Changes

<b>Data Collection</b>

<b>Data Collection</b>

* Ensure data is collected <I><u> responsibly and </I></u>in a manner that maximizes use, <I><u>reuse</I></u> and availability of data

* Ensure data is collected <I><u> responsibly and </I></u>in a manner that maximizes use, <I><u>reuse</I></u> and availability of data

* Align to existing enterprise and international standards, <I><u> or where none exist, develop standards in the open with key subject matter experts <I><u>and consultation with Enterprise Data Community of Practice</u></I>

* Align to existing enterprise and international standards, <I><u> or where none exist, develop standards in the open with key subject matter experts </I></u>and consultation with Enterprise Data Community of Practice</u></I>

* <I><u>When collecting personal data or information, ensure that your practices are responsible and align with enterprise data ethics standards as well as relevant policy and legislation. The Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices. The government is moving toward defaulting to gender, sex by exception, and adding a third gender option in a respectful and inclusive manner. This involves making changes in the front end (collection) and the back end (coding, display). For collecting information, the recommended approach is to offer the options “male”, “female” or the third option of “another gender”. If there is a need for more specificity and the capacity for analysis, add a write in option labelled “Please Specify” </I></u>

* <I><u>When collecting personal data or information, ensure that your practices are responsible and align with enterprise data ethics standards as well as relevant policy and legislation. The Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices is an example of relevant policy that can inform considerations of gender diversity and inclusion. </I></u>

* <I><u>Ensure data is collected only if it cannot be obtained through data-sharing</I></u>

* <I><u>Ensure data is collected only if it cannot be obtained through data-sharing</I></u>

* Data should only be purchased once and should align with international standards

* Ensure that data collection <I><u>methodology</I></u> yields high quality data <I><u>in alignment with enterprise data standards</I></u>

* <I><u>Data purchased or obtained through data-sharing should be sourced to encouraged use by others</I></u>

* <I><u>Engage with key stakeholders within the federal government, as well as provincial, territorial and </I></u> other levels of government, including indigenous people

* Where necessary, ensure collaboration with department/agency data stewards/custodians, other levels <u><i>and jurisdiction</i></u> of government and indigenous people

* <I><u>Adopt a needs-based approach to data collection and review existing data assets prior to collecting or acquiring new data</i></u>

* Reduce the collection of redundant data

* <I><u>Ensure access and quality provisions are in place for data collected or acquired through third-party contracting services</I></u>

* <I><u>Ensure provisions are in place for Data access when using third-party contracting services. '''(may revise section to Business Arch?)'''</u></I>

<b>Data Management</b>

<b>Ensure that Data is Managed Responsibly and in a manner that Maximize Use, Reuse and Availability of Data</b></I></u>

* Demonstrate alignment with enterprise and departmental data governance, <I><u>architecture</u></I>, strategies, <I><u>and reference models

* Align with enterprise and departmental policies and standards on data <I><u>architecture</u></I> and governance

* Where appropriate align data to existing common vocabulary

* <I><u>Enable discoverability, accessibility, resiliency and availability of the departmental data assets

* Ensure metadata is captured and defined to maximize discovery and availability </I></u>

* Asses, control and monitor data quality in alignment with enterprise data standards

* Ensure accountability for data roles and responsibilities

* Define and establish clear roles, responsibilities and accountabilities for data management

* Design to maximize data use and availability

* where possible, use automation to support the management of data

* Design data resiliency in accordance with GC policies and standards

* Identify and document the lineage of the departmental data assets

* Use Master Data Management to provide a single point of reference for appropriate stakeholders

* Regularly assess the value of the departmental data assets and undertake retention and disposition as per existing schedules

 

* Only handle data which is essential to your service. Do not store all data that you capture unless absolutely necessary</i></u>

* <i><u> Only handle data which is essential to your service. Do not store all data that you capture unless absolutely necessary</i></u>

* Ensure data is stored in a secure manner in accordance with <I><u>CSE approved cryptographic algorithms and protocols and legislation such as</I></u> the Privacy Act

* Ensure data is stored in a secure manner in accordance with <I><u>CSE approved cryptographic algorithms and protocols and legislation such as</I></u> the Privacy Act

* <I><u>Retain data for the minimum time necessary.</u></I> Follow existing retention and disposition schedules

* <I><u>Manage departmental data in a way that enables interoperability, not only within the department, but also at the enterprise level</u></I>  

* Ensure data is stored in a way to facilitate easy data discoverability, accessibility and interoperability

* Ensure that data is used in an Ethical and Secure manner

 

<u><b>Data Use</b>

* <I> Ensure that data is used in an Ethical and Secure manner

* Ensure that combined data does not risk identification or re-identification of sensitive or personal information

* Ensure that combined data does not risk identification or re-identification of sensitive or personal information

* Ensure the data is fit for the use it is employed for in accordance with data quality guidelines </I></u>

* Ensure the data is fit for the use it is employed for in accordance with data quality guidelines  

* inform decisions by the appropriate data and information</I></u>

<b>Data Sharing</b>

<b>Data Sharing</b>

* Data should be shared openly by default as per the Directive on Open Government <I><u>while taking into consideration existing laws and regulations related to the safeguarding of data, while permitting free and open access

* Data should be shared openly by default as per the Directive on Open Government

* If data cannot be shared, explicitly state the laws and/or regulations preventing its sharing </i></u>

* <I><u>If data cannot be shared, explicitly state the laws and/or regulations preventing its sharing  

* Ensure that any data you share adheres to existing <I><u>enterprise and international standards, including on quality or fitness for purpose</I></u>

* Encourage data sharing and collaboration

* Encourage data sharing and collaboration

* <I><u>Validate or transform all external input before processing</I></u>

* <I><u>Ensure that data received from external parties is profiled and validated prior to its use.

* Enable internal and external sharing of data and information as appropriate</I></u>

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