In order to take advantage of big data and stay at the pinnacle of data science, U-M must update its data governance and stewardship model, which was created in 1994 and not substantially updated since. To do so, representatives from many university areas are working to identify and, where possible, quickly implement improvements to data governance processes.
This revitalization effort is jointly sponsored by the Provost and the VPIT-CIO.
We are approaching the revitalization effort in multiple stages.
Stage One: Create High-level Recommendations (Complete)
The high-level recommendations were published in 2019. They are:
Review and revise SPG 601.12 Institutional Data Resource Management Policy
Create a Data Governance Oversight Committee (DGOC) Structure
Provide dedicated resource support
Create mechanisms to provide systematic logging of all requests for access to data
Define and provide central services that can support and guide any data request
Reduce the number of, and better define the roles within, the data governance framework
Stage Two: Recommend Actionable Improvements (In Progress)
A Data Governance Council was established in April 2020 to work on Stage Two of data governance revitalization. The council has identified the following areas of focus for their work in 2020:
Data Availability and Sharing
Document existing and desired processes. Establish common guidelines for obtaining access to data. Wherever possible, automate data request processing.
Identify opportunities for improvement in how data quality issues are addressed. Work to improve consistency of data definitions. Publish data quality metrics.
Roles, Responsibilities, and Appointments
Simplify data stewardship structure. Create consistency in roles and alignment on responsibilities. Improve maintenance of Data Governance structure.
Data Catalog Implementation
U-M does not currently have a data catalog that covers data sets and their metadata across the university. Such a data catalog will be instrumental in successfully achieving several of the high-level objectives from Stage One. We are currently exploring a data catalog that is included in a tool ITS uses for Data Virtualization, from Denodo.
Please contact the Data Governance Council co-chairs with any questions you may have at email@example.com