Institutional data and analytics services will produce high quality and trusted data.

We will aim to:

• Manage and value our data as institutional assets
• Provide curated ‘analytics-ready’ institutional data sets for broad use by units
• Inform decision-making using the highest quality, fit-for-purpose data
• Provide metadata to ensure that data meaning is consistent across the institution

Institutional data will be shared appropriately and securely across the University and with our partners (includes researchers, vendors, government) to inform decision-making.

We will aim to:

• Ensure processes and criteria for accessing institutional data are transparent, consistent, and equitable
• Apply security controls to ensure people have appropriate access to the right data
• Ensure data are accessible to authorized users when and where required
• Implement auditing processes to monitor access to and uses of data

The University will adopt advances in data and analytics technologies and capabilities to meet its current and future needs.

We will aim to:

• Evaluate new and updated technologies in terms of their feasibility and scalability to support units’ data and analytics requirements
• Realize institutional efficiencies through collective acquisition and access to institution-wide tools (e.g., storage/integration, reporting, business intelligence, analytics)
• Align data and analytics technology requirements with the University’s broader IT strategy

The University will empower its data community with the tools and the means to enable them to actively contribute to the changes needed to realize effective data-informed decision-making.

We will aim to:

• Encourage and recognize data-informed decision-making for strategic and operational purposes
• Formally engage our data and analytics community to promote sharing of knowledge and establish common data and analytics solutions and standards
• Implement institutional learning and development opportunities to improve data literacy across the spectrum of data and analytics-related roles
• Design our data and analytics operating model such that staffing, and services are optimized to support divisional partners in achieving their goals through the better use of data

The University will foster the trust of all those who interact with institutional data.

We will aim to:

• Promote transparency in the collection, processing, and use of our institutional data
• Involve affected parties in the development of data policy and use initiatives
• Promote a culture of responsible use of data among all those who work with institutional data

Terms of Reference

1. Develop and champion the data strategy of the University.
2. Ensure data strategy initiatives are aligned with the University’s mission, objectives, and obligations.
3. Recommend policies and guidelines for Governing Council approval.
4. Appoint members of a Data Governance Council and approve terms of reference.
5. Appoint members of a Reporting and Analytics Council and approve terms of reference.
6. Provide oversight for the Data Governance Council and the Reporting and Analytics Council.
7. Ensure cross-alignment across the R&A and DG Councils to support the design and implementation of the institutional data strategy.
8. Develop plans for a “Roster of Expert Reviewers”, establish mandate and appoint members.

Members

Term

For academic divisional members, term length will be 2-3 years and staggered to maintain continuity

Frequency of Meetings

The IDS Steering Committee will meet three times per year.

Meeting Documents

For members of the IDS Steering Committee, meeting documents can be accessed here.

Terms of Reference

1. Promote the institutional data governance program goals to support the responsible use of high- quality institutional data.
2. Collaborate with the R&A Council to oversee IDS initiatives and monitor evaluation plans.
3. Engage with the Institutional Research and Data Governance (IRDG) office and working groups to gather requirements and/or recommendations for strategic initiatives.
4. Review and provide guidance around recommended data governance processes, frameworks, and guidelines.
5. Approve data domains and appoint data trustees.
6. Act as a mediation panel to resolve complex data governance issues.
7. Oversee standing committees and ad hoc working groups, as required.
8. Provide regular updates to the Institutional Data Strategy Steering Committee.

Members

Term

For academic divisional members, term length will be 2-3 years and staggered to maintain continuity.

Frequency of Meetings

The DG Council will meet 3 times per year.

Meeting Documents

For members of the DG Council, meeting documents can be accessed here.

Terms of Reference

1. Promote and champion the use of institutional data to advance the goals of the University.
2. Collaborate with the DG Council to oversee IDS initiatives and monitor evaluation plans.
3. Engage with the Institutional Research and Data Governance (IRDG) office and working groups to gather requirements and/or recommendations for strategic initiatives.
4. Review and provide guidance around recommended analytics processes, frameworks, and guidelines.
5. Approve priorities for institution-wide analytics projects (e.g., development of institutional data marts, dashboards, and advanced analytics solutions).
6. Oversee standing committees (e.g., Data Access Committee) and ad hoc working groups, as required.
7. Provide regular updates to the Institutional Data Strategy Steering Committee.

Members

Term

For administrative and academic representative members, term length will be 2-3 years and staggered to maintain continuity.

Frequency of Meetings

The Reporting & Analytics Council will meet 3 times per year.

Meeting Documents

For members of the Reporting & Analytics Council, meeting documents can be accessed here.