Data asset management aims to ensure high quality and trusted data. The purpose of this guidance is to outline the recommended data management functions of a data asset throughout its lifecycle. Those accountable for the data asset should determine if and how each of the data management functions will be supported.
Section 1: Administration
- Assigns and tracks data management roles and responsibilities (e.g. who is responsible for the storage of the data asset? Who is responsible for approving access to the data asset?)
Section 2: Data Collection
- Articulates the principal business objectives, purposes, and uses supported by the data asset
- Determines the method(s) of data collection (i.e. build on existing data collection tool vs. net new data collection tool) that will meet business, operational and/or analytical requirements
- Identifies and approves the data types and formats for the key data elements required to support the business objectives, purposes and uses
- Ensures that Notice(s) of Data Collection and Use are in place and kept current to support the business objectives, purposes and uses
- Ensures that consent processes are in place, if required
Section 3: Metadata & Documentation
- Ensures that documentation is in place to allow for effective use and understanding of the data. This may include:
- A description of the data asset and the supported business objectives
- A business glossary (functional definitions of key terms)
- A data dictionary (acceptable data formats)
- Documentation of the technical data lineage and architecture
- An inventory of analytics products supported by the data asset
- Determines which metadata management processes (such as a definition management process) are required and, if so, ensures that they are in place.
- Approves metadata and definitions as required.
Section 4: Data Quality Management
- Approves the data quality standards for key data elements
- Determines if a data quality process is required for key data elements and, if so, ensures that one is in place
- Determines if a quality management process is required to address gaps in data quality and, if so, ensures that one is in place
Section 5: Storage & Security
- Ensures that appropriate back up plans are in place depending on the criticality, business value, and availability needs of the data asset
- Classifies the data asset according to the data classification standard at the University
- Ensures that data protection protocols and technology (collection, storage, access) meet University standards based on the classification of the data asset
- Ensures that sensitive data fields are appropriately identified
- Sets data masking standards
Section 6: Disclosure & Access
- Understands and communicates the allowable uses for the collected data according to the Notice of Data Collection and Use, University policies and legal obligations
- Determines the type of role(s) that can access and use these data
- Determines allowable data linkages
- Determines the various formats in which data can be consumed
- Determines if a data literacy training program is required and, if so, ensures that it is in place
- Sets/approves the conditions of data use including:
- Appropriate and inappropriate data uses
- Data literacy training requirements for users
- Guidance on data downloads
- How results can be shared
- Sets/approves the data access approval process based on the confidentiality of the data and breadth of the user base. In accordance with University guidance, elements to consider include:
- The information and people required to approve access
- The frequency of data access renewal
- Methods by which users are properly trained on appropriate data use
- Processes that ensure that users are adhering to the conditions of data use
Section 7: Retention & Preservation
- Sets/approve guidelines on data retention, archiving and destruction, consistent with University guidance
- Ensures adherence to guidelines on data retention, archiving and destruction