Skip to main content
SpringerLink
Log in

A Collaborative Environment for Authoring Large Knowledge Bases

  • Published:
Journal of Intelligent Information Systems Aims and scope Submit manuscript

Abstract

Collaborative knowledge base (KB) authoring environments are critical for the construction of high-performance KBs. Such environments must support rapid construction of KBs by a collaborative effort of teams of knowledge engineers through reuse of existing knowledge and software components. They should support the manipulation of knowledge by diverse problem-solving engines even if that knowledge is encoded in different languages and by different researchers. They should support large KBs and provide a scalable and interoperable development infrastructure. In this paper, we present an environment that satisfies many of these goals.

We present an architecture for scalable frame representation systems (FRSs). The Generic Frame Protocol (GFP) provides infrastructure for reuse of software components. It is a procedural interface to frame representation systems that provides a common means of accessing and modifying frame KBs. The Generic KB Editor (GKB-EDITOR) provides graphical KB browsing, editing, and comprehension services for large KBs. Scalability of loading and saving time is provided by a storage system (PERK) which submerges a database management system in an FRS. Multi-user access is controlled through a collaboration subsystem that uses a novel optimistic concurrency control algorithm. All the results have been implemented and tested in the development of several real KBs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Abarbanel, R. and Williams, M. (1986). A relational representation for knowledge bases, Technical Report, IntelliCorp. Mountain View, CA.

    Google Scholar 

  • Ballou, N., Chou, H.-T., Garza, J.F., Kim, W., Petrie, C., Russinoff, Donald Steiner, and Woelk, D. (1988). Coupling an Expert System Shell With and Object-Oriented Database System, Journal of Object Oriented Programming, 1(2), 12–21.

    Google Scholar 

  • Bernstein, P.A., Hadzilacos, V., and Goodman, N. (1987). Concurrency Control and Recovery in Database Systems, Addison-Wesley Publishing Company.

  • Borgida, A. and Brachman, R.J. (1993). Loading data into description reasoners. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data. (pp. 217–226). Washington, DC.

  • Borgida, A., Brachman, R.J., McGuinness, D.L., and Resnick, L.A. (1989). CLASSIC: A structural data model for objects. Proceedings of the 1989 ACM SIGMOD International Conference on Management of Data. (pp. 58–67). Portland, OR.

  • Chaudhri, V.K., Farquhar, A., Fikes, R., Karp, P.D., and Rice, J.P. (1998). OKBC: A programmatic foundation for knowledge base interoperability. Proceedings of the AAAI-98. Madison, WI.

  • Chaudhri, V.K., Farquhar, A., Fikes, R., Karp, P.D., and Rice, J.P. (1997). The generic frame protocol 2.0. Technical Report, (July). Artificial Intelligence Center, SRI International, Menlo Park, CA.

    Google Scholar 

  • Chaudhri, V.K. and Hadzilacos, V. (1998). Safe Locking Policies for Dynamic Databases. Journal of Computer and System Sciences. To Appear.

  • Chen, I.A. and Markowitz, V.M. (1995). An Overview of the Object-Protocol Model (OPM) and the OPM Data Management Tools, Information Systems, 20(5), 393–418.

    Google Scholar 

  • Chou, H.T. and Kim, W. (1986). A unifying framework for version control in a CAD environment. Proceedings of the Twelfth International Conference on Very Large Data Bases. (pp. 336–344).

  • Copeland, G. and Khoshafian, S. (1985). A decomposition storage model. Proceedings of the ACM SIGMOD International Conference on Management of Data. (pp. 268–279).

  • Davidson, S.B., Garcia-Molina, H., and Skeen, D. (1985). Consistency in Partitioned Networks, Computing Surveys, 17(3), 341–370.

    Google Scholar 

  • Eilerts, E.F. (1994). KnEd: An Interface for a Frame-Based Knowledge Representation System, Master' Thesis, University of Texas, Austin.

    Google Scholar 

  • Eriksson, H., Puerta, A.R., Gennari, J.H., Rothenfluh, T.R., Tu, S.W., and Musen, M.A. (1994). Custom-tailored development tools for knowledge-based systems. Technical Report KSL-94-67, Stanford University Knowledge Systems Laboratory, Stanford, CA.

    Google Scholar 

  • Eswaran, K., Gray, J., Lorie, R., and Traiger, I. (1976). The Notions of Consistency and Predicate Locks in Database Systems, Communications of the ACM, 19(9), 624–633.

