875
edits
Changes
Jump to navigation
Jump to search
Line 59:
Line 59: − + − <strong>[https://expo.da-an.ca Virtual Expo]</strong> | − + − <!--<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Announcements Announcements]</strong>-->+ Line 87:
Line 86: − + Line 112:
Line 111: + + + + + Line 174:
Line 178: + + + + Line 465:
Line 473: + Line 471:
Line 480: + Line 499:
Line 509: + Line 526:
Line 537: + Line 569:
Line 581: +
Discover more about data (view source)
Revision as of 14:30, 21 February 2023
, 14:30, 21 February 2023no edit summary
[[Image:DataCon2022-Banner-EN.png |100%|Data Conference 2022: Driving Data Value and Insights for All Canadians, 23 + 24 February 2022]]
[[Image:DataCon2022-Banner-EN.png |100%|Data Conference 2022: Driving Data Value and Insights for All Canadians, 23 + 24 February 2022]]
<p style="background-color: #f18f34; padding: 5px; width:1130px""><small>
<p style="background-color: #f18f34; padding: 5px; width:1130px""><small>
<strong>[https://www.csps-efpc.gc.ca/events/data-conference2022/index-eng.aspx Register now]</strong> |
<strong>[https://vexpodev.z9.web.core.windows.net/en/#/2203/lobby Virtual Expo]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda Agenda]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda Agenda]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Speakers Conference speakers]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Speakers Conference speakers]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Networking_Missions Networking Missions]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Networking_Missions Networking Missions]</strong> |
<strong>[https://wiki.gccollab.ca/Discover_more_about_data DISCOVER MORE ABOUT DATA]</strong> |
<strong>[https://wiki.gccollab.ca/GC_Data_Conference_2023/Discover_more_about_data Discover more about data 2023]</strong> |
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Announcements Announcements]</strong>
</small></p>
</small></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>
[https://www.csps-efpc.gc.ca/digital-academy/index-eng.aspx Digital Academy]
<h3 style="text-decoration:none;">[https://www.csps-efpc.gc.ca/digital-academy/index-eng.aspx Digital Academy]</h3>
<p>The CSPS Digital Academy was established by the Canada School of Public Service (CSPS) in 2018 to help federal public servants gain the knowledge, skills and mindsets they need in the digital age. It supports the principles of Canada's Beyond2020 initiative for an agile, inclusive and equipped workforce and advocates for a digital-first approach that aligns with Canada's Digital Standards. </p>
<p>The CSPS Digital Academy was established by the Canada School of Public Service (CSPS) in 2018 to help federal public servants gain the knowledge, skills and mindsets they need in the digital age. It supports the principles of Canada's Beyond2020 initiative for an agile, inclusive and equipped workforce and advocates for a digital-first approach that aligns with Canada's Digital Standards. </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>
<p>(In English) A re-cap of ODC’s Implementation Working Group meeting held last September 2021.</p>
<p>(In English) A re-cap of ODC’s Implementation Working Group meeting held last September 2021.</p>
<p class="recco">Recommended by the Office of the CIO of Canada, Treasury Board of Canada Secretariat, a GC Data Community partner</p>
<p class="recco">Recommended by the Office of the CIO of Canada, Treasury Board of Canada Secretariat, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www.turing.ac.uk/news/can-data-trusts-be-backbone-our-future-ai-ecosystem Can data trusts be the backbone of our future AI ecosystem?]</h3>
<p class="author">Dr Aida Mehonic, on The Alan Turing Institute</p>
<p>(In English) Here at The Alan Turing Institute, we’re interested in how data trusts could help to shape the future artificial intelligence (AI) ecosystem. At present, lots of well-intentioned initiatives to create machine learning algorithms fail because of the lack of training datasets, and this is true both in the private and the public sector. A data trust could enable safe and secure data sharing that would allow the UK to develop and deploy AI systems to benefit society and the economy.</p>
<p class="recco">Recommended by [https://wiki.gccollab.ca/Data_Conference_2022_Speakers#Chantal_Bernier Chantal Bernier], a Data Conference 2022 speaker</p>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science/network/data-visualizations Creating Compelling Data Visualizations]</h3>
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/data-science/network/data-visualizations Creating Compelling Data Visualizations]</h3>
<p>The AI Accelerator is a new service from the NRC that helps Government of Canada departments and agencies harness the power of artificial intelligence (AI).</p>
<p>The AI Accelerator is a new service from the NRC that helps Government of Canada departments and agencies harness the power of artificial intelligence (AI).</p>
<p class="recco">Recommended by the National Research Council of Canada</p><p class="recco"></p>
