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Sunday, May 21, 2000

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Stanford Medical Informatics Preprint Archive The knowledge model of Protege-2000: Combining interoperability and flexibility
"Knowledge-based systems have become ubiquitous in recent years. The World-Wide Web consortium is developing the Resource Description Framework (RDF) - a system for annotating even Web pages with knowledge elements. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. Therefore, interoperability among different knowledge-representation systems is essential. The Open Knowledge-Base Connectivity protocol (OKBC) is a common query and construction interface for frame-based systems that facilitates this interoperability. Protege-2000 is an OKBC-compatible knowledge-base–editing environment developed in our laboratory. Protege-2000 has an easy-to-use and configurable interface. We describe its OKBC-compatible knowledge model that makes the import and export of knowledge bases from and to other knowledge-base servers easy. We discuss how the requirements of being usable and configurable knowledge-acquisition tool affected our decisions in the knowledge-model design. Protege-2000 also has a flexible metaclass architecture which provides configurable templates for new classes in the knowledge base. The use of metaclasses makes Protege-2000 easily extensible and enables its use with other knowledge models. For example, we demonstrate that we can resolve many of the differences between the knowledge models of Protege-2000 and RDF by defining a new metaclass set. Resolving the differences between the knowledge models in declarative way enables easy adaptation of Protege-2000 as an editor for other knowledge-representation systems."
The Protege Project
"Protégé allows domain experts to build knowledge-based systems by creating and modifying reusable ontologies and problem-solving methods.

"Protégé-2000 source code is available under the open-source license."

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Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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