Data Governance

William & Mary manages institutional data as a critical university resource entrusted to our care.

Data governance provides the shared responsibilities, standards, and practices that help W&M define, protect, manage, share, and use institutional data responsibly.

It helps ensure that data can be trusted and appropriately used to support university operations, reporting, analytics, planning, decision-making, and emerging uses of technology. W&M’s governance framework applies to institutional data across academic, administrative, operational, reporting, and analytic activities.

Our Approach

W&M’s approach to data governance establishes clear responsibility for how institutional data is defined, managed, protected, and used.

It brings together university leadership, functional experts, technology professionals, data professionals, and the people who create and use data every day.

Governance Helps W&M:

Establish clear responsibility for institutional data
Create shared definitions and business rules
Identify trusted sources
Improve and maintain data quality
Manage access and appropriate use
Support consistent reporting and analytics
Provide clear paths for resolving definition, quality, access, and cross-functional data issues
Prepare trusted data for advanced analytics and responsible uses of AI

W&M Data Principles

W&M’s approach to institutional data is guided by these principles:

Data is a sustainable W&M asset.
Data quality and informed usage are shared responsibilities across W&M faculty, staff, and students.
Data is secure and used in legal, ethical, and responsible ways; privacy is respected.
Data is defined collaboratively through stewardship and trusted institutional understanding.
Data is timely, accessible, and appropriately available for approved use.
Data flow, movement, and usage are actively managed and communicated.
Data literacy, curiosity, and learning are institutional responsibilities supported across the university.
Data is understood and used within the appropriate operational and business context.
Decisions are made using trusted, high-quality institutional information.
Trusted Analytics and Reporting depends on aligned definitions, governed business rules, and trusted data meaning.
Data analytics, automation, and AI-enabled capabilities are used responsibly, transparently, and ethically in support of W&M’s mission and decision-making.
Governance and stewardship support shared understanding, collaboration, operational alignment, and trusted institutional decision-making across William & Mary.

Collapsible table with one column

Shared Responsibility for Data

Everyone who creates, manages, accesses, analyzes, or uses university data has a role in maintaining its trust and appropriate use.

University Leadership - Provides institutional direction, establishes accountability, and supports responsible management of university data.
Data Trustees and Data Stewards - Provide business leadership for data in their areas, including meaning, rules, quality, access, and appropriate use.
Technology and Data Professionals - Build and support the systems, platforms, integrations, security, and data capabilities needed to manage and use information effectively.
Faculty and Staff - Use institutional data appropriately, understand the information they use, protect sensitive data, and raise questions or concerns when something appears incorrect or unclear.
Students - Help protect university information and use data responsibly when accessing university systems, information, and resources.

From University Activity to Trusted Data

Trusted data starts with understanding the university activities that create and use it.

W&M’s Activity Model provides a shared view of what the university does, how key work flows, and what supports that work.

Data Activity Model

These activities create and use institutional data. Data governance provides the shared meaning, stewardship, quality, trusted sources, access, and responsible-use practices needed to turn that data into trusted information.

Protecting and Using Data Responsibly

Managing university data responsibly means considering how information is accessed, protected, shared, retained, and used throughout its lifecycle.

W&M uses governance, security, privacy, access controls, stewardship, and university policies and standards to help ensure institutional data is available to people who need it while being appropriately protected.

Access to institutional data is based on factors such as role, business or academic need, authorization, data sensitivity, and responsible use.

W&M works to use only the information needed for the intended purpose and to support responsible use of data in reporting, analytics, automation, and AI. This includes coordinating priority legal, regulatory, privacy, security, and reporting requirements so responsibilities and obligations are understood and monitored over time.

Data Quality and Trust

Trusted decisions depend on trusted information.

W&M works to identify and address data that may be incomplete, inaccurate, inconsistent, outdated, duplicated, or unclear.

Data quality is a shared responsibility involving the functional areas that understand the information, the technology and data teams that manage it, and the people who use it.

For institutional reporting and analytics, W&M also works to establish consistent definitions, business rules, timing, and trusted sources so information can be understood and used appropriately.

Governance Across W&M

Data governance is coordinated across the university through the Data Governance Advisory Council and supporting teams and working groups.

The Data Governance Advisory Committee (DGAC) provides university-wide guidance and oversight for institutional data governance and helps align governance priorities with university strategy, operational priorities, reporting obligations, analytics needs, and institutional risk.

Data Governance Advisory Committee Members
First	Last	Function
Alana	Davis	University Registrar (Co-chair)
Barbara	Forth	Chief Data Officer (Co-chair)
Bruce	Aird	University Advancement
Alyson	Wilson	Research
Anne	Roemer	Human Resources
Galloway	Sean	Finance
Ben	Boone	School of A&S
Iria	Giuffrida	Provost
Laura	Morales	Library

Supporting teams help put governance into practice across university activities:

Data Governance Team (DGT) - brings together Data Stewards, functional experts, technology professionals, and others to help resolve cross-cutting data questions and support consistent governance practices.
Data & Analytics Team (D&AT) - brings together analytics and functional leaders to support reporting and analytics alignment, shared practices and platform, data use, and collaboration across W&M.

Governance in Practice

W&M is continuing to mature its data governance and data management capabilities through a coordinated W&M Data Program beginning January 2027.

The program is focused on strengthening shared definitions, stewardship, data quality, trusted sources, access, regulatory reporting, records retention, reporting and analytics, and related data management practices across the university.

This work is being implemented over time and reflects an ongoing leadership focus on making institutional data more trusted, usable, and responsibly managed.

Progress will be demonstrated through defined responsibilities, operating practices, and evidence that priority capabilities are working as intended.

Shared Meaning - Common definitions and business rules help people understand information consistently.
Data Stewardship - People closest to university activities help establish meaning, rules, quality, and appropriate use.
Data Quality - Issues are identified, evaluated, and addressed so data remains fit for its intended purpose.
Trusted Sources - Important institutional information is connected to authoritative or trusted sources.
Responsible Access & Use - Data access and use reflect business need, authorization, sensitivity, privacy, and security requirements.
Data Impact & Change - Important data impacts are considered when changes cross systems, programs, or university activities.
Trusted Analytics & AI - Governed data provides a stronger foundation for reporting, analytics, automation, and responsible AI.