Data Domains & Classifications

Definitions

Data Domains

A data domain is a specific category of data that share similar characteristics or represent a particular aspect of the overall information. In the context of data governance, a data domain can be thought of as a logical grouping or a subset of data that is defined by its content, structure, context, or usage.

Data Classifications

Categories of data based on content, sensetivity, purpose, or other characteristics. These classifications are generally defined by regulatory compliance, business purpose, or sensitivity of the data or dataset.


UW Data Domains

  • Financial

  • Human Resources

  • Student

  • Admissions


UW Data Classifications

 

Level 1: Public 

Definition:

Data meant for outside of UW (University of Wyoming) consumption. Must have at least one of the following applied to the data: De-identification, Anonymization, Aggregation, Suppression. 

Examples (not limited to):

Enrollment Counts, IPEDS Federal Reporting data, Degree Data. 

 

Level 2: General 

Definition:

Data meant for only internal UW (University of Wyoming) community members. Must have at least one of the following applied to the data: De-identification, Anonymization, Aggregation, Suppression. 

Examples (not limited to):

Aggregated class enrollment numbers, aggregated financial data, anonymized program enrollments. 

 

Level 3: Restricted 

Definition:

Data that could identify a specific person, but access is needed to conduct university business. Access restrictions are required; however, breadth of access is determined by the data stewards/managers with suggestions from IT and Data Governance. Specific training may be required to access some or all portions of this data. 

Examples (not limited to):

PRAXIS exam data, Payroll With Fringe data, Classroom usage, Student Data (FERPA (Federal Education Rights and Privacy Act)), Student Financial Data (GLBA (Gramm Leach Bliley Act)), HR (FCRPA), Medical Data (HIPAA).

 

Level 4: Critical 

Definition:

Data that is already governed by the Restricted level (3) but mishandling of the data could cause irreparable harm to employees, students, or the university. This level of data is rarely needed for day-to-day operations. 

Examples (not limited to):

SSN, Bank Account Information.