistical research for the public good, without requiring consent.
In Canada, Statistics Canada's project to collect detailed data on banking and credit card transactions has drawn particular attention. These new sources of information are key to addressing emerging critical data gaps in Canada's economic and financial measures as a result of important changes to consumer patterns and debt. In response to concerns raised by some Canadians, Statistics Canada suspended its work to address them before proceeding with the project. The agency is also collaborating with the Office of the Privacy Commissioner to address concerns as a result of complaints it received about this project. After investigating these complaints, the Privacy Commissioner of Canada concluded that Statistics Canada was not in contravention of the Privacy Act.
The need for transparency on matters of privacy and confidentiality is essential to maintaining public trust. Statistics Canada must clearly inform Canadians why the information it collects is needed and explain the measures it takes to protect the confidentiality of Canadians' personal information. The need for transparency is especially heightened in this project, given the sensitivity of personal banking information and the volume and detail of information that may be collected.
Moving forward, the agency needs to engage with a focus on guiding principles to meet the rapidly changing data context. Statistics Canada is working in consultation with the Privacy Commissioner of Canada to develop a new methodology framework based on the principles of necessity and proportionality. This methodology framework, which the agency is sharing with the global statistical community, is a significant and thoughtful initiative.
The framework recognizes Statistics Canada's legal authority under the Statistics Act to collect personal information for statistical purposes, and Statistics Canada's legal obligation under the same act to ensure the confidentiality of this information. The framework also recognizes the country's data protection laws. These include the federal Privacy Act, which sets out how personal information held by the federal government and federal public sector institutions is used, stored and shared, and the Personal Information Protection and Electronic Documents Act, which sets out how organizations engaged in commercial activities must handle personal information.
3.1 Provincial and territorial data sharing
The provinces and territories have a long history of sharing administrative data with Statistics Canada in areas such as vital statistics, education and justice. Statistics Canada has the authority to collect these data under the Statistics Act, and most provinces and territories have provisions in their data protection laws to enable them to share data for statistical purposes for the public good.
For many years, some provincial and territorial health authorities have invoked provincial data protection laws as barriers to sharing certain health data. This has contributed in part to the poor state of national health data, as seen during the COVID-19 pandemic. In response to questions about privacy issues during the pandemic, the Privacy Commissioner of Canada stated that, "During a public health crisis, privacy laws still apply, but they are not a barrier to appropriate information sharing."
Discussions about data sharing must be broadened to include priority needs for national data. To make measurable progress, Statistics Canada must have federal government support to play a leadership role and build on the new avenues of government collaboration created in response to the pandemic.
Many provinces and territories are reviewing their data protection laws to take into account new technologies for collecting and sharing personal information. Statistics Canada must work with them to ensure that revisions to data protection laws recognize the importance of official national statistics and that there are no legislative ambiguities with regard to Statistics Canada's legal authority to collect data from their jurisdictions.
4. Microdata access
Recommendation 5: Modernizing microdata access
The need for a modern infrastructure to access Statistics Canada's microdata, including secure remote access, has never been greater, as duly authorized researchers undertake statistical analysis to inform governments and Canadians.
It is recommended that the Chief Statistician
5.1 give high priority to and accelerate the modernization of the Microdata Access Program, including providing secure remote access by duly authorized researchers to its anonymized microdata and streamlining the current authentication process for granting secure access to Statistics Canada's microdata.
The need for a modern infrastructure to access Statistics Canada's microdata, including secure remote access, has never been greater, as duly authorized researchers look to inform governments and Canadians on issues such as the social and economic impacts of the COVID-19 pandemic.
To meet the specific information needs of Canadians, the agency has introduced web portals to transform complex data into easy-to-understand visuals. The "COVID-19: A data perspective" portal is a good example. Created in response to the pandemic, it provides governments and Canadians access in one place to a wide array of relevant health, social and economic statistical information with tables, infographics, interactive maps, data visualizations and statistical analyses.
For many years, Statistics Canada has provided students and researchers with a range of ways to access data, with strict security restrictions for access to confidential microdata. Non-confidential Public Use Microdata Files are used extensively by postsecondary students through the Data Liberation Initiative. Students and duly authorized researchers can also use the online Real Time Remote Access system available for most social surveys. The output is largely descriptive and useful for general findings and preliminary research activities. It presently requires knowledge of SAS programming, which limits access to the data for some researchers.
Confidential microdata can be accessed through Statistics Canada's Research Data Centres (RDCs). These are secure facilities located on university campuses that offer access to Statistics Canada's more detailed—and therefore most analytically powerful—data holdings. They include detailed microdata from Statistics Canada's household surveys, census data and an increasing number of administrative datasets such as the cancer registry. Since the opening of the first RDC in 2000, the Canadian Research Data Centre Network has expanded and now includes over 30 secure data laboratories in which over 2,000 duly authorized researchers across Canada conduct advanced quantitative social science and health research.
