Defined Components
Five components, one operating framework.
Each component feeds a shared understanding of what data exists, what it means, where it lives, and how it should be used.
Accountability Model
Roles & Responsibilities
Roles and Responsibilities define the governance structure through which accountability, decision-making, and execution are distributed across the university's data governance program. It establishes who is responsible for what, from strategy to coordination to implementation and execution, ensuring that every governance activity has a clearly identified owner, executor, and escalation path. The structure follows a maturity-based approach, with the continuous refinement of roles built-in as the program scales and governance processes become embedded in daily operations.
Distributed Accountability
Assigns a clear owner, executor, and escalation path to every governance activity.
Strategy to Execution
Connects institutional leadership, coordination, and domain-level operational roles.
Discovery & Meaning
Data Catalog
The Data Catalog provides a centralized, searchable inventory of the university's data assets, including business glossary terms, data definitions, data classifications, and source-level metadata, enabling stakeholders to discover, understand, and trust the data available to them. It supports transparency and accountability by providing Data Stewards, Data Custodians, and Data Users with a shared understanding for what data exists, what it means, where it lives, and how it should be used.
Searchable Inventory
Assets, definitions, classifications, and source-level metadata in one place.
Business Glossary
Shared, plain-language definitions of institutional terms and critical elements.
Access Process
Data Access Lifecycle Management
Data Access Lifecycle Management defines the end-to-end process by which data access is requested, evaluated, provisioned, monitored, audited, and revoked across the university. It ensures that the right people have the right access to the fit for purpose data at the right time by aligning access decisions with university data policies, governance standards, and data classification levels—reinforcing both security and usability. This includes the ability to audit data access at any point in the lifecycle—providing a clear, traceable record of who has access, how it was granted, when it was last reviewed, and whether it remains appropriate—so that the university can demonstrate compliance and maintain accountability over its data assets.
Full Lifecycle
Covers request, evaluation, provisioning, monitoring, audit, and revocation.
Policy-Aligned
Every decision is tied to policy, standards, and data classification.
Trust & Remediation
Data Quality Framework
The Data Quality Framework focuses on establishing rules and thresholds to measure data quality, prioritizing critical and sensitive data, and enabling the remediation of data quality issues by both correcting the data and the processes used to capture data. The framework is supported by regular review and maintenance to keep data quality measures accurate and relevant and is designed to be part of the validation processes for operational development along with supporting existing data infrastructure.
Rules & Thresholds
Measures quality against defined standards, prioritizing critical and sensitive data.
Root-Cause Remediation
Corrects both the data and the processes that produced it, with regular review.
Enabling Technology
Governance Technology Framework
The Governance Technology Framework defines how the university identifies, evaluates, and leverages technology to enable effective data governance and position data as a strategic asset. It aligns technology capabilities to governance objectives while also extending governance to the technology that creates, stores, processes, and shares university data. The framework ensures that technology used—whether to perform governance activities or to support broader university operations—fits within the overall governance framework, adheres to established data policies and standards, and is evaluated for alignment with governance principles, data classification requirements, and strategic objectives before procurement or deployment.
Evaluate & Leverage
Identifies and adopts technology that enables and scales governance practice.
Govern the Systems
Extends governance to the systems that create, store, process, and share data.