    Google Scholar 

  • Farquhar, A., Fikes, R., Pratt, W., and Rice, J. (1995). Collaborative ontology construction for information integration. Technical Report KSL-95-63, Stanford University, Knowledge Systems Laboratory, Stanford, CA.

    Google Scholar 

  • Franklin, M. (1996). Client Data Caching: A Foundation for High Performance Object Database Systems, Kluwer Academic Publishers.

  • Franklin, M., Zwilling, M., Tan, C.K., Carey, M., and DeWitt, D.J. (1992). Crash recovery in client-server EXODUS. Proceedings of the ACM SIGMOD 1992 Annual Conference. (pp. 165–174). San Diego, CA.

  • Geiger, K. (1995). Inside ODBC, Microsoft Press.

  • Genesereth, M.R. and Fikes, R.E. (1992). Knowledge interchange format,Version 3.0 Reference Manual. Technical Report Logic-92-1, Computer Science Department, Stanford University, Stanford, CA.

    Google Scholar 

  • Gruber, T. (1992). Ontolingua: A mechanism to support portable ontologies. Technical Report KSL 91–66, Stanford University, Knowledge Systems Laboratory. Revision.

  • Gruber, T. (1993). A translation approach to portable ontology specifications, Knowledge Acquisition, 5(2), 199–220.

    Google Scholar 

  • Hall, K. (1991). A Framework for Change Management in a Design Database. Ph.D. Thesis, Stanford University Computer Science Department, Stanford, CA.

    Google Scholar 

  • Kaiser, G.E. (1990). A flexible transaction model for software engineering. Proceedings of the Sixth International Conference on Data Engineering. (pp. 560–567).

  • Karp, P., Riley, M., Paley, S., Pellegrini-Toole, A., and Krummenacker, M. (1998). EcoCyc: Electronic encyclopedia of E. coli Genes and Metabolism, Nuc. Acids Res., 26(1), 50–53.

    Google Scholar 

  • Karp, P.D. (1992). The design space of frame knowledge representation systems. Technical Report 520, SRI International, Artificial Intelligence Center. URL ftp://www.ai.sri.com/pub/papers/karp-freview.ps.Z.

  • Karp, P.D. and Paley, S.M. (1995). Knowledge representation in the large. Proceedings of the 1995 International Joint Conference on Artificial Intelligence. (pp. 751–758).

  • Karp, P.D., Paley, S.M., and Greenberg, I. (1994). A storage system for scalable knowledge representation. In N. Adam (Ed.), Proceedings of the Third International Conference on Information and Knowledge Management. (pp. 97–104), New York, Association for Computing Machinery. Also available as SRI International Artificial Intelligence Center Technical Report 547.

    Google Scholar 

  • Kehler, T. and Clemenson, G. (1984). KEE: The Knowledge Engineering Environment for Industry, Systems And Software, 3(1), 212–224.

    Google Scholar 

  • Kemper, A. and Kossmann, D. (1995). Adaptable Pointer Swizzling Strategies in Object Bases: Design, Realization, and Quantitative Analysis, VLDB Journal, 4(3), 519–566.

    Google Scholar 

  • Korth, H.F. and Speegle, G.D. (1990). Long-duration transactions in software design projects. Proceedings of the Sixth International Conference on Data Engineering. (pp. 568–574). Los Angeles, CA.

  • Lenat, D.B. and Guha, R.V. (1989). Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project, Reading, MA: Addison-Wesley Publishing Co.

    Google Scholar 

  • MacGregor, R. (1991). The evolving technology of classification-based knowledge representation systems. In J. Sowa (Ed.), Principles of Semantic Networks (pp. 385–400). Morgan Kaufmann Publishers: Los Altos, CA.

    Google Scholar 

  • Mays, E., Lanka, S., Dionne, B., and Weida, R. (1991). A Persistent Store for Large Shared Knowledge Bases, IEEE Transactions on Knowledge and Data Engineering, 3(1), 33–41.

    Google Scholar 

  • McKay, D., Finin, T., and O'Hare, A. (1990). The intelligent database interface: Integrating AI and database systems, Proceedings of the 1990 National Conference on Artificial Intelligence. (pp. 677–684). Morgan Kaufmann Publishers.

  • Mitchell, T., Allen, J., Chalasani, P., Cheng, J., Etzioni, E., Ringuette, M., and Schlimmer, J. (1989). THEO: A framework for self-improving systems. In Architectures for Intelligence. Erlbaum.