Secure access to anonymized business and economic microdata is provided to government researchers through the Canadian Centre for Data Development and Economic Research Program at Statistics Canada headquarters in Ottawa.
4.1 Modernizing the Microdata Access Program
The RDCs, with their physical data laboratories, have become outdated and are no longer able to adequately support Canada's research and analysis needs. The COVID-19 pandemic has made clear the need for Statistics Canada to transition from the RDCs' physical infrastructure to new distributed modes of access. Once a world leader, Statistics Canada has fallen behind. The agency is currently modernizing its microdata access infrastructure with more sophisticated datasets, secure remote access technologies and expansion of secure access to anonymized business data in the RDCs. This is a long-awaited initiative that will greatly improve the quality and depth of research and analysis in Canada across all sectors. However, the timeline of well into 2022 for full implementation of secure remote microdata access is too long and should be accelerated.
"The modernization of Statistics Canada's microdata access infrastructure is a long-awaited initiative that will greatly improve the quality and depth of research and analysis in Canada across all sectors; however, its timeline for full implementation is too long and should be accelerated."
With the wealth of statistical information, data expertise and technical savvy found in public, academic and private institutions across the country, there are tremendous opportunities to transform how data are developed and used in Canada. Researchers in Canada currently have secure access to a vast amount of data from a wide range of sources, including from government administrative data sources, universities and the private sector. The explosion of big data and data analytics is also generating a growing pool of talented data scientists. A modernized research data access program will greatly facilitate and support the statistical research required to address the increasingly complex and multifaceted issues faced by Canadians.
Statistics Canada must also modernize and streamline its administrative processes, such as the authentication of researchers. Statistics Canada should look to international models such as that used in the Netherlands, where the authentication process includes a class of "duly authorized researchers" who may be required to take training on privacy and security and must be affiliated with a government department, university or institute for scientific research. As in Canada, research must be for statistical purposes as opposed to private commercial research.
There is also interest from national and regional Indigenous organizations in developing and implementing information and research data centres in their communities. This would provide Indigenous peoples with better access to Statistics Canada microdata and other Indigenous microdata on the health, social and economic well-being of Indigenous communities. Analytic capacity would also be expanded to include the use of new data, analytic techniques and technology to support research, planning and development and to build statistical capacity to assist vulnerable Indigenous communities.
Definitions
Administrative data
are holdings of individual records collected by government departments and other organizations for the purpose of administering benefits, services and taxes. Under provisions of the Statistics Act, administrative data can be shared with Statistics Canada for statistical purposes.
Microdata
are individual records containing information collected from the census, surveys, administrative data and other sources. They may represent an individual, a household, a business or an organization. The confidentiality of identifiable information about individuals is protected under the Statistics Act.
Nationwide data
are data collected from the census, surveys, administrative data and other sources that represent all Canadians, including at the individual and household levels. They include pooled and integrated administrative data collected from provincial and territorial jurisdictions. The data are aggregated to produce national social and economic statistics, such as employment rates, life expectancy and gross domestic product. These data can be grouped by social and economic characteristics and can be analyzed statistically to examine issues such as socioeconomic inequalities and health outcomes.
Necessity and proportionality
refer to principles applied to the collection of information. The agency considers needs for data to ensure the well-being of the country (necessity), and it also tailors the volume and detail of the data collected to meet these needs (proportionality).
Statistical information
is the added value to statistics resulting from quantitative interpretation, modelling and analysis. This can take many forms, including charts, interactive visualizations and analytical articles.
The Employment Equity Act defines members of visible minorities as "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour." Many data users use visible minority as a proxy for race.
Under the authority of the Statistics Act, Statistics Canada is hereby requesting the following information, which will be used solely for statistical and research purposes and will be protected in accordance with the provisions of the Statistics Act and any other applicable law. This is a mandatory request for data.
Statistics Canada is requesting a list of federally appointed judges, including the following variables: first and last name (or a unique identifier), gender (or sex), type of court, location (of court), and appointment start date and appointment end date (or removal).
What personal information is included in this request?
This request contains personal information such as the first and last name (or unique personal identifier) and gender (or sex) of federally appointed judges. The personal identifiers are required to perform data processing activities only, such as removing duplicates from files, imputing missing values (if necessary) and tracking records over time. Only aggregate statistics will be disseminated.
What years of data will be requested?
Annual data as of 2018 is being requested.
From whom will the information be requested?
This information is being requested from the Office of the Commissioner for Federal Judicial Affairs Canada
Why is this information being requested?
