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Data Matters in 2025 Platforms – 1/5

April 20, 2025 in Uncategorized by Tracey | Permalink

During election time, I have a tradition to review published political platforms. To date only 3/5 parties have published these as seen below. In 1/5 I review what the Liberal pitch.

  1. Liberal Party of Canada – Canada Strong, Document, website
  2. Bloc Québécois – Choisir le Québec, Document, website
  3. Green Party of Canada – Change, Vote for it, Document, website
  4. Conservative Party of Canada – Canada First for a Change – Document????, website
  5. New Democratic Party of Canada – Made for People, Built for Canada – Document???, website

My methodological process is very rudimentary, guerrilla testing like & expedient: I download the document, I peruse, do a word search for data related matters, take some screen captures & count the incidence of the use of the term & do a cursory assessment of the term is used for some context.

1/5 the Liberal Party of Canada Platform

Here is what I saw in the Liberal Party of Canada, Canada Strong Platform. This is what I look at:

  • openness, followed by
  • mis/disinformation,
  • connectivity,
  • earth observation, followed by
  • data, technology, AI and
  • digital closing with
  • other data & technology related topics
  • full count

Openness

I have been watching openness since the early 2000s, especially during the Harper years (2006-2011) & especially after the cancellation of the long-form Census (2011) and during COVID. Openness was prominent in platforms in 2006 but alas, no it is more. Not even ethics! This is of concern as w/so much new money going into data, digital, AI, Innovation and technology projects, one would think that accountability in terms of procurement and contracting; as is transparency and ethics. It is most disconcerting as the platform mentions reducing ‘red tape’ in terms of technology & digital & AI procurement. Open science, is also absent, odd considering the focus on AI and the 3 main AI centres and the AI Data Act. Science is mentioned in terms of R & D & investment, but alas, not the social sciences (0) and universities were mentioned twice but only Nunangat University and the First Nations University while data science or critical data science education were not discussed. There is also nothing about measuring the impact of investments and related indicators to monitor the progress of decisions.

  • Open Data = 0
  • Open Government = 0
  • Open Science = 0
  • Ethics = 0
  • Indicators = 0
  • Accountability = 2 (w/CBC)
  • Transparency = 4 (w/labeling in supply chains, risk disclosure for energy, corporate taxes & budget)
  • Science = 6 (R&D, investment in startups, research)

Mis/Disinformation & fake news

Mis/Disinformation & fake news have been of concern during elections since Brexit & the Cambridge Analytica Scandal as discussed in the 2018 UK Information Commissioner Office Democracy Disrupted: Personal information and political influence. Elections Canada has also been monitoring the social media information ecosystem for interference as seen in their Democratic Processes–Protecting Against Threats to the Electoral Process. This is such an important sovereignty issue, and considering that sovereignty was mentioned 42 times in the platform. This is what I counted:

  • Social Media = 0
  • Misinformation = 0
  • Data Brokers = 0
  • Ethics = 0
  • AI (the role of) = 0 (even though there is important investment)
  • Disinformation = 2 (w/against US media & tools to track – both CBC)

Connectivity

Connectivity is required to move data, and I would have expected a conversation about communication satellites especially in light of the cancellation of Starlink contracts & conversations of digital sovereignty, high costs, and AI investment & compute needs, but alas only 1 mention of rural broadband, 1 for high speed but in the context of AI, but not internet nor the digital divide. Data centres are mentioned twice but not cloud computing, while AI is mentioned 30 times. How are data supposed to move without infrastructure investment in connectivity with all the new data centres and new monies in this field? In terms of infrastructure only 2 of the 55 mentions, discussed connectivity. Also, what of Indigenous communities and connecting the North, even with addtional EO monitoring and surveillance?

