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Intelligent Tools for Building a Scientific Information Platform pp 121–151Cite as

Methods and Tools for Ontology Building, Learning and Integration – Application in the SYNAT Project

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 390))

Abstract

One of the main goals of the SYNAT project is to equip scientific community with a knowledge-based infrastructure providing fast access to relevant scientific information. We have started building an experimental platform where different kinds of stored knowledge will be modeled with the use of ontologies, e.g. reference/system ontology, domain ontologies and auxiliary knowledge including lexical language ontology layers. In our platform we use system ontology defining “system domain” (a kind of meta knowledge) for the scientific community, covering concepts and activities related to the scientific life and domain ontologies dedicated to specific areas of science. Moreover the platform is supposed to include a wide range of tools for building and maintenance of ontologies throughout their life cycle as well as interoperation among the different introduced ontologies.

The paper makes a contribution to understanding semantically modeled knowledge and its incorporation into the SYNAT project. We present a review of ontology building, learning, and integration methods and their potential application in the project.

This work is supported by the National Centre for Research and Development (NCBiR) under Grant No. SP/I/1/77065/10 by the Strategic scientific research and experimental development program: ,,Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.

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References

  1. Gawrysiak, P., Ryżko, D.: Acquisition of scientific information from the Internet: The PASSIM Project Concept. In: Proc. of ICAART 2011, Rome (2011)

    Google Scholar 

  2. Web of Science, http://thomsonreuters.com/products_services/science/science_products/a-z/web_of_science/

  3. Scopus, http://www.scopus.com/home.url

  4. Google Scholar, http://scholar.google.com

  5. Etxebarria, G., Gomez-Uranga, M.: Use of Scopus and Google Scholar to measure social science production in four major Spanish universities. Scientometrics 82, 333–349 (2010)

    Article  Google Scholar 

  6. Microsoft Academic Search, http://academic.research.microsoft.com/

  7. Sheth, A., Ramakrishnan, C.: Semantic (Web) Technology In Action: Ontology Driven Information Systems for Search, Integration and Analysis. Bulletin of the Technical Committee on Data Engineering 26(4), 40–48 (2003)

    Google Scholar 

  8. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American (May 2001)

    Google Scholar 

  9. Della Valle, E., Cerizza, D., Celino, I., Estublier, J., Vega, G., Kerrigan, M., Ramírez, J., Villazon, B., Guarrera, P., Zhao, G., Monteleone, G.: SEEMP: An Semantic Interoperability Infrastructure for e-Government Services in the Employment Sector. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, pp. 220–234. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Project Boemie, financed by sixth framework programme UE (2006-2009), http://www.boemie.org/

  11. State of the Art on Ontology And Vocabulary Building & Maintenance Research And Applications Solutions for System and Domain Ontologies. Technical Report B12 in SYNAT project, Institute of Computer Science, WUT (March 2011)

    Google Scholar 

  12. Suárez-Figueroa, M.C., et al.: Revision and Extension of the NeOn Methodology for Building Contextualized Ontology Networks. NeOn Deliverable D5.4.3, NeOn Project (January 2010), http://www.neon-project.org

  13. Ye, J., Coyle, L., Dobson, S., Nixon, P.: Ontology-based models in pervasive computing systems. The Knowledge Engineering Review 22(04), 315–347 (2007)

    Article  Google Scholar 

  14. Protégé Editor, http://protege.stanford.edu

  15. NeOn Toolkit, http://neon-toolkit.org

  16. Gruninger, M., Fox, M.S.: Methodology for the design and evaluation of ontologies. In: Proc. Int. Joint Conf. AI Workshop on Basic Ontological Issues in Knowledge Sharing, Montreal (1995)

    Google Scholar 

  17. Fernández-López, M., Gómez-Pérez, A., Jurysto, N.: METHONOLOGY: From Ontological Art Towards Ontological Engineering. In: Spring Symposium on Ontological Engineering of AAAI, Stanford University, California, pp. 33–40 (1997)

    Google Scholar 

  18. Cimiano, P., Maedche, A., Staab, S., Voelker, J.: Ontology learning, Handbook on ontologies. Springer, Heidelberg (2009)

