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Discover more about data (view source)
Revision as of 15:03, 14 February 2022
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<p>For data science enthusiasts: Find resources, training, tools, and communities.</p>
<p>For data science enthusiasts: Find resources, training, tools, and communities.</p>
<p class="recco">Recommended by Agriculture and Agri-Food Canada, a GC Data Community partner</p>
<p class="recco">Recommended by Agriculture and Agri-Food Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www.tbs-sct.gc.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making]</h3>
<p>The Government of Canada is increasingly looking to utilize artificial intelligence to make, or assist in making, administrative decisions to improve service delivery. The Government is committed to doing so in a manner that is compatible with core administrative law principles such as transparency, accountability, legality, and procedural fairness. Understanding that this technology is changing rapidly, this Directive will continue to evolve to ensure that it remains relevant.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/eng/data-science/network/automated-systems Responsible use of automated decision systems in the federal government]</h3>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/eng/data-science/network/automated-systems Responsible use of automated decision systems in the federal government]</h3>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science Data Science Centre]</h3>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science Data Science Centre]</h3>
<p>In this rapidly-changing digital era, statistical agencies need to find innovative ways to harness the power of data. Statistics Canada is embracing the possibilities of data science to better serve the information needs of Canadians.</p>
<p>In this rapidly-changing digital era, statistical agencies need to find innovative ways to harness the power of data. Statistics Canada is embracing the possibilities of data science to better serve the information needs of Canadians.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science/network Data Science Network for the Federal Public Service]</h3>
<p>Looking for a dynamic space to collaborate and learn about data science? Join the new Data Science Network for the Federal Public Service. Our vision is to create a vibrant community of data science enthusiasts and to offer a dynamic space for members to collaborate and learn about data science.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h2>Tools</h2>
<h2>Tools</h2>
<h3 style="text-decoration:none;">[https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/algorithmic-impact-assessment.html Algorithmic Impact Assessment Tool]</h3>
<p>The Algorithmic Impact Assessment (AIA) is a mandatory risk assessment tool intended to support the Treasury Board’s Directive on Automated Decision-Making (“the Directive”). The tool is a questionnaire that determines the impact level of an automated decision-system. It is composed of 48 risk and 33 mitigation questions. Assessment scores are based on many factors including systems design, algorithm, decision type, impact and data.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www150.statcan.gc.ca/n1/pub/89-20-0006/892000062021001-eng.htm Framework for Responsible Machine Learning Processes at Statistics Canada ]</h3>
<p>This document is a handbook for practitioners developing and implementing Machine Learning (ML) processes. It provides guidance and practical advice on how to responsibly develop these automated processes within Statistics Canada but could be adopted by any organization. They can be applied to processes that are put in production or that are dealing with research.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
[[Image:Data-interoperatiblity_guide-UN.png|150px|Data Interoperability Guide]]
[[Image:Data-interoperatiblity_guide-UN.png|150px|Data Interoperability Guide]]
<p class="author">from Statistics Canada</p>
<p class="author">from Statistics Canada</p>
<p>In the news: daily releases.</p>
<p>In the news: daily releases.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science/network/newsletter Data Science Network for the Federal Public Service newsletter]</h3>
<p>Keep up to speed on the latest news in the world of data science by subscribing to the Network newsletter: Data Science Bits and Bytes—your source of info for all things data science in the Government of Canada and beyond.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>