Changes

The following definitions are intended to support a common understanding of key terminology when reading the 2023-2026 Data Strategy for the Federal Public Service. They are intended to be a source of collaboration and knowledge sharing and are not official policy definitions.

The following definitions are intended to support a common understanding of key terminology when reading the 2023-2026 Data Strategy for the Federal Public Service. They are intended to be a source of collaboration and knowledge sharing and are not official policy definitions.

; Data flow : The circulation or movement of computerised data and information through interoperable systems and across organisations, geopolitical regions or jurisdictions.<ref>Organisation for Economic Co-operation and Development (1985). ''Declaration on Transborder Data Flows''. OECD: Better Policies for Better Lives. https://www.oecd.org/sti/ieconomy/declarationontransborderdataflows.htm</ref>

; Data flow : The circulation or movement of computerised data and information through interoperable systems and across organisations, geopolitical regions or jurisdictions.<ref>Organisation for Economic Co-operation and Development (1985). ''Declaration on Transborder Data Flows''. OECD: Better Policies for Better Lives. https://www.oecd.org/sti/ieconomy/declarationontransborderdataflows.htm</ref>

Data portability: The capacity of digital data and information to be transmitted or circulated through interoperable applications or systems and across organisations 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, p. 45.</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>

; Data portability : The capacity of digital data and information to be transmitted or circulated through interoperable applications or systems and across organisations 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, p. 45.</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>

 

; Data governance : A system of decision rights and accountabilities, responsibilities and rules for the management of the availability, usability, integrity and security of the data and information to enable coherent implementation and co-ordination of data stewardship activities as well as increase the capacity (technical or otherwise) to better control the data value chain, and the resulting regulations, policies and frameworks that provide enforcement. This includes the systems within an enterprise, organization or government that define who has authority and control over data assets and how those data assets may be used, as well as the people, processes, tools and technologies required to manage and protect data assets .<ref>Data Governance Institute. (n.d.). ''Governance and Decision Making''. Data Governance Institute. https://datagovernance.com/governance-and-decision-making/  </ref><ref name=":2">Organization for Economic Co-operation and Development (2008). ''OECD Glossary of Statistical Terms'', OECD Publishing, Paris. https://doi.org/10.1787/9789264055087-en.</ref><ref>Organisation for Economic Co-operation and Development (2019). Data Governance in the Public Sector ''In'' ''The Path to Becoming a Data-Driven Public Sector'', OECD Digital Government Studies, OECD Publishing, Paris. https://doi.org/10.1787/059814a7-en.  </ref><ref name=":5">Plotkin, D. (2021). Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance (2^nd Ed.). London, UK: Academic Press.</ref><ref name=":0">Statistics Canada. (2020b). Sta''tistics Canada Data Strategy: Delivering insight through data for a better''  ''Canada'' [PDF]. [https://www.statcan.gc.ca/eng/about/datastrategy/statistics_&#x20;canada_data_strategy.pdf Statistics Canada Data Strategy (statcan.gc.ca)]</ref><ref name=":1">Statistics Canada. (2021b). ''Enterprise Information and Data Management Glossary'' [PDF]. Unpublished internal departmental document.  </ref>

Data governance: A system of decision rights and accountabilities, responsibilities and rules for the management of the availability, usability, integrity and security of the data and information to enable coherent implementation and co-ordination of data stewardship activities as well as increase the capacity (technical or otherwise) to better control the data value chain, and the resulting regulations, policies and frameworks that provide enforcement. This includes the systems within an enterprise, organization or government that define who has authority and control over data assets and how those data assets may be used, as well as the people, processes, tools and technologies required to manage and protect data assets .<ref>Data Governance Institute. (n.d.). ''Governance and Decision Making''. Data Governance Institute. https://datagovernance.com/governance-and-decision-making/  </ref><ref name=":2">Organization for Economic Co-operation and Development (2008). ''OECD Glossary of Statistical Terms'', OECD Publishing, Paris. https://doi.org/10.1787/9789264055087-en.</ref><ref>Organisation for Economic Co-operation and Development (2019). Data Governance in the Public Sector ''In'' ''The Path to Becoming a Data-Driven Public Sector'', OECD Digital Government Studies, OECD Publishing, Paris. https://doi.org/10.1787/059814a7-en.  </ref><ref name=":5">Plotkin, D. (2021). Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance (2^nd Ed.). London, UK: Academic Press.</ref><ref name=":0">Statistics Canada. (2020b). Sta''tistics Canada Data Strategy: Delivering insight through data for a better''  ''Canada'' [PDF]. [https://www.statcan.gc.ca/eng/about/datastrategy/statistics_&#x20;canada_data_strategy.pdf Statistics Canada Data Strategy (statcan.gc.ca)]</ref><ref name=":1">Statistics Canada. (2021b). ''Enterprise Information and Data Management Glossary'' [PDF]. Unpublished internal departmental document.  </ref>

; 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=":0" /><ref name=":1" /><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 name=":6">Government of Canada, Treasury Board Secretariat. (2019). ''Policy on Service and Digital''. Ottawa, ON: Her Majesty the Queen in Right of Canada. https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32603</ref><ref>Statistics Canada. (2020a). ''Data Literacy Competencies''. Statistics Canada. https://www.statcan.gc.ca/en/wtc/data-literacy/compentencies </ref>

 

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=":0" /><ref name=":1" /><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 name=":6">Government of Canada, Treasury Board Secretariat. (2019). ''Policy on Service and Digital''. Ottawa, ON: Her Majesty the Queen in Right of Canada. https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32603</ref><ref>Statistics Canada. (2020a). ''Data Literacy Competencies''. Statistics Canada. https://www.statcan.gc.ca/en/wtc/data-literacy/compentencies </ref>

Data quality: The ‘quality’ of data refers to its fitness for purpose, often measured by such criteria offered in the sub bullet below. Data quality assurance measures are used to assess and improve the quality of data. Quality assurance measures planning, implementation, and control of activities that apply quality management techniques to data (whether statistical, administrative, or otherwise) and the statistical production process, to assure data is fit for purpose, which means that it is both usable and relevant in a primary or other use-context, and meets the needs of data users. Different users may have different needs that must be balanced.

Data quality: The ‘quality’ of data refers to its fitness for purpose, often measured by such criteria offered in the sub bullet below. Data quality assurance measures are used to assess and improve the quality of data. Quality assurance measures planning, implementation, and control of activities that apply quality management techniques to data (whether statistical, administrative, or otherwise) and the statistical production process, to assure data is fit for purpose, which means that it is both usable and relevant in a primary or other use-context, and meets the needs of data users. Different users may have different needs that must be balanced.