Changes

=== Data security ===

=== Data security ===

:The definition, planning, development, and execution of security policies and procedures used to provide proper authentication, authorization, access, and auditing of data and information assets. Data security enables the protection of privacy, confidentiality, and integrity, as well as the maintenance of trust and social license to operate.<ref name=":2" /><ref name=":3" /><ref name=":4" /><ref>Economic Commission for Europe of the United Nations (UNECE). (2000). Terminology on Statistical Metadata in ''Conference of European Statisticians Statistical Standards and Studies''. (53), Geneva. </ref>

:The definition, planning, development, and execution of security policies and procedures used to provide proper authentication, authorization, access, and auditing of data and information assets. Data security enables the protection of privacy, confidentiality, and integrity, as well as the maintenance of trust and social license to operate.<ref name=":2" /><ref name=":3" /><ref name=":4" /><ref>Economic Commission for Europe of the United Nations (UNECE). (2000). Terminology on Statistical Metadata in ''Conference of European Statisticians Statistical Standards and Studies''. (53), Geneva. https://digitallibrary.un.org/record/442455</ref>

 

=== Data standards ===

=== Data standards ===

:Data standards are the rules and specifications by which data are described, defined and recorded. In order to share, exchange, and understand data, standardized formats and meanings are needed. Examples of data standards include data models, reference data, identifier schemas, and statistical standards. The use of data standards enables the integration of data over time and across different data sources, as well as reduces the resource requirements associated with many aspects of survey development and maintenance. <ref name=":2" /><ref name=":1" /><ref>International Organization for Standardization. (2016) Data quality — Part 61: Data quality management: Process reference model (ISO standard no. 8000-61:2016) https://www.iso.org/obp/ui/#iso:std:iso:8000:-61:ed-1:v1:en

:Data standards are the rules and specifications by which data are described, defined and recorded. In order to share, exchange, and understand data, standardized formats and meanings are needed. Examples of data standards include data models, reference data, identifier schemas, and statistical standards. The use of data standards enables the integration of data over time and across different data sources, as well as reduces the resource requirements associated with many aspects of survey development and maintenance. <ref name=":2" /><ref name=":1" /><ref>International Organization for Standardization. (2016) Data quality — Part 61: Data quality management: Process reference model (ISO standard no. 8000-61:2016) https://www.iso.org/obp/ui/#iso:std:iso:8000:-61:ed-1:v1:en