  • Broadband = 1 (rural)
  • Internet = 0
  • Digital Divide = 0
  • Cloud computing = 0
  • High speed = 1 (w/AI)
  • Data Centres = 2 (w/AI, industry)
  • Satellites = 2 (Monitor the North, Monitor the Oceans & w/GPS & Drones)
  • Infrastructure = 55 (53 for hard & social infrastructure, 1 w/digital & 1 high speed)

Earth Observation(EO) w/ Eyes in the sky

Earth Observation w/ Eyes in the sky as in radar and earth observation (EO) satellites are back, they were a political issue in 2017 when the sale of Radarsat to Lockheed Martin was stopped for sovereignty reasons, and now satellites, drones, GPS and radar to monitor borders, coasts, the North, The Arctic, the seas, the air and underwater tool. The remote sensing folks might get a major R & D boost and the platform is mostly about the North.

  • Radar = 2 (w/monitoring the Arctic)
  • Satellites = 2 (Monitor the North, Monitor the Oceans & w/GPS & Drones)
  • Drones = 3 (persistence presence in the Arctic, to survey the seas and boders)

Data & Technology

Data & Technology, data are inseparable from the tools & technologies used to create and generate them and in this platform, arguably most of the big promises involve data and systems to management them, including supply chains and logistics, and of course EO technologies part of these. Here I focus on what was mentioned, not what is implied as Data (15), AI (30), Technology (27) & Digital (12).

  • Data (15) – this is the first time I see data & sovereignty mentioned but limited to monitoring transactions to protect the economy and cross border data exchange, it is also mentioned in terms of sharing & access to health care data where they can follow you regardless of which jurisdiction you are in, the usual suspects such as data storage, data centres, and data analysis for surveillance are mentioned, but also data collection to monitor the environment, & women’s health. There is no mention of data governance, or of a data strategy, nor the means to protect people from the harms of data brokers, AI, mental health apps and so on and no mention of open data!
  • AI (30) – There is no AI without data, thus the surprise at the lack of data governance and a data strategy, but also, there ought to also no AI without ethics! The Artificial Intelligence and Data Act (AIDA) is also not mentioned, but AI in terms of AI military support, surveillance & security, (6), Canadian economy and innovation (3); AI infrastructure, AI-powered data analysis to protect shores, AI to monitor & protect fresh water, AI to support innovation, AI to ensure competitiveness, AI for better service deliverly, AI & Energy, investment in AI training, adoption & commercialization, AI tax incentives, AI to support AI research such as Mila, Vector, Amii (how did they get such an honourable mention?) & AI to grow the ecosystem; AI procurement & a new Office of Digital Transformation, the support for mid-level career AI education, AI & cybersecurity, AI to improve the public service delivery. This is a very technologically solutionist & industry & approach, but not much in the way of AI for wellbeing; there is not discussion of AI & its ecological footprint, & AIDA. The new office of Digital Transformation is of concern as it is about centralizing, speeding up decisions and reducing red tape in terms of AI procurement
  • Technology (27) – although frequently mentioned, it is not so much ICTs, and when it is, it is for advanced R & T and defence BOREALIS; drone fleets; AI tech solutions, fraud detection solutions for CRA, for the public service and water security technology, the rest are green tech, clean tech, carbon storage related tech (3) and as capital investment. The bulk of the technology discussion is surveillance and the military, but it is very nice to see a focus on green tech and clearly AI is tech but they are not mentioned together often.
  • Digital (12) – Here it is about building a digital AI infrastructure, digital supply chains, digital tools for the news, digitalization, digital health, marine digital solutions, digital innovations & patents, improving the public service with a new Office of Digital Transformation to improve the Canadian tech sector but also to reduce red tape, and we know how well that is going in the south!!! .

Other data & technology related topics

Here are frequently mentioned topics that are related to data, but alas, I had to stop somewhere in terms of analysis. It is surprising though that Digital Sovereignty is not a major issue!

  • Climate (28) Supply chain (14), Carbon (20), Net-Zero (2) and of course Sovereignty (42) but not data sovereignty.

The full list in order of the # of mentions in the Liberal Platform.

