Data Standards Issue Documentation

November 2020 Proposal Forum

Resources

Data Standards Proposal

Presentation Slides 

Sample UMS Data Standards pages

Proposal Summary

Data quality issues are abundant and persistent across the UMS. This proposal puts forth a potential method for documenting—and making available—UMS data standards as they are created or as they currently exist in unpublished form.

Background

Across the UMS, MaineStreet—and other data systems—have been set up by many individuals across functional areas and over a period of time. Due to the distributed manner of implementation of these systems, we have significant variation in our usage of data elements and coding/definitions within those elements. In some cases, different codes may be used on different campuses in order to meet the specific needs of those institutions; in other cases, different coding values and/or definitions are simply the result of different individuals creating codes in various functional areas or at different institutions or points of time. 

Solution & Next Steps 

• Documentation:
  • Create a reference Data Standards index with comprehensive information regarding the expectations for that data (Example data elements: Classification of Instructional Programs and Instructor Workload). Potential information to include ranges from type and location of data to data quality specifications and data classification level.
• Stewardship:
  • Audit compliance with data standards at appropriate intervals and provide specific data needing revision for standards to be met.
• Leadership:
  • Set an expectation of compliance

Comments & Questions

• Documentation of standards is a good idea. A potential additional section for the Data Standards: could we include a place for indicating the individuals who need to be notified of changes? What is the means and type of communication that needs to go out with any such changes.
  • Adding communication needed to ensure stakeholders are aware of changes is a great potential addition. Next steps include discussing content of standards, as well as location and format to ensure maximum usefulness and ease-of-use.
• What is the process for adding standards? Is it only as a result of DG projects?
  • Ideally, we would add standards through both DG projects and other mechanisms. While we wouldn't want to create too many standards too quickly and overwhelm the functional areas with compliance requests, we do need data standards in order to move our data consistency and quality forward.
• Historical context and historical data values and meanings–will these be documented in the standards pages too?
  • That has not yet been considered, but is a great idea for consideration by a team that will implement and build out standards.
• Specific to the CIP standard, it is not always the case that CIPs are specified out to six-digits. For example, when coding faculty, four digits are used.
  • The publishing of standards and an expectation of compliance also opens the door for ensuring that the standards we put into place are the 'right' standards. This should be an ongoing conversation.
• Will standards be linked to Data Cookbook?
  • Interlinkages are important to keeping standards, definitions, locations, field values, etc. all fully documented and easily found regardless of entry point into documentation.
  • Data Cookbook is also a possible location for the standards themselves. If Data Cookbook is used for standards, then linkages will be different across Cookbook, Confluence, etc.
• Variations in definitions--full-time definition---is that for Data Cookbook, or is that standards?
  • Both….perhaps when it is a data field, it needs a standard? 
  • Otherwise, if definitions only, then Data Cookbook?
  • This is a great example of scoping data standards and the questions that will need to be answered in order to finalize and implement a high-quality set of standards.

Resources & Research

Related Links

• Data Standards definition   
• Data Standards proposal  

Strategic Goals Addressed

• Unified Accreditation: Standardization of coding across campuses
• EDUCAUSE 2021 Top 10 IT Issues: Technology Alignment - Identifying and applying sustainable digital strategies and innovations
• Declaration of Strategic Priorities to Address Critical State Needs: Aligning Academic Programs & Innovation to Drive Student Success & Employer Responsiveness

Audience

• System-Wide