Developing Ontologies within Decentralised Settings

  • Alexander Garcia
  • Kieran O’Neill
  • Leyla Jael Garcia
  • Phillip Lord
  • Robert Stevens
  • Oscar Corcho
  • Frank Gibson
Chapter
Part of the Annals of Information Systems book series (AOIS, volume 11)

Abstract

This chapter addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This chapter presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralised settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering.

References

  1. 1.
    Editorial: Compete, collaborate, compel. Nat Genet 39(8) (Aug 2007) 931Google Scholar
  2. 2.
    Julian, S., J. Rector, A.: The state of multi-user ontology engineering. In: Proceedings of the 2nd International Workshop on Modular Ontologies, Canada (2007)Google Scholar
  3. 3.
    Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L., Eilbeck, K., Lewis, S.: The obo foundry: Coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11) (2007) 1251–1255CrossRefGoogle Scholar
  4. 4.
    Gruber, T.: Collective knowledge systems: Where social web meets the semantic web. In: Proceedings of the 5th International Semantic Web Conference, Athens, GA, USA (2006)Google Scholar
  5. 5.
    Tudorache, T., Noy, N.: Collaborative protege. In: Social and Collaborative Construction of Structured Knowledge, Proceedings of 16th International WWW Conference, Alberta, Canada (2007)Google Scholar
  6. 6.
    Feigenbaum, E., McCorduck, P.: The Fifth Generation. Addison-Wesley, Reading, MA (1983)Google Scholar
  7. 7.
    Kendal, S., Creen, M.: An Introduction to Knowledge Engineering. Springer, New York, NY (2007)Google Scholar
  8. 8.
    Sowa, J.: Knowledge Representation: Logical, Philosophical, and Computational Foundation. Brooks Cole Publishing, Pacific Grove, CA (2000)Google Scholar
  9. 9.
    Sure, Y.: Methodology, Tools and Case Studies for Ontology Based Knowledge Management. PhD Thesis, Universitat Fridericiana zu Karlsruhe (2003)Google Scholar
  10. 10.
    Uschold, M., King, M.: Towards methodology for building ontologies. In: Workshop on Basic Ontological Issues in Knowledge Sharing, Held in Conjunction with IJCAI-95. Cambridge, UK (1995)Google Scholar
  11. 11.
    Gruninger, M., Fox, M.S.: The role of competency questions in enterprise engineering. In: Proceedings of the IFIP WG5.7 Workshop on Benchmarking – Theory and Practice, Trondheim, Norway (1994)Google Scholar
  12. 12.
    Bernaras, A., Laresgoiti, I., Corera, J.: Building and reusing ontologies for electrical network applications, 12th European Conference on Artificial Intelligence ECAI. Wiley, Budapest, Hungary (1996) 298–302Google Scholar
  13. 13.
    Fernadez-Lopez, M., Perez, A.G., Pazos, S.J., Pazos, S.A.: Building a chemical ontology using methontology and the ontology design environment. IEEE Intelligent Systems and Their Applications 14 (1999) 37–46CrossRefGoogle Scholar
  14. 14.
    Swartout, B., Ramesh, P., Knight, K., Russ, T.: Toward distributed use of largescale ontologies. In: Symposium on Ontological Engineering of AAAI, Stanford, California (1997)Google Scholar
  15. 15.
    Pinto, H.S., Staab, S., Tempich, C.: Diligent: Towards a fine-grained methodology for distributed, loosely-controlled and evolving engineering of ontologies. In: European Conference on Artificial Intelligence, Valencia, Spain (2004) 393–397Google Scholar
  16. 16.
    Vrandecic, D., Pinto, H.S., Sure, Y., Tempich, C.: The diligent knowledge processes. Journal of Knowledge Management 9(5) (2005) 85–96CrossRefGoogle Scholar
  17. 17.
    Garcia, C.A., Rocca-Serra, P., Stevens, R., Taylor, C., Nashar, K., Ragan, M.A., Sansone, S.: The use of concept maps during knowledge elicitation in ontology development processes – the nutrigenomics use case. BMC Bioinformatics 7 (2006) 267CrossRefGoogle Scholar
  18. 18.
    Mirzaee, V.: An Ontological Approach to Representing Historical Knowledge. MSc Thesis. PhD Thesis, Department of Electrical and Computer Engineering, University of British Columbia (2004)Google Scholar
  19. 19.
    Moreira, D., Musen, M.A.: Obo to owl: A protege owl tab to read/save obo ontologies. Bioinformatics 23(14) (2007) 1868–1870CrossRefGoogle Scholar
  20. 20.
