Changes

=== Aggregated data ===

=== Aggregated data ===

<blockquote>Unit level data that has been combined and summarized, often from multiple sources, into a collective form, often for the purposes of statistical analysis. Aggregate data allows for greater analysis and insight about particular groups based on specific variables, such as age or gender.<ref name=":9">National Collaborating Centre for Indigenous Health (2010). The Importance of Disaggregated Data. https://www.nccih.ca/docs/context/FS-ImportanceDisaggregatedData-EN.pdf </ref><ref>Strategic Data and Metadata eXchange (2020). SDMX Glossary Version 2.1. https://sdmx.org/wp-content/uploads/SDMX_Glossary_version_2_1-Final-2.docx  </ref></blockquote>

:Unit level data that has been combined and summarized, often from multiple sources, into a collective form, often for the purposes of statistical analysis. Aggregate data allows for greater analysis and insight about particular groups based on specific variables, such as age or gender.<ref name=":9">National Collaborating Centre for Indigenous Health (2010). The Importance of Disaggregated Data. https://www.nccih.ca/docs/context/FS-ImportanceDisaggregatedData-EN.pdf </ref><ref>Strategic Data and Metadata eXchange (2020). SDMX Glossary Version 2.1. https://sdmx.org/wp-content/uploads/SDMX_Glossary_version_2_1-Final-2.docx  </ref></blockquote>

=== Disaggregated data ===

=== Disaggregated data ===

<blockquote>Compiled or aggregate data that has been separated or broken down into smaller information units for the purposes of analysis. Disaggregated data allows for detailed analysis and insight about various subsets or outcomes within a larger data set. Data can be disaggregated by variables such as income or socio-cultural background.<ref name=":9" /></blockquote>

:Compiled or aggregate data that has been separated or broken down into smaller information units for the purposes of analysis. Disaggregated data allows for detailed analysis and insight about various subsets or outcomes within a larger data set. Data can be disaggregated by variables such as income or socio-cultural background.<ref name=":9" /></blockquote>

=== Data flow ===

=== Data flow ===

=== Data management ===

=== Data management ===

:A discipline that directs and supports effective and efficient management of information and data in an organization or public administration, from planning and systems development to disposal or long-term preservation. Data management involves the development, execution, and supervision of plans, policies, practices, concepts, programs, and the accompanying range of systems that contribute to the organizational or governmental mandates and to public good, as well as the maintenance of data processes to meet ongoing information lifecycle needs. It enables the delivery, control, protection, and enhancement of the value of data and information assets through integrated, user-based approaches. Key components of data lifecycle management include a searchable data inventory, reference and master data management, and a quality assessment framework.<ref name=":6" /><ref name=":10" /><ref name=":4" /><ref name=":3">Data Management Association (DAMA) (2017). DAMA-DMBOK: Data Management Body of Knowledge (2^nd Ed.). Basking Ridge, NJ: Technics Publications.</ref><ref>Statistics Canada (2020). ''Data Literacy Competencies''. Statistics Canada. https://www.statcan.gc.ca/en/wtc/data-literacy/compentencies </ref>

:A discipline that directs and supports effective and efficient management of information and data in an organization or public administration, from planning and systems development to disposal or long-term preservation. Data management involves the development, execution, and supervision of plans, policies, practices, concepts, programs, and the accompanying range of systems that contribute to the organizational or governmental mandates and to public good, as well as the maintenance of data processes to meet ongoing information lifecycle needs. It enables the delivery, control, protection, and enhancement of the value of data and information assets through integrated, user-based approaches. Key components of data lifecycle management include a searchable data inventory, reference and master data management, and a quality assessment framework.<ref name=":6" /><ref name=":10" /><ref name=":4" /><ref name=":3">Data Management Association (DAMA) (2017). DAMA-DMBOK: Data Management Body of Knowledge (2^nd Ed.). Basking Ridge, NJ: Technics Publications.</ref><ref>Statistics Canada (2020). ''Data Literacy Competencies''. Statistics Canada. https://www.statcan.gc.ca/en/wtc/data-literacy/compentencies </ref>

=== Data portability ===

=== Data portability ===

<blockquote>The capacity of digital data and information to be transmitted or circulated through interoperable applications or systems and across organizations or geopolitical regions. Data portability enables data subjects to have clear and manageable access to their personal data, which they have provided to a controller in a structured, commonly used, machine-readable and interoperable format, and are free to transfer it to another controller without undue burden.<ref>Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [2016] Official Journal of the European Union, Legislation Series 119. https://eur-lex.europa.eu/eli/reg/2016/679/oj</ref><ref>Government of Canada, Innovation, Science and Economic Development Canada (2019). ''Canada’s Digital Charter in Action: A Plan by Canadians, for Canadians.'' Ottawa, ON: Her Majesty the Queen in Right of Canada. https://ised-isde.canada.ca/site/innovation-better-canada/en/canadas-digital-charter/canadas-digital-and-data-strategy</ref></blockquote>

:The capacity of digital data and information to be transmitted or circulated through interoperable applications or systems and across organizations or geopolitical regions. Data portability enables data subjects to have clear and manageable access to their personal data, which they have provided to a controller in a structured, commonly used, machine-readable and interoperable format, and are free to transfer it to another controller without undue burden.<ref>Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [2016] Official Journal of the European Union, Legislation Series 119. https://eur-lex.europa.eu/eli/reg/2016/679/oj</ref><ref>Government of Canada, Innovation, Science and Economic Development Canada (2019). ''Canada’s Digital Charter in Action: A Plan by Canadians, for Canadians.'' Ottawa, ON: Her Majesty the Queen in Right of Canada. https://ised-isde.canada.ca/site/innovation-better-canada/en/canadas-digital-charter/canadas-digital-and-data-strategy</ref></blockquote>

=== Data quality ===

=== Data quality ===