Introduced in Budget 2018, the Gender Results Framework (GRF) represents the Government of Canada's vision for gender equality. The GRF contains 43 indicators designed to track how Canada is currently performing; define what is needed to achieve greater equality and determine how progress will be measured going forward.
Greater gender balance and diversity in the judicial system will enable the system to be more responsive to the differing needs and situations of all Canadians.
Statistics Canada is requesting this information to create and publish statistics on the gender distribution of federally appointed judges. These statistics will be used by policy makers and researchers to track the gender distribution of federally appointed judges over time.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
The Office of the Commissioner for Federal Judicial Affairs Canada (FJA) is responsible for collecting demographic information on judicial applicants and appointees based on voluntary disclosure by candidates through self-identification.
When will this information be requested?
December 2020 and onward (yearly)
What Statistics Canada programs will primarily use these data?
List of employees and work email addresses for Government employees working in Nunavut
What information is being requested?
Statistics Canada is requesting employee information for government employees working in Nunavut to create the Nunavut Government Employee Survey (NGES) survey frame. The requested information includes employee lists containing their Personal Record Identifier (PRI), full name, sex, date of birth, department name, and work email addresses.
What personal information is included in this request?
This request contains personal information such as the employee's PRI, first name, last name, sex, date of birth, work email address, and department name.
Personal identifiers, including PRI, first name, last name, sex, date of birth and department name, are necessary to update the survey frame and facilitate data linkages for statistical purposes only. The data will be linked to federal employee payroll files, which are currently used by Statistics Canada, to create the NGES survey frame. Once the data are linked, all direct identifiers - such as names, addresses, telephone numbers, or any other identifying information - will be removed and the data will be anonymized.
What years of data will be requested?
The NGES is conducted every five years.
Data will be collected starting with the 2021 reference year.
From whom will the information be requested?
This information will be requested from government departments with employees located in Nunavut.
Why is this information being requested?
Article 23 of the Nunavut Agreement aims to increase Inuit participation in government employment to a representative level through an ongoing Nunavut Inuit Labour Force Analysis (NILFA). By strengthening Inuit representation in public institutions in Nunavut, the NILFA is supporting Inuit self-determination. As a signatory to the Nunavut Agreement, the NILFA is a federal government obligation.
Statistics Canada is requesting this data to verify and update employee payroll data (already held by Statistics Canada's Centre for Labour Market Information Division) which is used to create the Government of Canada component of the NGES frame. Work email address will also be used to send the electronic questionnaire link to Government employees in Nunavut.
As part of the NILFA, the NGES was designed to collect data on Inuit enrolled under the Nunavut Agreement regarding their availability, interest and level of preparedness for government employment. This data informs the development of Inuit Employment Plans and Pre-Employment Training Programs within both the Government of Nunavut, as well as the Government of Canada within Nunavut.
Nunavut Tunngavik Incorporated, which represents the interests of Inuit enrolled under the Nunavut Agreement, and a member of the NILFA Technical Working Group, supports this data acquisition. Without the acquisition of these data, Statistics Canada would not be able to ensure all individuals in the NGES target population are identified on the survey frame. Furthermore, the agency would not be able to send out the electronic questionnaire link to the survey sample of Government employees in Nunavut, ultimately excluding them from the survey.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
These organizations meet the definitions in Article 23 of the Nunavut Agreement because they are Federal departments that have offices in Nunavut, and Treasury Board is their employer.
When will this information be requested?
Starting in September 2020
What Statistics Canada programs will primarily use these data?
Language has been updated to make it clear that this is an ongoing request as the NGES occurs every five years.
Revenue and expenditures
Data on support for businesses through the Business Innovation and Growth Support (BIGS) programs
What information is being requested?
Information on the support granted through the governmental BIGS programs. Such information includes the value of support, the transaction dates, the types of support, the names of the beneficiary enterprises, their business number, their contact information, the project numbers, the effective dates of the agreements, and the amounts of the agreements.
What personal information is included in this request?
This request does not contain any personal information.
What years of data will be requested?
Open-ended, data beginning with the 2007 reference year.
From whom will the information be requested?
From all federal departments or agencies that have Business Innovation and Growth Support (BIGS) programs.
Why is this information being requested?
Statistics Canada requires this information to produce and publish statistics on government programs that support business growth and innovation. These statistics will help Statistics Canada, together with the Treasury Board Secretariat, identify the impacts of business innovation and growth support programs. The data will also be used by policy makers, researchers and stakeholders to assess and measure the performance of these programs.
Statistics Canada may also use the information for other statistical and research purposes.
Why were these organizations selected as data providers?
These organizations collect information on the business innovation and growth programs they administer and keep that information up to date.
When will this information be requested?
Starting in April 2021
What Statistics Canada programs will primarily use these data?