    Sathiamurthy, M., Peters, B., Bui, H.H., Sidney, J., Mokili, J., Wilson S.S., Fleri, W., McGuinness, D., Bourne, P., Sette, A.: An ontology for immune epitopes: Application to the design of a broad scope database of immune reactivities. BMC Immunology 1(2) (2005)Google Scholar
  21. 21.
    Bada, M., Stevens, R., Goble, C., Gil, Y., Ashbourner, M., Blake, J., Cherry, J., Harris, M., Lewis, S.: A short study on the success of the geneontology. Journal of Web Semantics 1 (2004) 235–240CrossRefGoogle Scholar
  22. 22.
    Berners-Lee, T., Hendler, J., Lassila, O., et al.: The semantic web. Scientific American 284(5) (2001) 28–37CrossRefGoogle Scholar
  23. 23.
    Shadbolt, N., Berners-Lee, T., Hall, W.: The semantic web revisited. IEEE Intelligent Systems (2006) 96–101Google Scholar
  24. 24.
    Degtyarenko, K., Matos, P., Ennis, M., Hastings, J., Zbinden, M., McNaught, A., Alcantara, R., Darsow, M., Guedj, M., Ashburner, M.: ChEBI: A database and ontology for chemical entities of biological interest. Nucleic Acids Research (2007)Google Scholar
  25. 25.
    Smith, B., Kumar, A., Bittner, T.: Basic formal ontology for bioinformatics. Retrieved Jul. 12, 2010 from http://www.uni-leipzig.de/~akumar/JAIS.pdf Journal of Information Systems (2005) 1–16
  26. 26.
    Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L.: Sweetening Ontologies with Dolce. Lecture Notes in Computer Science (2002) 166–181Google Scholar
  27. 27.
    Herre, H., Heller, B., Burek, P., Hoehndorf, R., Loebe, F., Michalek, H.: General Formal Ontology (GFO) – A Foundational Ontology Integrating Objects and Processes. Onto-Med Report 8Google Scholar
  28. 28.
    Eden, H.A., Hirshfeld, Y.: Principles in formal specification of object oriented design and architecture. In: Proceedings of the 2001 Conference of the Centre for Advanced Studies on Collaborative Research, Toronto, Canada, IBM Press (2001)Google Scholar
  29. 29.
    Pressman, S.R.: Software Engineering, A Practitioners Approach. 5th edn. McGraw-Hill Series in Computer Science. Thomas Casson, New York, NY (2001)Google Scholar
  30. 30.
    Martin, J.: Rapid Application Development. Prentice-Hall, Englewood Cliffs, NJ (1991)Google Scholar
  31. 31.
    Gilb, T.: Evolutionary project management: Multiple performance, quality and cost metrics for early and continuous stakeholder value delivery. In: International Conference on Enterprise Information Systems, Porto, Portugal (2004)Google Scholar
  32. 32.
    Perez, A.G.: Some Ideas and Examples to Evaluate Ontologies. Technical Report, Stanford University (1994a)Google Scholar
  33. 33.
    Gilb, T.: Principles of Software Engineering Management. Addison-Wesley Longman, Boston, MA (1988)Google Scholar
  34. 34.
    Garcia, A.: Developing Ontologies Within the Biomedical Domain. PhD, University of Queensland (2007)Google Scholar
  35. 35.
    Fernandez, M.: Overview of methodologies for building ontologies. In: Proceedings of the IJCAI-99 Workshop on Ontologies and Problem-Solving Methods(KRR5), Stockholm, Sweden (1999)Google Scholar
  36. 36.
    Corcho, O., Fernadez-Lopez, M., Gomez-Perez, A.: Methodologies, tools, and languages for building ontologies. Where is their meeting point? Data and Knowledge Engineering 46(1) (2003) 41–64CrossRefGoogle Scholar
  37. 37.
    Fernandez, M., Gomez-Perez, A., Juristo, N.: Methontology: From ontological art to ontological engineering. In: Workshop on Ontological Engineering. Spring Symposium Series. AAAI97, Stanford (1997)Google Scholar
  38. 38.
    Good, B., Tranfield, E.M., Tan, P.C., Shehata, M., Singhera, G., Gosselink, J., Okon, E.B., Wilkinson, M.: Fast, cheap, and out of control: A zero curation model for ontology development. In: Pacific Symposium on Biocomputing. Maui, Hawaii, USA. (2006)Google Scholar
  39. 39.
    Van Heijst, G., Van der Spek, R., Kruizinga, E.: Organizing corporate memories. In: Tenth Knowledge Acquisition for Knowledge-Based Systems Workshop (KAW’96). (1996)Google Scholar
  40. 40.
    Mizoguchi, R., Vanwelkenhuysen, J., Ikeda, M.: Task ontology for reuse of problem solving knowledge. In: Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing (KBKS’95). (1995) 46–57Google Scholar
  41. 41.
