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SciGraph

  • What it is — SciGraph represents ontologies and ontology-encoded data as a Neo4j property graph. It is an OWL-centric, domain-agnostic loader and access layer with graph, vocabulary, annotation, and REST operations.

  • Key concepts —

    • Ontologies are presented as formal, explicit specifications of shared conceptualizations that can serve as data, vocabulary, or semantics.
    • OWL classes, subclass relations, object properties, and existential restrictions are mapped into graph structure; the documentation stresses that “the IRI is king” and distinguishes IRIs, CURIEs, and fragments as identifiers.
    • Vocabulary support connects ontology identity to application features: label-to-node resolution, CURIE-to-IRI resolution, search, autocomplete, suggestions, OpenRefine resolution, and free-text entity identification.
    • The graph enables relationship-pattern queries across combined ontological and biological data, illustrated with subclass, phenotype, interaction, orthology, and sequence relationships.

  • How you’d use it —

    • Ingest OWLAPI-supported formats—including OWL, RDF, OBO, and TTL—into Neo4j with the batch loader and YAML configuration; configuration can name ontologies, reasoner settings, categories, and mapped properties.
    • Consume the result directly through Neo4j/Cypher, add scigraph-core for convenience and vocabulary operations, or run scigraph-services as a Dropwizard REST service. The documented REST surface includes vocabulary lookup/search/autocomplete, lexical annotation, graph lookup/neighborhoods, and configurable domain-specific Cypher queries.
    • Graph endpoints can return json-bbop, GraphML, GraphSON, GML, JPEG, or PNG. Once generated, the graph can also be used by an application with no SciGraph dependency.

  • LLM angle — none stated

  • Pitfalls & lessons —

    • The mapping is explicitly lossy and does not round-trip ontologies; SciGraph does not create, manage, or version ontologies, is not a primary data store, and does not support CRUD operations.
    • Reasoning support is a stated non-goal. The presentation also says OWL mapping requires declarations in cases such as SKOS.
    • SciGraph is OWL-centric: an arbitrary SKOS ontology whose skos:Concept resources are not asserted as owl:Class will not expose those concepts to OWLAPI and they will not be loaded.
    • The authors list Neo4j limitations for this use: poor fit for global aggregate number crunching and binary/blob/object storage, Neo4j-specific Cypher, and a conceptual shift; an earlier presentation also flags replication.
    • Because Neo4j uses memory-mapped I/O, its database cannot be stored in a Vagrant shared directory.

  • Verdict — A focused OWL-to-Neo4j ingestion and access toolkit for ontology-backed graph, vocabulary, and annotation services—not an ontology authoring, versioning, round-tripping, or general reasoning system.

Sources consulted

  • README.md
  • docs/presentation/20150211 SciGraph.pptx
  • docs/presentation/20150801 SciGraph.pptx