    Google Scholar 

  19. Gawrysiak, P., Protaziuk, G., Rybiński, H., Delteil, A.: Text onto miner – A semi automated ontology building system. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds.) Foundations of Intelligent Systems. LNCS (LNAI), vol. 4994, pp. 563–573. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  20. Cunningham, H., Humphreys, K., Gaizauskas, R.J., Wilks, Y.: GATE – A general architecture for text engineering. In: Proceedings of Applied Natural Language Processing (ANLP), pp. 29–30 (1997)

    Google Scholar 

  21. Cimiano, P.: Ontology Learning and Population from Text: Algorithms, Evaluation and Applications. Springer, Heidelberg (2006)

    Google Scholar 

  22. Buitelaar, P., Cimiano, G., Magnini, B.: Ontology Learning from Text: An Overview. In: Ontology learning from text: methods, evaluation and applications. IOS Press (2005)

    Google Scholar 

  23. Protaziuk, G., Kryszkiewicz, M., Rybiński, H., Delteil, A.: Discovering compound and proper nouns. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 505–515. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  24. Rybiński, H., Kryszkiewicz, M., Protaziuk, G., Jakubowski, A., Delteil, A.: Discovering Synonyms Based on Frequent Termsets. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 516–525. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  25. Rybinski, H., et al.: Text Mining Approach in Ontology Building and Maintenance Methodology – Project for FT, Final Report and Follow Up, WUT, ICS Rep. Warsaw (2007)

    Google Scholar 

  26. Cimiano, P., Völker, J.: Text2Onto. In: Montoyo, A., Muńoz, R., Métais, E. (eds.) NLDB 2005. LNCS, vol. 3513, pp. 227–238. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  27. Biemann, C.: Ontology Learning from Text – a Survey of Methods. In: LDV-Forum, vol. 20(2) (2005)

    Google Scholar 

  28. Brewster, C., Alani, H., Dasmahapatra, S., Wilks, Y.: Data-driven ontology evaluation. In: Proc. of the 4th International Conference on Language Resources and Evaluation, Lisbon (2004)

    Google Scholar 

  29. Völker, J., Vrandečić, D., Sure, Y.: Automatic evaluation of ontologies (AEON). In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 716–731. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  30. Haase, P., Völker, J.: Ontology learning and reasoning — dealing with uncertainty and inconsistency. In: da Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2005 - 2007. LNCS (LNAI), vol. 5327, pp. 366–384. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  31. Maedche, A., Volz, R.: The Text-To-Onto ontology extraction and maintenance system. In: Workshop on Integrating Data Mining and Knowledge Management, collocated with the 1st International Conference on Data Mining (2001)

    Google Scholar 

  32. Buitelaar, P., Olejnik, D., Sintek, M.: A Protégé plug-in for ontology extraction from text based on linguistic analysis. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 31–44. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  33. Velardi, P., Navigli, R., Cuchiarelli, A., Neri, F.: Evaluation of OntoLearn, a methodology for automatic population of domain ontologies. In: Buitelaar, P., Cimiano, P., Magnini, B. (eds.) Ontology Learning from Text: Methods, Applications and Evaluation, Frontiers in Artificial Intelligence and Applications, vol. 123, pp. 92–106. IOS Press (2005)

    Google Scholar 

  34. Pinto, H.S., Gomez-Perez, A., Martins, J.P.: Some issues on ontology integration. In: Proceedings of the IJCAI-1999 Workshop on Ontologies and Problem-Solving methods (KRR5), Stockholm, Sweden (1999)

    Google Scholar 

  35. INTEROP, Ontology Interoperability, State of the Art Report. WP8ST3 Deliverable (2004)

    Google Scholar 

  36. de Bruijn, J., Ehrig, M., Feier, C., Martin-Recuerda, F., Scharffe, F., Weiten, M.: Ontology Mediation, Merging, and Aligning. John Wiley & Sons, Ltd (2006)

    Google Scholar 

  37. Ehrig, M.: Ontology Alignment Bridging the Semantic Gap. Springer, Heidelberg (2007)

    Google Scholar 

  38. Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. The Knowledge Engineering Review Journal (KER) 18(1), 1–31 (2003)

