What is meant by ‘ontology’?
Ontologies, as the term is used here, are formal descriptions of entities in a certain domain and their relationships to one another. This is different from Ontology as a sub-field of philosophy, which is about the study of being and the fundamental categories of existence. Formal ontologies, in contrast to taxonomies (like the familiar taxonomy of animals and plants), or thesauri or vocabulary lists, define the relations between entities as logical constraints, which allows for reasoning.
For example, an ontology on buildings may contain generic concepts (e.g. building, house, roof, colour, or tilt), which can be related to one another, e.g. a house has a roof as part and is located in a village and a roof has a colour and a tilt (“has part”, “located in”, “has colour” and “has tilt” are relations).
Specific instances of classes can be defined as well, e.g. the Eiffel tower is a building and has a grey colour. Here, the Eiffel tower is an instance of the class of buildings and grey is an instance of colour. [Booshehri et al., Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis, Energy and AI, Vol. 5, 2021, https://doi.org/10.1016/j.egyai.2021.100074]
Why do ontologies matter?
Ontologies provide a human- and machine-readable representation of the concepts, their meaning and their relations to other concepts within a domain. Typical applications are data integration and annotation, reuse of information, knowledge sharing, semantic search and information retrieval. They can serve as a backbone for knowledge graphs and linked data. There are expected to improve the usage of large language models by providing domain-oriented factual information which helps e.g. to reduce hallucinations.
What kinds of ontologies exist?
Ontologies are distinguished by their purpose:
Reference ontologies represent concepts (‘terms’) and their relations to each other for a certain domain, i.e. area of interest / research, agnostic to a specific use case. Here especially, a focus is on consensus creation within the respective domain / research community on the definition of concepts and their (logical and text-based) definitions. These ontologies are built for reuse.
In contrast, application ontologies are tailored especially for a certain use case, e.g. a project. These ontologies are usually not built for reuse.
Ontologies, especially reference ontologies, can furthermore be distinguished by their level of detail. The most typical are top-level ontologies and domain ontologies.
Top-level ontologies represent fundamental concepts (e.g., ‘object’, ‘property’, ‘process’) to provide a basic and domain-independent pre-structure for domain ontologies. Common top-level ontologies are BFO, UFO or DLOCE.
Domain ontologies represent the knowledge of a certain area of interest with respect to the necessary level of detail. They ideally use a top-level ontology as pre-defined structure.
How do I use an ontology?
Ontologies usually serve as a backbone rather than a direct user tool. They provide the shared structure that allows data, systems, and models to “speak the same language.” By connecting information to well-defined concepts and relationships, ontologies make it possible to integrate, compare, and reason over data from different sources. While end users rarely interact with ontologies themselves, many applications — such as semantic search, knowledge graphs, or automated data validation — rely on them in the background to ensure consistent meaning and interoperability.
Relevance in the NFDI4Energy Context
Within NFDI4Energy, a set of energy-related ontologies are being developed to represent the different aspects, i.e. domains, of the research cycle. The goal is to make these ontologies interoperable to each other and to other energy-related ontologies, e.g. Open Energy Ontology.
Related Task Areas
Related NFDI4Energy Services
The Open Energy Ontology is accessed through the Open Energy Platform or through the Terminology Service