Ontology software helps to structure and manage knowledge on a domain so that it becomes more machine-readable. This enables AI to answer domain-related queries more accurately, and perform tasks more efficiently, than when using unstructured data.
What is an ontology?
The formal framework of rules, relationships and concepts that govern a domain’s data is known as an ontology. An ontology standardises the definitions of concepts within an area of knowledge, so that both machines and human experts understand them.
Why do ontologies matter?
Ontologies are valuable because they make data integration and semantic search easier and more reliable. In other words, they bring lots of data together from different sources, and make it easier to find data by understanding the searcher’s intent better. This provides vertical AI with greater powers of accuracy, speed and insight.
Ontologies open up opportunities for automation and AI innovation. Large language models (LLMs) cannot always be relied upon for critical tasks when they use unstructured data, as it can cause them to hallucinate and make mistakes. Ontologies, on the other hand, enable AI to perform a much wider range of critical and high value jobs because the outputs are more transparent and verifiable.
In the age of AI, demand for ontologies is growing fast.
How does ontology software help?
Ontology as a service (OaaS) provides a digital environment for ontology development, where non-technical users can build, visualise, query and integrate ontologies. On a technical level, ontology software can support AI teams and enterprises by suggesting ways to define classes (categories of entities), properties (relationships or attributes), and instances (specific examples).
OaaS can also help with building consensus around the standardised rules, relationships and concepts that make up an ontology. They do this by offering collaborative tools and anonymised feedback. Introducing deadlines and nudges can help to keep up momentum and get a working ontology over the line.
Who uses ontology software?
Ontology tools are widely used in bioinformatics, advanced manufacturing, the insurance industry – and increasingly in the art world. All these sectors have huge stores of often siloed data that they want to get more value out of.
A domain intelligent database can provide detailed and contextually smart search results in seconds, making everyone’s life easier. A 2024 study by BioRxiv tied domain intelligence to ontology-driven knowledge representation in biomedicine and healthcare.
What is an example of ontologies in action?
Taking museums as an example, ontology software can help academics from around the world to agree on semantic definitions (the precise meaning of ‘watercolour’, for example), and map out how items in various collections, and the attributes of those items, relate to one another. AI can then assist academics to search and compare items, explore the relationships between works of art and people (how ‘Sunflowers’ relates to a particular art dealer, for example), and make new discoveries.