wiki

Changes

Discover more about data (view source)

Revision as of 14:30, 21 February 2023

2,247 bytes added ,  14:30, 21 February 2023
no edit summary
Line 59: Line 59:  
[[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>&nbsp;&nbsp;|&nbsp;&nbsp;
+
<strong>[https://vexpodev.z9.web.core.windows.net/en/#/2203/lobby Virtual Expo]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
−
<strong>[https://expo.da-an.ca Virtual Expo]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
   
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda Agenda]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
 
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda Agenda]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
 
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Speakers Conference speakers]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
 
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Speakers Conference speakers]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
 
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Networking_Missions Networking Missions]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
 
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Networking_Missions Networking Missions]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
−
<strong>[https://wiki.gccollab.ca/Discover_more_about_data DISCOVER MORE ABOUT DATA]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
+
<strong>[https://wiki.gccollab.ca/GC_Data_Conference_2023/Discover_more_about_data Discover more about data 2023]</strong>&nbsp;&nbsp;|&nbsp;&nbsp;
−
<!--<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Announcements Announcements]</strong>-->
+
<strong>[https://wiki.gccollab.ca/Data_Conference_2022_Announcements Announcements]</strong>
 
</small></p>
 
</small></p>
   Line 82: Line 81:  
<p><strong>[https://www.csps-efpc.gc.ca/catalogue/courses-eng.aspx?code=I511 The Role of Data in Digital Government]</strong> (virtual classroom)</p>
 
<p><strong>[https://www.csps-efpc.gc.ca/catalogue/courses-eng.aspx?code=I511 The Role of Data in Digital Government]</strong> (virtual classroom)</p>
 
<p class="recco">Recommended by the Canada School of Public Service, a GC Data Community partner</p>
 
<p class="recco">Recommended by the Canada School of Public Service, a GC Data Community partner</p>
 +
 +
<h3 style="text-decoration:none;">[https://catalogue.csps-efpc.gc.ca/catalog?pagename=Catalog&cm_locale=en Canada School of Public Service Learning catalogue]</h3>
 +
<p>Browse the School's full catalogue of courses, events, programs and other learning tools. For recommended learning by theme or community, view our Learning paths.</p>
 +
<p class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
 +
 +
<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 class="recco">Recommended by Statistics Canada, a GC Data Community partner</p>
    
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/wtc/data-literacy Statistics Canada’s Data Literacy Training Initiative]</h3>
 
<h3 style="text-decoration:none;">[https://www.statcan.gc.ca/en/wtc/data-literacy Statistics Canada’s Data Literacy Training Initiative]</h3>
Line 104: Line 111:  
<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>
Line 166: Line 178:  
<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>
Line 457: Line 473:  
<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]]
Line 463: Line 480:  
<p>(In Engish) We live in a world of Big Data &#8212; and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it &#8212; 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 &#8212; 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 &#8212; and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it &#8212; 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 &#8212; 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>
   Line 491: Line 509:  
<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>   
   Line 518: Line 537:  
<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>
Line 561: Line 581:  
<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>
  
Retrieved from "https://wiki.gccollab.ca/Special:MobileDiff/66838...91544"