Description
Semantic web resources or Knowledge Graphs have emerged as a preferential source of training data for large language models and generative artificial intelligence. Domain specific Knowledge Graphs are currently being constructed by various NFDI consortia to enhance AI readiness and interoperability of data and metadata within and across these domains.
Here, we outline the construction of Knowledge Graphs from a bioimage data repository. We employ an ontology-based mapping mechanism between the underlying relational database and the semantic web layer, offering a SPARQL endpoint for semantic queries.
Recently, we have augmented our solution with GeoSPARQL capabilities, allowing query clients to find, access, and relate images based on geolocation coordinates. This provides a concrete example of how domain-specific metadata can be made discoverable and accessible to users and AI agents beyond the bioimage community.
Furthermore, we are exploring the federation of Knowledge Graphs across
independent bioimage repositories. Such a federated semantic layer could
enable AI agents to discover and access distributed bioimaging data through a common query interface, without requiring knowledge of the underlying repository implementations.
| MPI | Max Planck Institute for Evolutionary Biology |
|---|---|
| NFDI Consortium | NFDI4BIOIMAGE |