Description
Ontologies are widely used across scientific domains, e.g. life sciences and materials science to organize complex knowledge and describe relationships between concepts, data, and processes. However, accessing this knowledge often requires familiarity with ontology engineering, specialized terminology, or query languages such as SPARQL. This can limit the use of ontologies by researchers and practitioners who could otherwise benefit from them.
This work presents how the Model Context Protocol (MCP) can support more natural ways of interacting with ontologies. Through an MCP-based conversational interface, users could ask questions in ordinary language—for example, about biological entities, material properties, or relationships between concepts—and receive answers grounded in the underlying ontologies. The system can also point users to relevant terms, relationships, and data sources, helping them understand where an answer comes from.
An important aspect of this approach is that it can support access to knowledge from several ontologies at once. These may be hosted within the same repository or distributed across different ontology repositories. This makes it possible to connect information from different domains, compare related concepts, and answer questions that cannot be addressed by a single ontology alone. For example, a user may combine information about a biological process with material properties relevant to biomedical applications.
By lowering the technical barrier to ontology use, this approach could help non-ontologists explore and reuse structured scientific knowledge more easily. It may also support collaboration across disciplines by making life science and materials science ontologies easier to discover, query, connect, and interpret.
| Topic | Topic 4: Can knowledge graphs and AI-based synthesis improve ecological synthesis? |
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