    Uschold, M., Gruninger, M.: Ontologies: Principles, methods and applications. Knowledge Engineering Review 11 (1996) 93–136CrossRefGoogle Scholar
  42. 42.
    Fernadez-Lopez, M., Gomez-Perez, A.: Overview and analysis of methodologies for building ontologies. The Knowledge Engineering Review 17(2) (2002) 129–156Google Scholar
  43. 43.
    Lakoff, G.: Women, Fire, and Dangerous Things: What Categories Reveal About the Mind. Chicago University Press, Chicago (1987)Google Scholar
  44. 44.
    Cooke, N.: Varieties of knowledge elicitation techniques. International Journal of Human-Computer Studies 41 (1994) 801–849CrossRefGoogle Scholar
  45. 45.
    Arpirez, J., Corcho, O., Fernadez-Lopez, M., Gomez-Perez, A.: Webode in a nutshell. AI Magazine 24(3) (2003) 37–47Google Scholar
  46. 46.
    Hinchcliffe, D.: Dion hinchcliffe’s web 2.0 blog web 2.0 (2008)Google Scholar
  47. 47.
    Stoeckert, C.J., Parkinson, H.: The mged ontology: A framework for describing functional genomics experiments. Comparative and Functional Genomics 4 (2003) 127–132CrossRefGoogle Scholar
  48. 48.
    Perez, A.G., Juristo, N., Pazos, J.: Evaluation and assessment of knowledge sharing technology. In Mars, N. (ed.) Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing(KBK95), IOS Press, Amsterdam, The Netherlands, (1995) 289–296Google Scholar
  49. 49.
    Pinto, H.S., Martins, P. J.: Ontologies: How can they be built? Knowledge and Information Systems 6 (2004) 441–463CrossRefGoogle Scholar
  50. 50.
    IEEE: IEEE standard for software quality assurance plans (1998)Google Scholar
  51. 51.
    Greenwood, E.: Metodologia de la investigacion social. Paidos, Buenos Aires (1973)Google Scholar
  52. 52.
    Gomez-Perez, A., Fernandez-Lopez, M., Corcho, O.: Ontological Engineering. Springer, London (2004)Google Scholar
  53. 53.
    IEEE: IEEE standard for developing software life cycle processes (1996)Google Scholar
  54. 54.
    Mooney, S.D., Baenziger, P.H.: Extensible open source content management systems and frameworks: A solution for many needs of a bioinformatics group. Brief Bioinform 9(1) (Jan 2008) 69–74CrossRefGoogle Scholar
  55. 55.
    Stevens, R., Goble, C., Bechhofer, S.: Ontology-based knowledge representation for bioinformatics. Briefings in Bioinformatics (2000) 398–414Google Scholar
  56. 56.
    Gaines, B.R., Shaw, M.L.Q.: Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review 8(1) (1993) 49–85CrossRefGoogle Scholar
  57. 57.
    Rubin, D., Lewis, S., Mungall, C., Misra, S., Westerfield, M., Ashburner, M., Sim, I., Chute, C., Solbrig, H., Storey, M., Smith, B., Day-Richter, J., Noy, N., Musen, M.: National center for biomedical ontology: Advancing biomedicine through structured organization of scientific knowledge. OMICS 10(2) (2006) 85–98CrossRefGoogle Scholar
  58. 58.
    Cote, R., Jones, P., Apweiler, R., Hermjakob, H.: The ontology lookup service, a lightweight cross-platform tool for controlled vocabulary queries. BMC Bioinformatics 7(97) (2006)Google Scholar
  59. 59.
    Noy, N.F., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology. Technical Report, Stanford University (2001)Google Scholar
  60. 60.
    Perez, A.G., Fernadez-Lopez, M., Corcho, O.: Ontological Engineering. Computer Sciences. Springer. London (2004)Google Scholar
  61. 61.
    Haarslev, V., Mller, R.: Racer: A core inference engine for the semantic web. In: Proceedings of the 2nd International Workshop on Evaluation of Ontology-based Tools (EON2003), Sanibel Island, Florida, USA (2003) 27–36Google Scholar
  62. 62.
    Sirin, E., Parsia, B., Cuenca-Grau, B., Kalyanpur, A., Katz, Y.: Pellet: A practical owl-dl resoner. Journal of Web Semantics 5(2) (2007)Google Scholar
  63. 63.
    Garcia, A., Zhang, Z., Rajapakse, M., Baker, C., Tang, S.: Capturing and modeling neuro-radiological knowledge on a community basis: The head injury scenario. In: Health and Life Sciences workshop at the WWW2008. (2008)Google Scholar
  64. 64.
