Coordination of Evolving Conventions Enabling Sharing of Knowledge

Information Sciences Institute
University of Southern California

Building knowledge-based systems today usually entails constructing a new knowledge base from scratch. Even if several groups of researchers are working in the same general area, such as medicine or electronic diagnosis, each team must develop its own knowledge base from scratch. The cost of this duplication of effort has been high and will become prohibitive as we build larger and larger systems. Furthermore, lack of methodology for sharing and communicating knowledge poses a significant road-block in large scale research projects such as ARPA/Rolm Laboratory Planning and Scheduling Initiative. To overcome these barriers and advance the state of art, we must find ways of preserving existing knowledge bases, and sharing, reusing, and building on them.

The goal of this effort is to develop a technology that will enable researchers to develop new systems by selecting components from libraries of reusable modules and assembling them together. Their effort will be focused on creating specialized knowledge and reasoners specific to the task of their system. Their new system would inter-operate with existing systems, using them to perform some of its reasoning. In this way, declarative knowledge, problem solving techniques and reasoning services could be shared among systems. The reusable modules in the library them-selves will benefit from refinements that are only possible through extensive re-use. This would facilitate building larger systems cheaply and reliably. Infrastructure to support such sharing and reuse would lead to greater ubiquity of these systems. potentially transforming the knowledge industry.

Technical analyses of knowledge representation technology indicated four complementary areas in which development of common, agreed-upon conventions would enhance leverage between individual research efforts. (These analyses were initiated in a three-day workshop involving over 40 top AI and database researchers from DARPA, NSF, and industry communities.) The four areas are:

1. Mechanisms for translation between knowledge bases represented in different languages;
2. Common versions of languages and reasoning modules within families of representational paradigm;
3. Protocols for communication between separate knowledge-based modules, as well as between knowledge-based systems and databases; and,
4. Libraries of ``ontologies,'' i.e., pre-fabricated foundations for application-specific knowledge bases in a particular topic area.

1. Enabling Technology for Knowledge Sharing. Robert Neches, Richard Fikes, Tim Finin, Thomas Gruber, Ramesh Patil, Ted Senator, and William R. Swartout. AI Magazine, VOl 12, No.3, Fall 1991.
   Paper without figures for slow speed connections.
2. The DARPA Knowledge Sharing Effort: Progress Report. Ramesh S. Patil, Richard E. Fikes, Peter F. Patel-Schneider, Don McKay, Tim FInin, Thomas Gruber and Robert Neches. In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning, ed. B. Nabel, C.Rich, and W. Swartout, Cambridge, MA. Oct 25-29, 1992.
3. "KQML: An Information and Knowledge Exchange Protocol" , Tim Finin, Don McKay, Rich Fritzson, and Robin McEntire. In Kazuhiro Fuchi and Toshio Yokoi (Ed.), "Knowledge Building and Knowledge Sharing", Ohmsha and IOS Press, 1994.
4. Additional papers will appear here as they become available.

• The Knowledge Interchange Format

• Knowledge Query Manipulation Language

• Knowledge-Sharing Libraries including Ontologies.

• KRSS: Standard Specification for the KL-ONE family of languages. Available in Postscript and in Latex. These can also be accessed through annonymous FTP@isi.edu from ``pub/httpd/htdocs/isd/KRSharing/krss/'' directory.