Building the Data Foundations for UK Higher Education
We’re developing foundational open ontologies (data models) and shared controlled vocabularies (term lists, taxonomies, etc), helping the sector build a more interoperable future. These building blocks are key to leveraging data effectively, grounding AI initiatives, and preparing institutions to adopt new technologies.
Community Forums
This is our shared space for information and data architects, engineers and other professionals to connect, ask questions, and share best practices.
Shared Vocabularies
This is our shared dictionary. A central place to curate the agreed-upon terms, lists, and taxonomies (using standards like SKOS-XL) for the sector. This ensures that when we talk about the stuff and things in our institutions, such as a ‘student’ or a ‘course’, we all mean the same thing, and where we don’t, we can understand what the relationships actually are.
Models and Ontologies
Our collaborative project to build a shared blueprint. We use the terms from our vocabularies to build a common data model and ontology. This defines how data relates, providing the full structure that interoperability efforts can be built on and enabling new technologies.
About us
Our mission is to build the shared data foundations for the UK Higher Education sector. We believe that by creating open, foundational data models and shared vocabularies, we can help institutions unpick data complexity, streamline regulatory reporting, and build a more interoperable future.
This foundational work is essential for leveraging data effectively, grounding AI initiatives, and preparing the sector to adopt new technologies that understand the essence and the meaning of, the business of higher education.
Frequently Asked Questions
What is a Controlled Vocabulary?
A controlled vocabulary is an official, agreed-upon set of terms or phrases used to describe specific concepts.
Think of them in this context, a little like a shared dictionary for the sector.
They ensure that everyone is on the same page, using the same term for the same idea, for example using the term ‘Postgraduate Taught’ instead of ‘PGT’ or ‘Masters’.
For the term ‘Student’, its definition might be ‘A person formally enrolled for a programme of learning at a higher educational institution of learning.’
The purpose here is to have a shared common understanding of what a student is, and to stop using different words for the same thing (such as pupil or learner).
A controlled vocabulary is the first essential step in making data interoperable between different systems.
Are ontologies a new thing? Why am I only just hearing about them? What exactly is an ontology?
That’s more that one question, let’s try to unpack that.
No, they’re not new. They are deeply rooted in philosophy (the study of ‘being’) and have been a key part of artificial intelligence (AI) and the Semantic Web movement since the 1990s.
You’re hearing about them now, as their importance has ‘exploded’ recently, for a couple of key reasons: The rise of AI and Large Language Models (LLMs), and the ‘data mess’ many organisation find themselves in.
An ontology is really the formal blueprint or ‘model’ of a subject.
If a controlled vocabulary is a dictionary of words, then an ontology represents the grammar of how those words relate to each other.
For example, an ontology for a university would formally define what a ‘Student’ is, what a ‘Course’ is, and then define the relationship between them, for example a ‘Student is enrolled in a Course’. This model, which a computer can understand, allows different systems to share and reason over complex data and information.
I’m confused… If I want to define what the term ‘Student’ means, do I do that in my Controlled Vocabulary or in my Ontology?
Both. Kind of…
You define your term in your controlled vocabulary, the dictionary that manages the human-readable language, that defines what a Student represents to your university.
Your Ontology (the blueprint) uses your Controlled Vocabulary (the dictionary) for it’s labels. In your ontology, you define the logical class ‘Student’. To provide it with a human readable name and definition, you point it to the entry for ‘Student’ in your controlled vocabulary.
You won’t need to define the term ‘Student’ as we’re doing that for you. You can find it in our Controlled Vocabularies.
Why redefine the terms for a well-established industry?
It may seem like that, but that isn’t really what we are doing. If a term is already well defined somewhere, licensed free to use and modify, we may choose to adopt the same definition. Where this happens, the original author will be credited. The definition of terms is a ‘necessary evil’ of this initiative, whose primary goal is to build solid semantic foundations and structures for the Higher Education sector.
Why are you doing this?
This is an area that has rapid growth. Although there are differences in how UK Higher Education institutions are structured, there are also a lot of commonalities, perhaps more-so than some other industries.
There is a long history of universities working collaboratively with each other.
This initiatives formalises the words used to describe the things that make up these institutions and how those things relate to, and interact with, each other.
If each university in the UK were to pursue this individually, it would be time consuming, costly to deliver, onerous to maintain and would not resolve the underlying problem of inconsistent terminology.
It’s cost effective for the sector – this is a community driven effort, that provides a free tangible resource.
Your definition for ‘Student’ is wrong, can you change it please?
It’s not wrong. It may not align with your definition. Feel free to join the community, in order to constructively weigh-in.