Ontology Summit 2008 Communique Draft Review - "State of Art" Breakout Group

Ref: OntologySummit2008_Communique/Draft

The Team:

• Frank Olken
• Natasha Noy
• DeborahMcGuinness
• IndraNeilSarkar
• Katherine Goodier
• Mala Mehrotra
• Amy Davidson (BBN)

Reviewed and updated section

State of the Art for Ontology Repositories

The purpose of this section is to set out the major design decisions and the technology choices which are important to the creation of ontology repositories.

Ontology repositories support the storage, search, retrieval and integration of multiple ontologies.

Ontology repositories support macro-level storage, query and retrieval (across the collection of ontologies) and micro-level operations (within individual ontologies). At each level we would like to support both text search, and semantic search (variously faceted search, SPARQL, ontology and ontology language literate search). Some ontology repositories have used the same technologies for both macro-level and micro-level operations.

A key decision is the choice of a representation of the ontologies. Current practice includes: text, frames (e.g., OBO), graphs (e.g., RDF), and various types of logic, e.g., description logics (e.g., OWL-DL), first order logic (e.g., Common Logic), sorted logics, possibly higher order logic (HOL). Other possibilities include the use of UML (e.g., in the OMG Ontology Definition Metamodel).

Ontologies have been stored in long narrow relations, e.g., "triple stores" of RDF triples (subject, relationship, object), relational databases, customized data stores. Increasingly implementors are using "quad stores" in order to support Named Graphs. "Column stores" such as MonetDB and Vertica have also been used to store ontologies.

For the purposes of ontology integration it helps to have all of the ontologies in the repository encoded in a common representation. However, this requires the sometimes difficult and lossy translation of ontologies among various representations into the common representation. Some ontology repositories store ontologies in their native representation, with some metadata to identify the representation language.

We also need some way to support ontology interoperation by specifying the mappings among entities, e.g., with relationships such as same_as, is_a, and part_of. Other mapping relationships include: see_also, similar_to. Some ontology mapping consistency checking tools check that mappings between partially ordered ontologies, e.g., taxonomies, preserve the partial orders.

Many ontology repositories which support partially ordered ontologies (taxonomies and partonomies) may decide to materialize the transitive closure of the partial order relation. This provides faster query evaluation at the expense of additional ingestion costs, storage, and maintenance.

Provenance of definitions in ontologies is important to the credibility, scientific attribution, and regulatory compliance of ontologies. In particular, many definitions are embodied in legislation, administrative regulations, court decisions, professional society standards.

Provenance and other metadata are distinguishing features of recent ontology repositories. Such metadata ranges from authorship, and creation date, version information, to evaluation and usage reports. Other metadata may include intended use (context).

Modularization support is useful for large ontologies, and for facilitating reuse and mapping of portions of ontologies.

In a distributed setting, ontology repository developers increasingly are adopting Service Oriented Architectures (SOA), providing access, search, etc. capabilities via web services. Two major approaches to SOA are REST and SOAP. REST is built on HTTP, with a small set of operators (GET, PUT, POST, DELETE) and the use of URL (or URI) addresses for all objects of interest. SOAP is based on XML RPCs. REST is much simpler to implement and should be adequate for typical ontology repository functions. SOAP is supported by a wide variety of software tools. Both SOA approaches are currently being used.

Finally, an ontology repository typically facilitates access to a variety of ontology related tools: creation, editors, pretty printers, visualization tools, differencing tools, modularization tools, import / export, version management, access control, inference engines, explanation, summarization.

Version 2.0, April 29, 2008