Fuzzy Ontology-based Semantic Integration of Heterogeneous Data Sources in the Domain of Watershed Analysis
Resumo
In environmental research, data integration plays an important role given the increasing availability of heterogeneous data sources for specific features, such as soil type, climate, geographic location and so on. However, some of those features have inherently imprecise relationships and the lack of a suitable semantic model can be a major obstacle to its effective integration. In this context, this paper presents a semantic data integration system based on a fuzzy ontology, capable of perform query expansions based on imprecise aspects of real phenomena. We executed a real experience in the domain of watershed analysis. Consequently, watershed researchers obtained an homogeneous view of the data sources and more effective responses to their queries.Referências
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Madin, J. S., Bowers, S., Schildhauer, M. P., and Jones, M. B. (2008). Advancing ecological research with ontologies. Trends in Ecology & Evolution, 23(3):159–168.
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Rahm, E. and Bernstein, P. A. (2001). A survey of approaches to automatic schema matching. The VLDB Journal, 10(4):334–350.
Smith, M. K., Welty, C., and Mcguiness, D. L. (2004). Owl web ontology language guide. [link]. Access date: Jan. 2006.
Stoilos, G., Simou, N., Stamou, G., and Kollias, S. (2006). Uncertainty and the semantic web. IEEE Intelligent Systems, 21(5):84–87.
Vidal, V. M., Sacramento, E. R., Macêdo, J. A., and Casanova, M. A. (2009). An ontology-based framework for geographic data integration. In Proc. of the ER 2009 Workshops, pages 337–346, Berlin, Heidelberg. Springer-Verlag.
Yaguinuma, C. A., Biajiz, M., and Santos, M. T. P. (2007a). Sistema foque para expansão semântica de consultas baseada em ontologias difusas. In XXII Brazilian Symposium on Databases, pages 208–222, João Pessoa, PB. [in portuguese].
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Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3):338–353.
Carroll, J. J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., and Wilkinson, K. (2004). Jena: implementing the semantic web recommendations. In Int. WWW Conf., pages 74–83, New York, NY, USA. ACM.
Doan, A. and Halevy, A. Y. (2005). Semantic-integration research in the database community. AI Mag., 26(1):83–94.
Dupas, F. A., Souza, A. T. S., Tundisi, J. G., Tundisi, T. M., and Rohm, S. A. (2006). Indicadores ambientais para planejamento e gestão de bacias hidrográficas. In Eutrofização na América do Sul: causas, conseqüências e tecnologias para gerenciamento e controle, pages 491–506. IIE, São Carlos, SP [in portuguese].
Fonseca, F. T., Egenhofer, M. J., Agouris, P., and Câmara, G. (2002). Using ontologies for integrated geographic information systems. Transactions in GIS, 6(3):231–257.
Gruber, T. R. (2009). Ontology. In Encyclopedia of Database Systems, pages 1963–1965. Springer.
Halevy, A. (2009). Information integration. In Encyclopedia of Database Systems, pages 1490–1496. Springer.
Latre-Abadía, M. Á., Lacasta, J., Mojica, E., Nogueras-Iso, J., and Zarazaga-Soria, F. J. (2009). An approach to facilitate the integration of hydrological data by means of ontologies and multilingual thesauri. In AGILE Conf., pages 155–171.
Lenz, R., Beyer, M., and Kuhn, K. A. (2007). Semantic integration in healthcare networks. Int. Journal of Medical Informatics, 76(2-3):201 – 207. Connecting Medical Informatics and Bio-Informatics - MIE 2005.
Lopez, M., Gomez-Perez, A., Sierra, J., and Sierra, A. (1999). Building a chemical ontology using methontology and the ontology design environment. IEEE Intelligent Systems and their Applications, 14(1):37–46.
Lukasiewicz, T. and Straccia, U. (2008). Managing uncertainty and vagueness in description logics for the semantic web. Journal of Web Semantics, 6(4):291–308.
Madin, J. S., Bowers, S., Schildhauer, M. P., and Jones, M. B. (2008). Advancing ecological research with ontologies. Trends in Ecology & Evolution, 23(3):159–168.
Noy, N. F. (2004). Semantic integration: a survey of ontology-based approaches. SIG-MOD Record, 33(4):65–70.
OGC (2008). Ogc reference model - ogc 08-062r4. [link]. Access date: Dec. 2008.
Rahm, E. and Bernstein, P. A. (2001). A survey of approaches to automatic schema matching. The VLDB Journal, 10(4):334–350.
Smith, M. K., Welty, C., and Mcguiness, D. L. (2004). Owl web ontology language guide. [link]. Access date: Jan. 2006.
Stoilos, G., Simou, N., Stamou, G., and Kollias, S. (2006). Uncertainty and the semantic web. IEEE Intelligent Systems, 21(5):84–87.
Vidal, V. M., Sacramento, E. R., Macêdo, J. A., and Casanova, M. A. (2009). An ontology-based framework for geographic data integration. In Proc. of the ER 2009 Workshops, pages 337–346, Berlin, Heidelberg. Springer-Verlag.
Yaguinuma, C. A., Biajiz, M., and Santos, M. T. P. (2007a). Sistema foque para expansão semântica de consultas baseada em ontologias difusas. In XXII Brazilian Symposium on Databases, pages 208–222, João Pessoa, PB. [in portuguese].
Yaguinuma, C. A., Santos, M. T. P., and Biajiz, M. (2007b). Meta-ontologia difusa para representação de informações imprecisas em ontologias. In Workshop on Ontologies and Metamodeling in Software and Data Engineering, pages 57–67, João Pessoa, PB. SBC. [in portuguese].
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3):338–353.
Publicado
20/07/2010
Como Citar
FERRAZ, Vinícius R. T.; AFONSO, Gustavo F.; YAGUINUMA, Cristiane; BORGES, Sérgio; SANTOS, Marilde T. P..
Fuzzy Ontology-based Semantic Integration of Heterogeneous Data Sources in the Domain of Watershed Analysis. In: WORKSHOP DE COMPUTAÇÃO APLICADA À GESTÃO DO MEIO AMBIENTE E RECURSOS NATURAIS (WCAMA), 2. , 2010, Belo Horizonte/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2010
.
p. 565-574.
ISSN 2595-6124.