  • Open Data = 0
  • Open Government = 0
  • Open Science = 0
  • Social Media = 0
  • Cloud computing = 0
  • Data Brokers = 0
  • Digital Divide = 0
  • Ethics = 0
  • Indicators = 0
  • Internet = 0
  • Misinformation = 0
  • Broadband = 1 (rural)
  • Connectivity = 1 (w/electricity)
  • High speed = 1 (w/AI)
  • Data Centres = 2 (w/AI, industry)
  • Disinformation = 2 (w/against US media & tools to track – both CBC)
  • Radar = 2 (w/monitoring the Arctic)
  • Satellites = 2 (Monitor the North, Monitor the Oceans & w/GPS & Drones)
  • Accountability = 2 (w/CBC)
  • Drones = 3 (underwater & air & borders)
  • Transparency = 4 (w/labeling in supply chains, risk disclosure for energy, corporate taxes & budget)
  • Science = 6 (R&D, investment in startups, research)
  • Digital = 12 (see breakdown below)
  • Data = 15 (see breakdown below)
  • Technology = 27 (see breakdown below)
  • Climate = 28 (see breakdown below)
  • Artifical Intelligence (AI) = +/-30 (see breakdown below)
  • Infrastructure = 55 (53 for hard & social infrastructure, 1 w/digital & 1 high speed)
  • New concepts I do not recall ever being so prominent:
    • Climate (28) Supply chain (14), Carbon (20), Net-Zero (2) and of course Sovereignty (42).

That is all for now folks, happy easter!

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Tracing COVID-19 Data: Data and Technological Citizenship during the COVID-19 Pandemic

June 1, 2020 in academia, Access, canada, COVID-19, datasets, federal government, government, health, infrastructure, Open Data, openmovement, policy by Tracey | Permalink

I was just awarded a small but not insignificant award as part of the Carleton University COVID-19 Rapid Response Research Grants. Below is a description of what I will be up to, along with some great students and expert advisors.  I will share everyone’s names later.  Results of the work will be published here as it becomes available!  Stay tuned. Also, let me know if you want to contribute in any way! Tracey dot Lauriault at Carleton dot CA

Research Summary

There is much official COVID-19 data reporting by federal, provincial, territorial and Indigenous Communities. As the pandemic evolves, and more information comes to light, there is a call to add data attributes about Indigenous, Black and Racialized groups and of the affected labour force, and to report where cases predominate. The pandemic also revealed that foundational datasets are missing, such as a national list of elder care homes, maps of local health regions and data about the digital divide. This project will embrace technological citizenship, adopt a critical data studies theoretical framework and a data humanitarian approach to rapidly assess data shortfalls, identify standards, and support the building of infrastructure. This involves training students, conducting rapid response research, developing a network of experts, learning by doing and a transdisciplinary team of peer reviewers to assess results. The knowledge will be mobilized in open access blog posts, infographics, policy briefs and scholarly publications.

Research challenge:

Official COVID-19 public heath reports by Federal, Provincial, and Territorial (F/P/T) and First Nation Communities are uneven and there are calls to improve them ( 1 CBC News, Toronto Star). Asymmetries can be attributed to dynamically evolving challenges associated with the pandemic, such as working while practicing social distancing; jurisdictional divisions of power in terms of health delivery; and responding to a humanitarian crisis, where resources are stretched and infrastructures are splintered (i.e. digital divide, nursing home conditions).

The Harvard Humanitarian Initiative (HHI) developed a rights-based approach to the management of data and technologies during crisis situations which includes the right to: be informed, protection, privacy and security, data agency and rectification and redress (2). These apply to contact tracing (3 ITWorld, Scassa) and to equity groups calling for demographic data (1). Other have conducted rapid response data reporting, for example after the Haiti Earthquake volunteers developed real-time crowdsourcing data collection systems to support humanitarian responders (4 Meier) and WeRobotics mobilizes local drone expertise to objectively assess proposed pandemic response technologies (5 WeRobotics).

This research will apply a critical data studies (CDS) theoretical framework (6 Kitchin & Lauriault), the principles of the HHI and, practice technological citizenship (7 Feenbert) to the study of the Canadian COVID-19 data response. Lauriault will leverage her expertise and Canadian and international network of open data, open government, civic technology experts in government, civil society, and Indigenous Communities (see CV) as seen in the policy briefs published on DataLibre.ca (8) to rapidly assess and support COVID-19 data management and reporting.

