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GC Enterprise Architecture/Standards/Information Architecture (view source)
Revision as of 13:44, 6 March 2019
, 13:44, 6 March 2019Created page with "<!-- NAV --> {| class="FCK__ShowTableBorders" style="border-right: 0px; border-top: 0px; border-left: 0px; border-bottom: 0px; background-color: #3C6D9E" width="100%" align="c..."
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{{Translation to follow}}
This is a definition for GC Information Enterprise Architecture
<b>Data Collection</b>
* Ensure data is collected in a manner that maximizes use and availability of data
* Ensure data collected aligns to existing enterprise and international standards
* Where enterprise or international standards don't exist, develop Standards in the open with key subject matter experts
* Ensure collection of data yields high quality data as per data quality guidelines
* Ensure data is collected through ethical practices supporting appropriate citizen and business-centric use
* Data should only be purchased once and should align with international standards
* Where necessary, ensure collaboration with department/agency data stewards/custodians, other levels of government and indigenous people
<b>Data Management</b>
* Demonstrate alignment with enterprise and departmental data governance and strategies
* Ensure accountability for data roles and responsibilities
* Design to maximize data use and availability
* Design data resiliency in accordance with GC policies and standards
* Use Master Data Management to provide a single point of reference for appropriate stakeholders
<b>Data Storage</b>
* Ensure data is stored in a secure manner in accordance with the National Cyber Security Strategy and the Privacy Act
* Follow existing retention and disposition schedules
* Ensure data is stored in a way to facilitate easy data discoverability, accessibility and interoperability
<b>Data Sharing</b>
* Data should be shared openly by default as per the Directive on Open Government
* Ensure government-held data can be combined with data from other sources enabling interoperability and interpretability through for internal and external use
* Reduce the collection of redundant data
* Reduce existing data where possible
* Encourage data sharing and collaboration
{| class="FCK__ShowTableBorders" style="border-right: 0px; border-top: 0px; border-left: 0px; border-bottom: 0px; background-color: #3C6D9E" width="100%" align="center"
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| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="6%" | '''[[GC_Enterprise_Architecture|<span style="color: snow">'''Home'''</span>]]'''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="11%" | '''[[Government_of_Canada_Architectural_Standards|<span style="color: Snow">'''EA standards'''</span>]]'''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="13%" | '''[[Past_Endorsed_Architectural_Decisions|<span style="color: Snow">'''EARB Endorsements'''</span>]] '''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="11%" | '''[[Enterprise_Architecture_Artifacts|<span style="color: Snow">'''EA Artifacts'''</span>]] '''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="12%" | '''[[Architecture_Discussions|<span style="color: Snow">'''Working Groups'''</span>]] '''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="11%" | '''[[GC EARB|<span style="color: Snow">'''GC EARB'''</span>]] '''
| style="border-right: white 1px ridge; padding-right: 0px; padding-left: 0px; padding-bottom: 2px; padding-top: 2px; text-align: center; font-family: (Cooper black); font-size: 13pt" width="9%" | '''[[Monitoring_Architectural_Implementation|<span style="color: Snow">'''Other References'''</span>]] '''
|}
<!-- NAV end -->
{{Translation to follow}}
This is a definition for GC Information Enterprise Architecture
<b>Data Collection</b>
* Ensure data is collected in a manner that maximizes use and availability of data
* Ensure data collected aligns to existing enterprise and international standards
* Where enterprise or international standards don't exist, develop Standards in the open with key subject matter experts
* Ensure collection of data yields high quality data as per data quality guidelines
* Ensure data is collected through ethical practices supporting appropriate citizen and business-centric use
* Data should only be purchased once and should align with international standards
* Where necessary, ensure collaboration with department/agency data stewards/custodians, other levels of government and indigenous people
<b>Data Management</b>
* Demonstrate alignment with enterprise and departmental data governance and strategies
* Ensure accountability for data roles and responsibilities
* Design to maximize data use and availability
* Design data resiliency in accordance with GC policies and standards
* Use Master Data Management to provide a single point of reference for appropriate stakeholders
<b>Data Storage</b>
* Ensure data is stored in a secure manner in accordance with the National Cyber Security Strategy and the Privacy Act
* Follow existing retention and disposition schedules
* Ensure data is stored in a way to facilitate easy data discoverability, accessibility and interoperability
<b>Data Sharing</b>
* Data should be shared openly by default as per the Directive on Open Government
* Ensure government-held data can be combined with data from other sources enabling interoperability and interpretability through for internal and external use
* Reduce the collection of redundant data
* Reduce existing data where possible
* Encourage data sharing and collaboration