Data is a valuable resource that, when effectively managed and utilized, can transform how we work. Data governance positions data as a strategic asset by establishing clear roles, standards and processes for secure and shared use of data. This structured approach ensures that consistent policies and standards exist across various departments, faculties and units, enabling data for analysis, insights, innovation with AI.
In addition to delineating responsibilities for different types of data, data governance defines the standards and guidelines and enables governed data through common definitions, traceability, context and building trust in data. Data Governance ensures that data is governed, readily accessible, is enabled for analytics and AI while managing risks related to compliance and privacy.
Leadership and Operating Model
Data Governance is one of the aspects of strategic vision for Queen's data. Queen's University has established the role of Director- Data Strategy and Governance (DSG) to oversee the strategic use of data and lead university-wide data governance. The DSG Director serves a critical enterprise data governance role that includes development of data roles and accountabilities, stewardship structure, oversight structure, standards and policies to enable use of data for analytics and AI.
The DSG Director role reports to Chief Information Officer and Associate Vice-Principal (Information Technology Services) and works under the direction of the Data Governance Council (DGC). The DGC is chaired by the Provost and Vice-Principal (Academic) and consists of members of the university's Senior Leadership Team including Vice-Principals, Vice Provosts, Deans and representatives from key departments. The DGC operates through its sub-committees and a Data Trusteeship Committee (DTC). For more details about leadership and the accountability model, refer to Council and Committees.
Under the direction of the Data Governance Council, the Data Strategy and Governance (DSG) Director has established data governance framework and operationalized various aspects of the framework through developing data roles and accountability, establishing and managing data governance councils and committees, data access, usage and sharing standards and development of a university wide data glossary.
For questions about data strategy and governance at Queen's University, contact Data Strategy and Governance Director.
Vision
Data is governed and managed as an asset and used to provide insights in support of the university’s business capabilities and strategic goals.
Mission
To develop university-wide data accountability, leadership structure, standards and processes to improve data collaboration, quality, literacy and shared utilization, while ensuring data security, compliance and privacy.
Framework
The data governance framework defines leadership, accountability and responsibility related to data use, sharing and handling. It is supported by an operating model and relevant policies and procedures, all of which help build and foster a culture of data excellence where the right users get access to the right data at the right time through well-defined processes.
It sets the direction for security, accountability, and trustworthiness of data and provides a framework to support the goal of high quality and optimized use of data.
Data Accountability and Oversight: Through establishing clear data roles including stewardship, leadership, and decision-making structures.
Leverage value of data and break down silos: Through common policies, standards and processes for data access sharing and usage.
Enable discoverability: Through glossary of data terms, metadata, and making data visible and searchable.
Ensure compliance: Minimize legal and reputational risks through security, privacy, and data lifecycle management policies.
Establish trust: Through processes and standards for data quality that promote trust in data accuracy, completeness, and data consistency.
Data Governance
| Data Stewardship | Data Policies and Standards | Data Use, Security, and Compliance | Data Quality |
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