KSL-97-02 + redirect page
Large-Scale Repositories of Highly Expressive Reusable Knowledge + Has identifier
Large-Scale Repositories of Highly Expressive Reusable Knowledge + Ksl tr id
Large-Scale Repositories of Highly Expressive Reusable Knowledge + Number
| Large-Scale Repositories of Highly Expressive Reusable Knowledge |
Bibtype
techreport
Has publishing details
April,1997
Has title
Large-Scale Repositories of Highly Expressive Reusable Knowledge
Has where published
KSL-97-02
Has year
1997
Title
Large-Scale Repositories of Highly Expressive Reusable Knowledge
Year
1997
Abstract
We present a vision of next generation too … We present a vision of next generation tools and services that will enable the widespread development and use of computer interpretable ontologies. Central to that vision is the notion of distributed ontology repositories resident on multiple ontology servers containing large-scale highly structured ontologies and supported by sophisticated ontology construction, testing, merging, extraction, reformulation, and translation tools. The key enabler in the distributed ontology repository architecture is a network application programming interface (API) for ontology servers that will support storage, manipulation, and access to the contents of ontologies on a server. We describe how OKBC, an API specifically designed to provide knowledge-level interoperability among server and client systems, provides that support. We then consider the criteria for an ontology representation language and an agenda of extensions to current ontology representation languages that address major deficiencies in those languages and appear to be attainable in next generation languages. Finally, we address the issue of what reasoning is needed to support ontology repository construction and use, and describe a deductive retrieval facility under development for the Ontolingua ontology server that includes a theorem prover which runs as a background task to reformulate sentences so that are accessible by the server's special purpose high speed retrieval methods. cial purpose high speed retrieval methods.
Note
(Updated March 1998).
Address
Stanford, CA, USA +
Author
Richard Fikes and Adam Farquhar +
Has author
Richard Fikes and Adam Farquhar +
Has identifier
Large-Scale Repositories of Highly Expressive Reusable Knowledge +
Institution
Knowledge Systems, AI Laboratory +
Ksl tr id
Large-Scale Repositories of Highly Expressive Reusable Knowledge +
Month
April +
Number
Large-Scale Repositories of Highly Expressive Reusable Knowledge +
Process note
NO +
Categories KSL Technical Report +, Publication +, Technical Report +
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