    Orchard, S., Hermjakob, H., Apweiler, R.: The proteomics standards initiative. Proteomics 3(7) (2003) 1374–1376CrossRefGoogle Scholar
  65. 65.
    Taylor, C., Paton, N., Lilley, K., Binz, P., Julian, R.J., Jones, A., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E., Dunn, M., Heck, A., Leitner, A., Macht, M., Mann, M., Martens, L., Neubert, T., Patterson, S., Ping, P., Seymour, S., Souda, P., Tsugita, A., Vandekerckhove, J., Vondriska, T., Whitelegge, J., Wilkins, M., Xenarios, I., Yates, J.R., Hermjakob, H.: The minimum information about a proteomics experiment (miape). Nature Biotechnology 25(8) (2007) 887–93CrossRefGoogle Scholar
  66. 66.
    Jones, A., Gibson, F.: An update on data standards for gel electrophoresis. Proteomics 7(Suppl 1) (2007) 35–40CrossRefGoogle Scholar
  67. 67.
    Dagnino, A.: Coordination of hardware manufacturing and software development lifecycles for integrated systems development. In: IEEE International Conference on Systems, Man, and Cybernetics 3 (2001) 850–1855Google Scholar
  68. 68.
    Boehm, B.: A spiral model of software development and enhancement. ACM SIGSOFT Software Engineering Notes 11(4) (1986) 14–24CrossRefGoogle Scholar
  69. 69.
    McDermid, J., Rook, P.: Software development process models. In: Software Engineer’s Reference Book. CRC Press, Boca Raton, FL (1993) 15–28Google Scholar
  70. 70.
    Larman, C., Basili, R., V.: Iterative and incremental development: A brief history. Computer, IEEE Computer Society 36 (2003) 47–56CrossRefGoogle Scholar
  71. 71.
    May, L, E., Zimmer, A, B.: The evolutionary development model for software. HP Journal (1996) Retrieved Jul. 12, 2010 http://www.hpl.hp.com/hpjournal/96aug/aug96a4.pdf
  72. 72.
    Fox, M.S.: The tove project: A common-sense model of the enterprise systems. In: Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. (1992)Google Scholar
  73. 73.
    Arpirez, J., Corcho, O., Fernadez-Lopez, M., Gomez-Perez, A.: Webode in a nutshell. AI Magazine 24(3) (2003) 37–47Google Scholar
  74. 74.
    Fellbaum, C.: WordNet, An Electronic Lexical Database. The MIT Press, Cambridge, MA (2000)Google Scholar
  75. 75.
    Knight, K., Luk, S.: Building a large-scale knowledge base for machine translation. In: Proceedings of the National Conference on Artificial Intelligence. Wiley, New York (1994) 773–773Google Scholar
  76. 76.
    Knight, K., Chander, I.: Automated postediting of documents. In: Proceedings of the 12th National Conference on Artificial Intelligence (vol. 1) Table of Contents, American Association for Artificial Intelligence Menlo Park, CA, USA (1994) 779–784Google Scholar
  77. 77.
    Knight, K., Graehl, J.: Machine transliteration. Computational Linguistics 24(4) (1998) 599–612Google Scholar
  78. 78.
    Valente, A., Russ, T., MacGregor, R., Swartout, W.: Building and (Re) Using an Ontology of Air Campaign Planning. IEEE Intelligent Systems (1999) 27–36Google Scholar
  79. 79.
    Tempich, C., Pinto, H., Sure, Y., Vrandecic, D., Casellas, N., Casanovas, P.: Evaluating diligent ontology engineering in a legal case study. In: XXII World Congress of Philosophy of Law and Social Philosophy, IVR2005 Granada, May 24th, 29th (2005)Google Scholar
  80. 80.
    Garcia, A.: Developing Ontologies in the Biological Domain. PhD Thesis, University of Queensland (2007)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Alexander Garcia
    • 1
  • Kieran O’Neill
    • 2
  • Leyla Jael Garcia
    • 3
  • Phillip Lord
    • 4
  • Robert Stevens
    • 5
  • Oscar Corcho
    • 6
  • Frank Gibson
    • 7
  1. 1.University of BremenBremenGermany
  2. 2.Terry Fox LaboratoryVancouverCanada
  3. 3.E-Business and Web Science Research GroupBundeswehr UniversityMunichGermany
  4. 4.School of Computing ScienceNewcastle UniversityNewcastle upon TyneUK
  5. 5.Department of Computer ScienceUniversity of ManchesterManchesterUK
  6. 6.Ontology Engineering Group, Departamento de Inteligencia Artificial, Facultad de InformticaUniversidad Politecnica de MadridMadridSpain
  7. 7.Abcam plcCambridgeUK

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