  • Neches, R., Fikes, R., Finin, T., Gruber, T., Patil, R., Senator, T., and Swartout, W. (1991). Enabling Technology for Knowledge Sharing, AI Magazine, 12(3), 36–56.

    Google Scholar 

  • Nodine, M.H. and Zdonik, S.B. (1990). Cooperative transaction hierarchies: Atransaction model to support design applications. Proceedings of the Sixteenth International Conference on Very Large Data Bases. (pp. 83–94). Brisbane, Australia, 1990.

  • Paley, S.M., Lowrance, J.D., and Karp, P.D. (1997). A generic knowledge base browser and editor. Proceedings of the Ninth Conference on Innovative Applications of Artificial Intelligence.

  • Papadimitriou, C. (1986). The Theory of Database Concurrency Control, Rockville, MD: Computer Science Press.

    Google Scholar 

  • Patil, R., Fikes, R.E., Patel-Schneider, P.F., Mackay, D., Finin, T., Gruber, T., and Neches, R. (1992). The DARPA knowledge sharing effort: Progress report. The Third International Conference on Principles of Knowledge Representation and Reasoning. (pp. 777–788). Boston, MA.

  • Rice, J.P. (1998). Writing an OKBC application. Technical Report KSL-98-15, Knowledge System Laboratory, Stanford, CA.

    Google Scholar 

  • Rice, J.P. and Farquhar, A. (1998). OKBC: A rich API on the cheap. Technical Report KSL-98-09, Knowledge System Laboratory, Stanford, CA.

    Google Scholar 

  • Rowley, S., Shrobe, H., and Cassels, R. (1987). Joshua: Uniform access to heterogeneous knowledge structures. Proceedings of the National Conference on Artificial Intelligence. (pp. 48–52). Seattle, WA.

  • Shrufi, A. and Topaloglou, T. (1995). Query processing for knowledge bases using join indices. Proceedings of the 4th International Conference on Information and Knowledge Management. Baltimore.

  • Sim, I. (1997). Trial Banks: An Informatics Foundation for Evidence-Based Medicine. Ph.D. Thesis, Stanford University.

  • Skuce, D. and Lethbridge, T. (1995). CODE4: A Unified System for Managing Conceptual Knowledge, International Journal of Human-Computer Studies.

  • Starr, B., Chaudhri, V.K., Farquhar, A., and Waldinger, R. (1998). Knowledge intesive query processing. Proceedings of the 5th International Workshop Knowledge Representation Meets Databases (KRDB'98). Seattle, USA.

  • Terry, D., Theimer, M., Petersen, K., Demers, A.J., Spreitzer, M., and Hauser, C.H. (1995). Managing update conflicts in bayou, a weakly connected replicated storage system. Proceedings of the 15th ACM Symposium on Operating Systems Principles (SOSP-15). Copper Mountain Resort, Colorado.

  • Tichy, W.F. (1985). RCS—A System for Version Control, Software—Practice and Experience, 15(7), 637–654.

    Google Scholar 

  • Valduriez, P., Khoshafian, S., and Copeland, G. (1986). Implementation techniques of complex objects. Proceedings of the 12th International Conference on Very Large Data Bases. (pp. 101–109). Kyoto, Japan.

  • Wäsch, J. and Klas, W. (1996). History merging as a mechanism for concurrency control in cooperative environments. Proceedings of RIDE'96: Interoperability of Non-Traditional Database Systems. New Orleans, Louisiana.

  • Wilkins, D.E. (1990). Can AI Planners Solve Practical Problems? Computational Intelligence, 6(4), 232–246.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pangea Systems, 4040 Campbell Avenue, Menlo Park, CA, 94025

    Peter D. Karp

  2. Artificial Intelligence Center, SRI International, 333 Raenswood Avenue, Menlo Park, CA, 94025

    Vinay K. Chaudhri

  3. Pangea Systems, 4040 Campbell Avenue, Menlo Park, CA, 94025

    Suzanne M. Paley

Authors
  1. Peter D. Karp
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vinay K. Chaudhri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suzanne M. Paley
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Karp, P.D., Chaudhri, V.K. & Paley, S.M. A Collaborative Environment for Authoring Large Knowledge Bases. Journal of Intelligent Information Systems 13, 155–194 (1999). https://doi.org/10.1023/A:1008763932600

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008763932600

Search

Navigation