Data models
A data model is a visual representation of how data is organised, and the relationships between different types of data. At UQ, we’re interested in several types of data models:
- Information Entity Catalogue
- Conceptual data models
- Logical data models
- Physical data models
Data models allow us to think holistically about data throughout the entire information lifecycle - all the way from collection through to disposal - improving its quality and accuracy. Depending on the type of data model, these visual representations capture the complex relationships between different categories of data, business areas, and business processes, and help us understand how they relate to each other.
The Data Strategy & Governance team has developed data models which provide greater understanding of UQ’s complex data landscape. This foundational but critical work has been completed in collaboration with subject matter experts from relevant organisational areas, helping build a greater understanding of their systems and business processes.
Learn more about the types of data models below:
Information Entity Catalogue
The Information Entity Catalogue describes, at an aggregate level, the data and information supporting University program and business operations. The data is organised and categorised in ‘Information Domains’, which relate to business functions and broad data categories termed ‘Information Entities’.
From the Information Entity Catalogue, specific Information Domains are expanded as Conceptual Data Models, showing the connections between each type of data. Conceptual data models offer a big-picture view of what the data associated with business functions use and generate, how data will be organised, and how different Information Entities relate to, or impact one another.
For example, referring to the Curriculum domain on the Information Entity Catalogue, course offerings, timetabling, and other Information Entities can be viewed as part of this Domain. Then moving over to the Conceptual Data Model that expands the Curriculum Domain, it becomes clear how these Information Entities relate to each other – an Academic Program incorporates data about the degree being studied, and graduate attributes. This may be helpful for an employee in student support who has been requested to assist a student with mapping their current degree to their career aspirations.
Logical data models are less abstract and provide greater detail about the concepts and relationships in the Domain under consideration. These data models are primarily informed by how data is organised within a system, as well as business rules.
Physical data models provide a schema for how the data will be physically stored within a database. They describe the relationships between fields, tables, and hierarchies. As such, they are the least abstract of all.
How can data models help me?
Data models give a holistic view of data use across the University. You can find current versions of the Information Entity Catalogue and data models on the Data Architecture Artefacts webpage (UQ login required).
Data models and the Information Entity Catalogue inform data integration activities, such as migrating data to a new IT system, and data sharing by providing information about who is responsible for approving access to data within different Information Domains and Entities. By providing contextual information about the UQ data landscape and relationships between data types, data models also enable stakeholders across the University to better leverage data to support strategic decision making, optimise reporting, mature data governance practices, and manage cybersecurity risks.
