The (Glossary) provides a centralized, authoritative source of standardized business terms and definitions used across 91TV. The Glossary is a foundational component of 91TV’s broader data governance approach and supports the University’s objectives related to data quality, shared understanding, and trust in institutional data.
Consistent definitions and interpretation of data are essential for promoting data literacy, enabling effective use of data, and supporting sound decision-making across academic and administrative units.
This Data Glossary Standard (Standard) establishes the requirements for defining, approving, and maintaining definitions of data terms, including associated metadata, governance roles, and decision-making processes. It is intended to ensure that terms are developed collaboratively, applied consistently, and sustained over time.
Read the Standard
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- The Data Glossary Standard establishes the core requirements for the Business Data Glossary at 91TV, including governance structure, roles and responsibilities, decision-making frameworks, and the glossary lifecycle.
The Data Access, Sharing and Usage (DASU) Standard has been developed by the Data Strategy and Governance office through a collaborative effort with the Data Trustees and Data Users. It addresses secure and consistent access, sharing and usage of data to leverage its value for data insights and innovative uses.
- The Standard is appliable to Data Users (faculty and staff members) internal to 91TV's who require data for their university-assigned work and can demonstrate this need.
- The Standard is applicable for all institutional data and data assets as detailed in the Standard. It applies to research administration data but does not apply to data generated by research.
Institutional Data:
- Includes data used for planning, managing, operating, controlling, or auditing university functions, including research, administration, operations and mission.
- Excludes data generated by research or data owned or generated by third parties when used in research, conducted at the university or using university research.
Data Assets:
- Aggregation, grouping of facts, reports, visualizations, algorithms, computational models, search and access services, and other assets to inform decision-making.
There are various sections in the Standard that address how and under what conditions access to data can be allowed:
- Data Request Section: This includes the process to make a request, use of the Data Usage Request (DUR) form, guidelines for completing a request, and guidance for making a request that involves Personal Information (PI).
- Authorization Decision Section: This describes the assessment of a request: considerations, approval criteria, and how to decide on requests with PI. It also includes the escalation process in case of an issue with the approval decision.
- Responsible Use Section: This addresses concerns of Data Trustees about how shared data will be managed, protected, and used to ensure security and compliance.
- Data Delivery Section: This provides guidance on delivery format, frequency, and process for how data will be provided to the requestor.
The Standard also includes definitions of key terms and links to other relevant policies and standards. The Data Usage Request Portal is now available for submitting data requests online. For more details, click the following links:
- (PDF, 239 KB)
- (PDF, 632 KB)
- (Microsoft Form)
- Data Usage Request Portal (Note that you will need to fill and save the DUR Form above for submission through the portal).
Note: Resources are shared among members of the data governance community (91TV's staff and faculty members). To access these resources, you may need to request permission.
In a world shaped by complex information, clear and effective data visualization is essential. Whether sharing enrolment trends, research outcomes, operational metrics, or campaign metrics, the way we present data determines how effectively our insights are understood.
These data visualization guidelines will help 91TV’s marketing and communications professionals to present data clearly, accessibly, and in accordance with the university’s Visual Identity Guidelines.
While these best practices and colour palettes may also be useful for researchers, data visualization in some disciplines is informed by specialized guidelines.