Data Governance

William & Mary manages institutional data as a shared university asset. Data governance helps create trusted definitions, clear accountability, appropriate access, data quality, responsible use, and confidence in the information used to operate and advance the university. 

Governance is not just a committee activity. It is part of how W&M makes decisions, manages information, improves data quality, supports trusted analytics, and uses institutional data responsibly. 

Governance Approach 

W&M uses a practical, federated stewardship model. Data responsibilities are shared across functional, operational, analytic, and technology areas, with coordination through university governance practices. 

• Shared Meaning helps ensure that institutional information is interpreted and used consistently across systems, reports, analytics, integrations, and AI-enabled capabilities. 
• Data Quality means data is accurate, complete, consistent, timely, reliable, reasonable, and fit for intended use. 
• Trusted Analytics and Reporting depend on trusted definitions, governed Data Facts, aligned business rules, trusted sources, stewardship coordination, and appropriate use. 
• Responsible Use: W&M expects institutional data to be used legally, ethically, securely, and appropriately. 

• AI Readiness: Responsible use of AI-enabled capabilities depends on trusted institutional meaning, aligned definitions, governed Data Facts, reusable data assets, stewardship, and appropriate oversight. 

Why Governance Matters - it helps W&M:

• Make informed decisions 
• Use consistent definitions 
• Improve trust in reports and dashboards 
• Clarify business rules 
• Improve data quality 
• Protect sensitive and regulated information 
• Support compliance and accountability 
• Support trusted analytics 
• Prepare responsibly for AI-enabled capabilities