Abstract
Ontology has become increasingly important to software systems. The aim of ontology learning is to ease one of the major problems in ontology engineering, i.e. the cost of ontology construction. Much of the effort within the ontology learning community has focused on learning from text collections. However, environmental domains often deal with numerical measurement data and, therefore, rely on methods and tools for learning beyond text. We discuss this characteristic using two relations of an ontology for lakes. Specifically, we learn a threshold value from numerical measurement data for ontological rules that classify lakes according to nutrient status. We describe our methodology, highlight the cyclical interaction between data mining and ontologies, and note that the numerical value for lake nutrient status is specific to a spatial and temporal context. The use case suggests that learning from numerical measurement data is a research area relevant to environmental software systems.
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Ashburner, M., Ball, C., Blake, J., Botstein, D., Butler, H., Cherry, J., Davis, A., Dolinski, K., Dwight, S., Eppig, J., Harris, M., Hill, D., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J., Richardson, J., Ringwald, M., Rubin, G., Sherlock, G.: Gene ontology: Tool for the unification of biology. Nature Genetics 25(1), 25–29 (2000)
Boeckmann, B., Bairoch, A., Apweiler, R., Blatter, M.C., Estreicher, A., Gasteiger, E., Martin, M., Michoud, K., O’Donovan, C., Phan, I., Pilbout, S., Schneider, M.: The Swiss-Prot Protein Knowledgebase and its supplement TrEMBL. Nucleic Acids Res. 31, 365–370 (2003)
Carroll, J.J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., Wilkinson, K.: Jena: Implementing the Semantic Web Recommendations. Tech. Rep. HPL-2003-146, HP Laboratories, Bristol, UK (2003)
Gruber, T.: A translation approach to portable ontology specifications. Knowledge Acquisition 5(2), 199–220 (1993)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update. SIGKDD Explorations 11 (2009)
Henson, C.A., Pschorr, J.K., Sheth, A.P., Thirunarayan, K.: SemSOS: Semantic Sensor Observation Service. In: Proc. of the 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore, MD (May 2009)
Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American (2001)
MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press (1967)
Manola, F., Miller, E.: RDF Primer. Tech. Rep. W3C Recommendation, W3C (2004)
Naumann, E.: Nagra synpunker angaende planktons okologi. Med sarskild hansyn till fytoplankton. Svensk Bot. Tidskr. 13, 129–158 (1919)
Nigro, H.O., Císaro, S.E.G., Xodo, D.H.: Data mining with ontologies: Implementations, findings, and frameworks. Information Science Reference (an imprint of IGI Global) (2008)
Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF. Tech. Rep. W3C Recommendation, W3C (2008)
Shamsfard, M., Barforoush, A.: The state of the art in ontology learning: A framework for comparison. Knowledge Engineering Review 18(4), 293–316 (2003)
Sydenham, P.H.: Handbook of Measurement Science: Volume 1 Theoretical Fundamentals. John Wiley & Sons, Chichester (1982)
Thienemann, A.: Physikalische und chemische Untersuchungen in den Maaren der Eifel. Verh. Naturh. Ver. preuss. Rheinl. u. Westfalens 71, 281–389 (1915)
Villa, F., Athanasiadis, I., Rizzoli, A.: Modelling with knowledge: A review of emerging semantic approaches to environmental modelling. Environmental Modelling and Software 24(5), 577–587 (2009)
Williams, R., Martinez, N., Golbeck, J.: Ontologies for ecoinformatics. Web Semantics 4(4), 237–242 (2006)
Zafar, A.: Taxonomy of lakes. Hydrobiologia 13(3), 287–299 (1959)
Zhou, L.: Ontology learning: State of the art and open issues. Information Technology and Management 8(3), 241–252 (2007)
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Stocker, M., Rönkkö, M., Villa, F., Kolehmainen, M. (2011). The Relevance of Measurement Data in Environmental Ontology Learning. In: Hřebíček, J., Schimak, G., Denzer, R. (eds) Environmental Software Systems. Frameworks of eEnvironment. ISESS 2011. IFIP Advances in Information and Communication Technology, vol 359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22285-6_48
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DOI: https://doi.org/10.1007/978-3-642-22285-6_48
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