    Article  Google Scholar 

  39. Stumme, G., Maedche, A.: Ontology Merging for Federated Ontologies on the Semantic Web. In: Proceedings of the International Workshop for Foundations of Models for Information Integration (FMII-2001), Viterbo, Italy (September 2001)

    Google Scholar 

  40. Noy, N.F., Musen, M.: PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: Proceedings of the 17th National Conference on Artificial Intelligence (AAAI 2000), Austin, TX, USA (2000)

    Google Scholar 

  41. Doan, A., Madhaven, J., Domingos, P., Halevy, A.: Ontology matching: A machine learning approach. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies in Information Systems. Springer, Heidelberg (2004)

    Google Scholar 

  42. Calvanese, D., De Giacomo, G., Lenzerini, M.: A framework for ontology integration. In: Proceedings of the 1st Internationally Semantic Web Working Symposium (SWWS), Stanford, CA, USA (2001)

    Google Scholar 

  43. Maedche, A., Motik, B., Silva, N., Volz, R.: MAFRA – A mApping fRAmework for distributed ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 235–250. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  44. Kalfoglou, Y., Schorlemmer, M.: IF-Map: an ontology mapping method based on information flow theory. Journal on Data Semantics 1(1) (October 2003)

    Google Scholar 

  45. Barwise, J., Seligman, J.: Information Flow: The Logic of Distributed Systems. Cambridge University Press (1997)

    Google Scholar 

  46. Castano, S., Ferrara, A., Montanelli, S.: Matching Ontologies in Open Networked Systems: Techniques and Applications. In: Spaccapietra, S., Atzeni, P., Chu, W.W., Catarci, T., Sycara, K. (eds.) Journal on Data Semantics V. LNCS, vol. 3870, pp. 25–63. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  47. Udrea, O., Getoor, L., Miller, R.J.: Leveraging data and structure in ontology integration. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of data, SIGMOD 2007 (2007)

    Google Scholar 

  48. Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and application of a metric on semantic nets. IEEE Transactions on Systems, Man and Cybernetics (1989)

    Google Scholar 

  49. Cho, M., Kim, H., Kim, P.: A new method for ontology merging based on concept using wordnet. In: The 8th International Conference on Advanced Communication Technology, ICACT 2006, vol. 3 (2006)

    Google Scholar 

  50. Hakimpour, F., Geppert, A.: Resolving Semantic Heterogeneity in Schema Integration: an Ontology Based Approach. In: Proc. of the 2nd Intl. Conf. on Formal Ontology in Information Systems. ACM Press, New York (2001)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warszawa, Poland

    Anna Wróblewska, Robert Bembenik, Grzegorz Protaziuk & Henryk Rybiński

  2. Institute of Biocybernetics and Bioengineering, Trojdena 4, 02-109, Warszawa, Poland

    Teresa Podsiadły-Marczykowska

Authors
  1. Anna Wróblewska
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  2. Teresa Podsiadły-Marczykowska
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  3. Robert Bembenik
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  4. Grzegorz Protaziuk
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  5. Henryk Rybiński
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Correspondence to Anna Wróblewska .

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Editors and Affiliations

  1. Institute of Computer Science, Faculty of Electronics and Information, Warsaw University of Technology, Ul. Nowowiejska 15/19, Warsaw, 00-665, Poland

    Robert Bembenik

  2. Institute of Computer Science, Faculty of Electronics and Information, Warsaw University of Technology, Ul. Nowowiejska 15/19, Warsaw, 00-665, Poland

    Lukasz Skonieczny

  3. Institute of Computer Science, Faculty of Computer Science and, Warsaw University of Technology, ul. Zolnierska 49, Warsaw, 00-665, Poland

    Henryk Rybiński

  4. , Interdisciplinary Centre for Mathematica, University of Warsaw, Ul. Pawińskiego 5a, Warsaw, 02-106, Poland

    Marek Niezgodka

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Wróblewska, A., Podsiadły-Marczykowska, T., Bembenik, R., Protaziuk, G., Rybiński, H. (2012). Methods and Tools for Ontology Building, Learning and Integration – Application in the SYNAT Project. In: Bembenik, R., Skonieczny, L., Rybiński, H., Niezgodka, M. (eds) Intelligent Tools for Building a Scientific Information Platform. Studies in Computational Intelligence, vol 390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24809-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-24809-2_9

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