The objective is to carry out the following activities:

  1. Compare official COVID-19 public health data reports to identify gaps and best practices (9 Lauriault & Shields).
  2. Identify and support the building of framework datasets to standardize reporting (10 Lauriault).
  3. Analyze data standards and protocols to support data management, interoperability and cross-jurisdictional reporting (11 GeoConnections).
  4. Publish case-studies, resources, an archives of official reporting, and a glossary and
  5. Rapidly conduct expert analysis, peer review, knowledge mobilization and provide evidence-based recommendations to improve data reporting.

The rationale for this research is as follows:

  1. Official COVID-19 public health data are inconsistently reported, impeding comparability, and the ability to assess impact and target actions. Also, predictions missed seniors’ homes, precarious labour, and Indigenous communities and social determinants (12 Global News, NCCDH), resulting in an increase in cases and deaths. Currently job classifications and Indigenous, Black, and Racialized people classifications (13 CTV News) remain absent. This research will create a corpus of F/P/T and Indigenous Communities’ official reports, compare results, identify gaps.
  2. Framework data are standard information infrastructures upon which other analysis can consistently be done (14 Toronto Star). When this is lacking analysis is impeded, for example there is no national reporting by health region since no national framework dataset exists (15 Lauriault), and mitigating the digital divide is thwarted with a lack of broadband maps (16 Potter & Lauriault et al.). Other missing national datasets include senior care facilities, homeless shelters, precarious labour, and Indigenous Communities (17 Gaetz et al.). Needed framework datasets will be identified and if necessary coordinate their building (18 SPCO, StatCan LODE), advocacy for the opening of public datasets such as corporate registries may be carried out (19 Fed. Registry,  Open Corporate, Open Contracting), and experts from public health , social planning, and Indigenous Communities will help identify localized frameworks.
  3. Consistent COVID-19 reporting requires an interoperable infrastructure which builds upon standards developed through consensus processes (20 CIHI, PHAC). Current uneven reporting may be attributed to a lack of standards adoption and formalization in terms of data flows. This research will develop a repository of standards and protocols and share these with decision-makers to improve interoperability (i.e. Data Standards for the Identification and Monitoring of Systemic Racism (21 ON Govt) and FNIGC OCAP Principles (22 FNIGC)).
  4. Rapidly mobilizing knowledge is important to improve reporting and manage data, and to build a crisis data reporting infrastructure for the future. This project will compile, and archive information, rapidly assess and peer review results with experts and report results on DataLibre.ca and other websites, will produce infographics and policy briefs, deliver online webinars, and help administrators and Indigenous Communities improve their data and technology policies.

A CDS framework recognizes that data have social and material shaping qualities and that they are never politically neutral while also being inseparable from the people and institutions who create them including practices, techniques, and infrastructures. This involves a team of data, technology, legal, social and health, and Indigenous experts to rapidly assess official COVID-19 data assemblages and to act as technological citizens by applying knowledge in real time and mobilize results to mitigate the data shortfalls witnessed during this crisis and support decision makers to respond with a data humanitarian and rights-based approach for now and to better respond in the future.

Expected Impact:

The target audience for this rapid response data and technology reporting is F/P/T public officials and Indigenous Community Leaders who manage public health, socio-economic, statistical and official record data flows; and civil society actors and the public involved in open data, open government and open contracting, transparency and accountability. This includes C-class executives, chief technology, information data, and digital officers.

The outcome of this research is to standardize and improve humanitarian crisis data management and data reporting in the short term to ensure consistent reporting, and in the long term establish standardized data workflows and operationalize data infrastructures for this pandemic in preparation for the next.

The timing to compile, inventory and build an open access archives of official data reporting is now as the fractures in the system have become apparent in real-time and have had negative consequences. It is important to monitor the response as it evolves so as to be able to improve it while our collective institutional memory is fresh and to have the evidence available as a reminder for if and when we forget, but also to build more robust systems.

The results of this research will be continuously reported and made openly accessible as it becomes available and will lead to the formation of a new research team.

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