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.

    • 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?)
    • Articulates the principal business objectives, purposes, and uses supported by the data assetDetermines 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
    • 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.
    • 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
    • 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
    • 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
    • Sets/approve guidelines on data retention, archiving and destruction, consistent with University guidance
    • Ensures adherence to guidelines on data retention, archiving and destruction