Contexts for the Semantic Web

  • Ramanathan Guha
  • Rob McCool
  • Richard Fikes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3298)


A central theme of the Semantic Web is that programs should be able to easily aggregate data from different sources. Unfortunately, even if two sites provide their data using the same data model and vocabulary, subtle differences in their use of terms and in the assumptions they make pose challenges for aggregation. Experiences with the TAP project reveal some of the phenomena that pose obstacles to a simplistic model of aggregation. Similar experiences have been reported by AI projects such as Cyc, which has led to the development and use of various context mechanisms. In this paper we report on some of the problems with aggregating independently published data and propose a context mechanism to handle some of these problems. We briefly survey the context mechanisms developed in AI and contrast them with the requirements of a context mechanism for the Semantic Web. Finally, we present a context mechanism for the Semantic Web that is adequate to handle the aggregation tasks, yet simple from both computational and model theoretic perspectives.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Tim Berners-Lee. Semantic web architecture,
  2. 2.
    Bobrow, D.G., Winograd, T.: On overview of krl, a knowledge representation language. Cognitive Science 1, 3–46 (1997)CrossRefGoogle Scholar
  3. 3.
    Buvač, S.: Quantificational logic of context. In: Shrobe, H., Senator, T. (eds.) AAAI 1996, pp. 600–606. AAAI Press, Menlo Park (1996)Google Scholar
  4. 4.
    Buvač, S., Buvač, V., Mason, I.: Metamathematics of contexts. Fundamenta Mathematicae 23(3) (1995), Available from
  5. 5.
    Buvač, S., Fikes, R.: A declarative formalization of knowledge translation. In: Proceedings of the ACM CIKM: the Fourth International Conference in Information and Knowledge Management (1995), Available from
  6. 6.
    Buvač, S., Mason, I.: Propositional logic of context. In: AAAI, pp. 412–419 (1993)Google Scholar
  7. 7.
    de Paiva, V.: Natural deduction and context as (constructive) modality. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds.) CONTEXT 2003. LNCS, vol. 2680, pp. 116–129. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Giunchiglia, F., Ghidini, C.: Local models semantics, or contextual reasoning = locality+compatibility. In: Cohn, A.G., Schubert, L., Shapiro, S.C. (eds.) KR 1998: Principles of Knowledge Representation and Reasoning, pp. 282–289. Morgan Kaufmann, San Francisco (1998)Google Scholar
  9. 9.
    Guha, R., McCarthy, J.: Varieties of contexts. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds.) CONTEXT 2003. LNCS, vol. 2680, pp. 164–177. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  10. 10.
    Guha, R.V.: Contexts: a formalization and some applications. Technical Report STAN-CS-91-1399, Stanford CS Dept., Stanford, CA (1991)Google Scholar
  11. 11.
    Hayes, P.: Rdf semantics,
  12. 12.
    Klyne, G.: Contexts and the semantic web,
  13. 13.
    Klyne, G.: Contexts for the semantic web,
  14. 14.
    McCarthy, J.: Generality in artificial intelligence. In: Lifschitz, V. (ed.) Formalizing Common Sense: Papers by John McCarthy, pp. 226–236. Ablex Publishing Corporation, Norwood (1990)Google Scholar
  15. 15.
    McCarthy, J.: Notes on formalizing contexts. In: Bajcsy, R. (ed.) Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, pp. 555–560. Morgan Kaufmann, San Mateo (1993)Google Scholar
  16. 16.
    Pandurang Nayak, P.: Representing multiple theories. In: Hayes-Roth, B., Korf, R. (eds.) AAAI 1994, Menlo Park, CA, pp. 1154–1160 (1994)Google Scholar
  17. 17.
    Guha, R., Lenat, D.: Context dependence of representations in cyc. In: Colloque ICO (1993)Google Scholar
  18. 18.
    Guha, R., McCool, R.: Tap: A semantic web platform. Computer Networks 42, 557–577 (2003)MATHCrossRefGoogle Scholar
  19. 19.
    Guha, R., McCool, R., Miller, E.: Semantic search. In: WWW 2004, Budapest, Hungary (2003)Google Scholar
  20. 20.
    Guha, R., McCool, R.: Tap: Towards a web of data,

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ramanathan Guha
    • 2
  • Rob McCool
    • 1
  • Richard Fikes
    • 1
  1. 1.Artificial Intelligence LaboratoryStanford UniversityUSA
  2. 2.IBM ResearchUSA

Personalised recommendations