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Ontology Reasoning with Large Data Repositories

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Ontology Management

Part of the book series: Computing for Human Experience ((ADSW,volume 7))

Reasoning with large amounts of data together with ontological knowledge is becoming a pertinent issue. In this chapter, we will give an overviewof wellknown ontology repositories, including native stores and database based stores, and highlight strengths and limitations of each store. We take Minerva as an example to analyze ontology storage in databases in depth, as well as to discuss efficient indexes for scaling up ontology repositories. We then discuss a scalable reasoning method for handling expressive ontologies, as well as summarize other similar approaches. We will subsequently delve into the details of one particular ontology language based on Description Logics called WSML-DL and show that reasoning with this language can be done by a transformation from WSML-DL to OWL DL and support all main DL-specific reasoning tasks. Finally, we illustrate reasoning and its relevance by showing a reasoning example in a practical business context by presenting the Semantic Business Process Repository (SBPR) for systemical management of semantic business process models. As part of this, we analyze the main requirements on a such a repository. We then compare different approaches for storage mechanisms for this purpose and show how a RDBMS in combination with the IRIS inference engine provides a suitable solution that deals well with the expressiveness of the query language and the required reasoning capabilities even for large amounts of instance data.

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Authors and Affiliations

  1. Digital Enterprise Research Institute, University of Innsbruck, Technikerstr. 21a, A-6020, Innsbruck, Austria

    Stijn Heymans, Darko Anicic, Nathalie Steinmetz, Cristina Feier & Graham Hench

  2. IBM China Research Lab, Building 19 Zhongguancun Software Park, 100094, Bei**g, China

    Li Ma, Yue Pan, **g Mei & Uwe Keller

  3. Institute of Architecture of Application Systems (IAAS), University of Stuttgart, Stuttgart, Germany

    Zhilei Ma & Branimir Wetzstein

  4. IBM Watson Research Center, 704, 10598, Yorktown Heights, NY, USA

    Achille Fokoue, Aditya Kalyanpur, Aaron Kershenbaum, Edith Schonberg & Kavitha Srinivas

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  1. Stijn Heymans
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  2. Li Ma
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  3. Darko Anicic
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  4. Zhilei Ma
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  6. Yue Pan
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  7. **g Mei
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  8. Achille Fokoue
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  10. Aaron Kershenbaum
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  13. Cristina Feier
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  14. Graham Hench
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  15. Branimir Wetzstein
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  16. Uwe Keller
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Editors and Affiliations

  1. University of Innsbruck, Technikerstr. 21a, A-6020, Innsbruck, Austria

    Martin Hepp

  2. Vrije Universiteit Brussel, Pleinlaan 2, B-1050, Brussel, Belgium

    Pieter De Leenheer

  3. CommunitySense, Cavaleriestraat 2, NL-5017 ET, Tilburg, Netherlands

    Aldo De Moor

  4. University of Karlsruhe, Vincenz-Priessnitz-Str. 1, D-76131, Karlsruhe, Germany

    York Sure

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Heymans, S. et al. (2008). Ontology Reasoning with Large Data Repositories. In: Hepp, M., De Leenheer, P., De Moor, A., Sure, Y. (eds) Ontology Management. Computing for Human Experience, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-69900-4_4

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