<p class="recco">Recommended by the National Research Council of Canada</p><p class="recco"></p>
<h3 style="text-decoration:none;">[https://busrides-trajetsenbus.csps-efpc.gc.ca/ Busrides]</h3>
<p>Busrides is a product of the Canada School of Public Service Digital Academy, and a destination created to deepen your understanding of everything digital and government.</p>
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
<h3 style="text-decoration:none;">[https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?DGUID=2021A000011124 Census of Population]</h3>
<h3 style="text-decoration:none;">[https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?DGUID=2021A000011124 Census of Population]</h3>
<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>
<br>
<br>
[[Image:Number-Sense-cover.jpg|150px|Numbersense: How to Use Big Data to Your Advantage, by Kaiser Fung]]
[[Image:Number-Sense-cover.jpg|150px|Numbersense: How to Use Big Data to Your Advantage, by Kaiser Fung]]
<p>(In Engish) We live in a world of Big Data — and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it — whether we realize it or not. The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations. <i>Numbersense</i> gives you the insight into how Big Data interpretation works — and how it too often doesn't work. You won't come away with the skills of a professional statistician, but you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.</p>
<p>(In Engish) We live in a world of Big Data — and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it — whether we realize it or not. The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations. <i>Numbersense</i> gives you the insight into how Big Data interpretation works — and how it too often doesn't work. You won't come away with the skills of a professional statistician, but you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.</p>
<p class="recco">Recommended by the Office of the CIO of Canada, Treasury Board of Canada Secretariat, a GC Data Community partner</p>
<p class="recco">Recommended by the Office of the CIO of Canada, Treasury Board of Canada Secretariat, a GC Data Community partner</p>
<br>
<br>
<br>
<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>
<br>
<br>
<br>
<br>
<br>
<p>(In French - original title: <strong>Analyse des données textuelles</strong>) Textual data analysis (TDA) makes it possible to explore and visualize a wide range of text collections: literary works, interview transcripts, political speeches, press files, archival documents, online surveys with open-ended questions, complaint files, and satisfaction surveys. This book provides a rigorous presentation of TDA methods, which combine exploratory statistics, visualizations, quantitative validation procedures, and qualitative approaches.</p>
<p>(In French - original title: <strong>Analyse des données textuelles</strong>) Textual data analysis (TDA) makes it possible to explore and visualize a wide range of text collections: literary works, interview transcripts, political speeches, press files, archival documents, online surveys with open-ended questions, complaint files, and satisfaction surveys. This book provides a rigorous presentation of TDA methods, which combine exploratory statistics, visualizations, quantitative validation procedures, and qualitative approaches.</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>
<br>
<br>
<br>
<br>
<br>
<p>(In English) Quantitative bioimaging is a broad interdisciplinary field that exploits tools from biology, chemistry, optics, and statistical data analysis for the design and implementation of investigations of biological processes. Instead of adopting the traditional approach of focusing on just one of the component disciplines, this textbook provides a unique introduction to quantitative bioimaging that presents all of the disciplines in an integrated manner. The wide range of topics covered include basic concepts in molecular and cellular biology, relevant aspects of antibody technology, instrumentation and experimental design in fluorescence microscopy, introductory geometrical optics and diffraction theory, and parameter estimation and information theory for the analysis of stochastic data.</p>
<p>(In English) Quantitative bioimaging is a broad interdisciplinary field that exploits tools from biology, chemistry, optics, and statistical data analysis for the design and implementation of investigations of biological processes. Instead of adopting the traditional approach of focusing on just one of the component disciplines, this textbook provides a unique introduction to quantitative bioimaging that presents all of the disciplines in an integrated manner. The wide range of topics covered include basic concepts in molecular and cellular biology, relevant aspects of antibody technology, instrumentation and experimental design in fluorescence microscopy, introductory geometrical optics and diffraction theory, and parameter estimation and information theory for the analysis of stochastic data.</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>
<br>
<br>
<br>
