Frequently Asked Questions

What is Data Governance?

Data governance is the process through which consistent and clear guidance around defining, creating, managing, accessing, and using Western's institutional data are organized and facilitated.  Data governance is a process used to promote and support the responsible use of high-quality institutional data, to facilitate informed and insightful use of these data, and to increase their value to the Western community.

Data governance includes attention to relevant risks, responsibilities, and legal obligations that are important and/or required for the institution. Data governance includes the definition and specification of decision rights and an accountability framework to encourage empowered and responsible behaviour in the valuation, creation, storage, use, archival, and destruction of data. Data governance is largely concerned with practices and processes which are used to ensure formal management of an organization’s data assets, while attending to data leadership, stewardship, quality, sharing and access, security and privacy, and reliability.

Western’s data governance framework does not pertain to data collected for scholarly research.

What is involved in Data Governance?


Sets of processes associated with strengthening the processes and elevating awareness related to Western’s institutional data assets, the ways in which data assets can and should be used, and the information lifecycles involved. Ensuring that there are common data definitions and that those definitions are made available across platforms is essential to enabling informed data-driven decision-making. This pillar will be used to make decisions on what those definitions are and how we technically support the requirements of those definitions.


Data leadership and stewardship are essential parts of any data governance program. Those responsible for data leadership are accountable for the integrity and quality of our data. This pillar will be used to determine who in the institution has the authority to make decisions regarding access, priorities, and data usage standards, and under what conditions those decisions can be made.


Processes and metrics to assist in the definitions and measurements of data quality, the attendant availability of institutional data, and the usefulness of said data within a variety of strategic and tactical contexts. This pillar is concerned with optimizing data and related data analytics infrastructure and services. This pillar will be used to determine who has the authority to make decisions regarding access, priorities, and data usage standards, and under what conditions those decisions can be made.


Working through the defining, creating, storing, sharing, archiving, and destruction phases of the information lifecycle, clear documentation that outlines data timeliness, relevancy, lifespan, and usefulness will be measured via this pillar. This pillar will be used to empower our data community through data literacy, manage access to relevant and appropriate datasets, and ensure that data are used in compliance with regulatory and institutional contexts, with privacy, security, and sensitivity embedded in our processes.

Who ensures Data Governance at Western?

Data Governance is only achieved through collective effort. The Western Data office will lead on the framework component but will rely on diffused roles, accountabilities, and responsibilities to effect maturity in this area.

What is the necessity of a Data Governance program?

The need of Data Governance is present in all organizations/institutions. Data Governance allows for all entities associated with the organization to trust in, and rely on, the data at hand, as well as understand the capabilities that stem from high quality institutional data. Data Governance is required for the following reasons:

  • To enhance Data Literacy throughout the institution
  • To understand and catalog institutional data sources
  • With an abundance of data, Western can determine insights through predictive and prescriptive analytics
  • As a tool to implement and support Western's strategy directions 
  • To identify Data Leads, Data Stewards and Data Custodians at Western

What are Data Leads?

Data Domain Leads are the roles that are accountable for data presence at the functional data domain level. Responsibilities include formal approval of data definitions, data classifications, data sharing agreements, approval of data access requests, and determination of ongoing departmental strategy. A Data Domain Lead is also concerned with risk, appropriate access to data, and the presence of a solution’s data within the institution. These roles actively champion the ideation, implementation, and enforcement of data governance within their functional areas of responsibility.

What are Data Stewards?

Data Stewards are highest level of specific domain expertise in a given area (knowledgeable about data definition, lifecycle, history, sharing, and use) and are largely concerned with application of data within data systems. Formally responsible for data presence within the institution and effort would include the ability to amend data definitions, data classifications, and data sharing arrangements. A Data Steward is concerned with the meaning of data and the correct use of data within respective contexts. Data Stewards are accountable to Data Leads within the data governance model specifically. Data Stewards lead in defining, implementing, and enforcing data management processes and procedures within their application context.

What are Data Custodians?

Data Custodians are roles identified as creators, curators, updaters, and sharers of institutional data within specified contexts. Formally responsibility for data reliability and trustworthiness and efforts include informing data definitions and data classifications. A Data Custodian manages the actual data in the form of processes, extract-transform-load (ETL) procedures, access control, backups, and documentation. The Data Custodian is responsible for documenting solution schema and data lineage. Data Custodians are system administrators or application operators who are responsible for the management of solutions that collect, manage and provide access to institutional data.

What is a Data Asset?

A Data Asset can be defined as a collection of data found within an organization and can be either a system or an application. Typically, databases that include transactional data, qualitative data, quantitative data etc. can be assets. A Data Asset can be a major system in use at Western (system of record), or something that provides specific functionality for a given requirement (line of business).  Also, a Data Asset can be spreadsheets, Access databases, etc. The point of a Data Asset is that it contains uniqueness, even if it draws source data from other systems.

What is a Data Glossary (Dictionary)?

A Data Glossary (or Dictionary) is a repository of data definitions, or a collection of metadata about data elements collected and used within the institution. Commonly used terms can be collected within a Data Glossary that can then be used to inform a University Data Reference Model. 

What is a Data Asset Catalog?

Simply put, a Data Asset Catalog is a well-maintained inventory of all data assets in the organization. It allows Western to gain a better understanding of the data at hand, which includes identifying capabilities and about what information we lack. The Data Asset Catalog is intrinsically linked to the Data Glossary, the mapping of Data Domains and Functional Domains with Data Trustees and Leads, and allows for linkage between glossary entries and fields that exist within applications.

How can data be accessed?

There have been multiple ways to access data from a variety of systems over the years. A request system is being developed that will allow for careful tracking of these types of requests and will formalize data sharing agreements where appropriate.

What data falls under the Data Governance program?

Institutional Data are informational elements created, captured, curated, and managed within the inclusive context of Western’s administrative and operational processes.  Such datasets are typically arrayed within structured databases but can also be found as unstructured in nature. 

Institutional data exists within the institution’s enterprise resource platform (ERP), student information system (SIS), learning management system (LMS), customer relationship management (CRMs) systems, and other data environments that fall under the definition of institutional systems of record (SoR). Institutional data may also reside within divisional or departmental contexts as line of business systems (LoB), or may be housed within granular local solutions such as forms, Excel spreadsheets, Access databases, etc.

Western’s data systems may also contain sensitive information not intended for institutional analytics, but they are still considered part of Western data governance in terms of defining purpose and roles and responsibilities. Such data repositories would include metadata and certain forms of transactional data.

Western’s data governance framework does not pertain to data collected for scholarly research.

What is Data Maturity?

We can define Data Maturity as a measure of how well data processes perform, and how these processes integrate with all other components within the institution.  

The Institutional Data Office will regularly monitor and evaluate Data Maturity with respect to each level of the institution and will also provide recommendations to augment processes to achieve the standards of the institution.