Ad-Hoc and Personal Ontologies: A Prototyping Approach to Ontology Engineering

  • Debbie Richards
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4303)


Large scale or common ontologies tend to be developed using structured and formal techniques that can be equated to the Waterfall system development life cycle. However, in domains that are not stable or well-understood a prototyping approach may be useful to allow exploration and communication of ideas. Alternatively, the ontology may be part of an intermediate step or representation that provides structure, organization, guidance and semantics for another task or representation. Given that the ontology is not the end goal and possibly not reusable, the overhead of developing or maintaining such ontologies needs to be minimal. This paper reviews some of the research using ad-hoc, one-off and, sometimes, throw away, personal ontologies and provides an example of a simple technique which uses Formal Concept Analysis to automatically generate an ontology as needed from a number of data sources including propositional rule bases, use cases, historical cases, text and web documents covering a range of applications and problem domains.


Personal Ontology Formal Concept Analysis Ontology Engineering 


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  1. 1.
    Bennett, B.R., Theodoulidis, B.: Towards a notion of Personal Ontology (accessed 10th July 2006),
  2. 2.
    Berners-Lee, T., Handler, J., Lassila, O.: The Semantic Web. Scientific American (May 2001)Google Scholar
  3. 3.
    Boettger, K., Schwitter, R., Mollá, D., Richards, D.: Towards Reconciling Use Cases via Controlled Language and Graphical Models. In: Bartenstein, O., Geske, U., Hannebauer, M., Yoshie, O. (eds.) INAP 2001. LNCS (LNAI), vol. 2543, pp. 115–128. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Busch, P., Richards, D.: Modelling Tacit Knowledge via Questionnaire Data. In: Eklund, P.W. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 321–328. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Carmichael, D.J., Kay, J., Kummerfeld, R.J.: Personal Ontologies for feature selection in Intelligent Environment visualisations. In: Baus, J., Kray, C., Porzel, R. (eds.) AIMS 2004 - Artificial Intelligence in Mobile System, pp. 44–51 (2004)Google Scholar
  6. 6.
    Cendrowska, J.: An algorithm for inducing modular rule. Int. Journal of Man-Machine Studies 27(4), 349–370 (1987)zbMATHCrossRefGoogle Scholar
  7. 7.
    Chaffee, J., Gauch, S.: Personal Ontologies For Web Navigation. In: Int.Conf. Info. Knowledge Mgt (CIKM), pp. 227–234 (2000)Google Scholar
  8. 8.
    Cho, W.C., Richards, D.: Improvement of Precision and Recall for Information Retrieval in a Narrow Domain: Reuse of Concepts by Formal Concept Analysis. In: Proc. IEEE/WIC/ACM Int. Conf. Web Intell (WI 2004), Beijing, China, September 20-24, pp. 370–376 (2004)Google Scholar
  9. 9.
    Cho, W.C., Richards, D.: Automatic construction of a concept hierarchy to assist Web document classification. In: Proc. 2nd Int.Conf.on Info. Mgt and Business (IMB 2006), Sydney, Australia, February 13-16 (2006)Google Scholar
  10. 10.
    Cimiano, P., Hotho, A., Stumme, G., Tane, J.: Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund, P.W. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 189–207. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Cimiano, P., Staab, S., Tane, J.: Automatic Acquisition of Taxonomies from TexT: FCA meets NLP. In: Proc. of the Int. W’shop on Adaptive Text Extraction and Mining (2003)Google Scholar
  12. 12.
    Colomb, R.M.: Representation of Propositional Expert Systems as Decision Tables Technical Report TR-FB-89-05 Paper presented at 3rd Joint Aust. AI Conf. (AI 1989) Melbourne, Victoria, Australia, November 15-17 (1989)Google Scholar
  13. 13.
    Erdmann, M.: Formal concept analysis to learn from the sisyphus-III material. In: Proc. of 11th KA for KBS Workshop, KAW 1998, Banff, Canada (1998)Google Scholar
  14. 14.
    Eriksson, H., Fergerson, R.W., Shahar, Y., Musen, M.A.: Automatic Generation of Ontology Editors. In: KAW 1999, Banff, October 16-21 (1999)Google Scholar
  15. 15.
    Gaines, B.R.: Induction and Visualization of Rules with Exceptions. In: Boose, J., Gaines, B. (eds.) Proc.6th Banff AAAI KAW 1991, vol. 1, pp. 7.1-7.17 (1991)Google Scholar
  16. 16.
    Gaines, B.R., Shaw, M.L.G.: Knowledge Acquisition Tools Based on Personal Construct Psychology Knowledge Engineering Review  8(1), 49–85 (1993)Google Scholar
  17. 17.
    Ganter, B., Wille, R.: Formal Concept Analysis – Mathematical Foundations. Springer, Berlin (1999)zbMATHGoogle Scholar
  18. 18.
    Haase, P., Stojanovic, N., Volker, J., Sure, Y.: Personalized Information Retrieval in Bibster, a Semantics-Based Bibliographic Peer-to-Peer System. In: Proceedings of I-KNOW 2005, Graz, Austria, June 29 - July 1 (2005)Google Scholar
  19. 19.
    Kalfoglou, Y., Dasmahapatra, S., Chen-Burger, Y.-H.: FCA in Knowledge Technologies: Experiences and Opportunities. In: Eklund, P.W. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 252–260. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  20. 20.
    Kalyanpur, A., Parsia, B., Hendler, J., Golbeck, J.: SMORE - Semantic Markup, Ontology and RDF Editor. Technical Report (2001),
  21. 21.
    Katifori, V., Poggi, A., Scannapieco, M., Catarci, T., Ioannidis, Y.: OntoPIM: How to Rely on a Personal Ontology for Personal Information Management. In: Proc. of the 1st Workshop on The Semantic Desktop (2005)Google Scholar
  22. 22.
    Kelly, G.A.: The Psychology of Personal Constructs Norton, New York (1955)Google Scholar
  23. 23.
    Kent, R.E., Neuss, C.: Creating a Web Analysis and Visualization Environment. Computer Networks and ISDN Systems 28 (1995)Google Scholar
  24. 24.
    Kim, S., Hall, W., Keane, A.: Using Document Structures for Personal Ontologies and User Modeling. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds.) UM 2001. LNCS (LNAI), vol. 2109, pp. 240–242. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. 25.
    Kim, M., Compton, P.: Evolutionary Document Management and Retrieval for Specialized Domains on the Web. Int.l Jrnl of Human Computer Studies 60(2), 201–241 (2004)CrossRefGoogle Scholar
  26. 26.
    Maciaszek, L.A., Liong, B.L.: Practical Software Engineering - A Case Study Approach. Addison-Wesley, Reading (2005)Google Scholar
  27. 27.
    Moran, M., Mocan, A.: Towards Translating between XML and WSML based on mappings between XML Schema and an equivalent WSMO Ontology. In: Second WSMO Implementation Workshop (WIW 2005), Innsbruck, Austria (June 2005)Google Scholar
  28. 28.
    Ohmukai, I., Takeda, H., Hamasaki, M., Numa, K., Adachi, S.: Metadata-Driven Personal Knowledge Publishing. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 591–604. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  29. 29.
    Prediger, S., Stumme, G.: Theory-driven Logical Scaling: Conceptual Information Systems meet Description Logics. In: KRDB, pp. 46–49 (1999)Google Scholar
  30. 30.
    Richards, D.: An Evaluation of the Formal Concept Analysis Line Diagram. In: Poster Proc. AI 1998, Griffith University, Brisbane, Australia, July 13-17, pp. 109–120 (1998)Google Scholar
  31. 31.
    Richards, D.: Reconciling Conflicting Sources of Expertise: A Framework and an Illustration. In: Proc. of PKAW 2000, Sydney, December 11-14 (2000)Google Scholar
  32. 32.
    Richards, D.: Merging Individual Conceptual Models of Requirements. Special Issue on Model-Based Requirements Engineering for the Int. Jrnl of Requirements Engineering 8, 195–205 (2003)Google Scholar
  33. 33.
    Richards, D.: Addressing the Ontology Acquisition Bottleneck through Reverse Ontological Engineering. Jnl of Knowledge and Information Systems (KAIS) 6, 402–427 (2004)Google Scholar
  34. 34.
    Richards, D., Compton, P.: Uncovering the Conceptual Models in Ripple Down Rules. In: Delugach, H.S., Keeler, M.A., Searle, L., Lukose, D., Sowa, J.F. (eds.) ICCS 1997. LNCS, vol. 1257, pp. 198–212. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  35. 35.
    Richards, D., Malik, U.: Multi-Level Knowledge Discovery in Rule Bases. Applied Artificial Intelligence 17(3), 181–205 (2003)CrossRefGoogle Scholar
  36. 36.
    Shaw, M.L.G., Gaines, B.R.: Using Knowledge Acquisition Tools to Support Creative Processes. In: Proc. of the 6th KA for KBS Workshop, Banff, Canada (1991)Google Scholar
  37. 37.
    Spangenberg, N., Wolff, K.E.: Conceptual grid evaluation. In: Norbert, S., Wolff, K.E. (eds.) Classification and related methods of data analysis, pp. 577–580. North-Holland, Amsterdam (1988)Google Scholar
  38. 38.
    Stumme, G., Madche, A.: FCA-Merge: Bottom-up merging of ontologies. In: 7th Intl. Conf. on Artificial Intelligence (IJCAI 2001), Seattle, WA, pp. 225–230 (2001)Google Scholar
  39. 39.
    Tilley, T.: A Software Modelling Exercise using FCA. In: Ganter, B., de Moor, A., Lex, W. (eds.) ICCS 2003. LNCS, vol. 2746, Springer, Heidelberg (2003)Google Scholar
  40. 40.
    Wille, R.: Concept Lattices and Conceptual Knowledge Systems Computers Math. Applic. 23(6-9), 493–515 (1992)zbMATHGoogle Scholar
  41. 41.
    Wille, R.: Conceptual Graphs and Formal Concept Analysis. In: Delugach, H.S., Keeler, M.A., Searle, L., Lukose, D., Sowa, J.F. (eds.) ICCS 1997. LNCS, vol. 1257, pp. 290–303. Springer, Heidelberg (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Debbie Richards
    • 1
  1. 1.Computing Department, Division of Information and Communication SciencesMacquarie UniversityAustralia

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