An ontology based approach to automating data integration in scientific workflows
Article No.: 44, Pages 1 - 6
Abstract
Due to the proliferation of data generating devices such as sensors in scientific applications, data integration has become most challenging task since the data stemming from these devices are extremely heterogeneous in terms of structure (schema) and semantics (interpretation). In practice, integration and transformation is typically performed by the scientists manually; in fact extensive efforts are required. The approaches for automating data integration task as much as possible are badly needed. DaltOn is a generic framework that offers various functionalities for managing the data in scientific applications. In this paper, we present DaltOn's functionality for automating data integration task based on exploitation of ontologies. In addition, we also elaborate the specific module of our framework which is responsible for implementing the functionality. At last, we also present core algorithms that demonstrate a good evaluation of our approach.
References
[1]
C. A. Goble et al. Transparent Access to Multiple Bioinformatics Information Sources. IBM Systems Journal, 40(2):532--552, 2001.
[2]
F. Baader, et al. The Description Logic Handbook: Theory, Implementation, and Applications, New York, USA: Cambridge University Press, 2003.
[3]
F. Giunchiglia, P. Shvaiko, M. Yatskevich. S-match: an algorithm and an implementation of semantic matching. In Proceedings of ESWS' 04, pp 61--75, 2004.
[4]
J. Madhavan, P. Bernstein, A. Doan, and A. Halevy. Corpus-Based Schema Matching. In ICDE'05, pages 57--68, 2005.
[5]
J. Madhavan, P. A. Bernstein, and E. Rahm. Generic schema matching with Cupid. In VLDB'01, pages 49--58, 2001.
[6]
L. Popa, Y. Velegrakis, R. J. Miller, M. Hernandes, and R. Fagin. Translating Web Data. In VLDB'02, pages 598--609, 2002.
[7]
L. Xu and D. Embley. Using Domain Ontologies to Discover Direct and Indirect Matches for Schema Elements. In Semantic Integration Workshop in ISWC'03, 2003.
[8]
N. Noy, M. Musen. Evaluating ontology mapping tools: Requirement and experience EKAW, pp. 1--14, 2002.
[9]
O. Curé, S. Jablonski. Ontology-based Data Integration in Data Logistics Workflows. Proc. CMLSA, ER07, Auckland, NZL, 2007.
[10]
P. Shvaiko, J. Euzenat. A Survey of Schema-based Matching Approaches, Journal on Data Semantics, 2005.
[11]
ProDatO Integration Technology GmbH: Handbuch iPM Integrated Process Manager, Erlangen, Germany, 2005, www.prodato.de
[12]
R. Dhamankar, Y. Lee, A. Doan, A. Halevy, P. Domingos. iMAP: discovering complex semantic matches between database schemas. In SIGMOD '04: Int. conf. on Management of data, pp. 383--394, 2004.
[13]
S. Bowers, B. Ludäscher. An Ontology-Driven Framework for Data Transformation in Scientific Workflows. Proc. DILS'04, 2004.
[14]
S. Jablonski, M. A. Rehman. DaltOn: Process based data integration in scientific application. Technical Report, Uni of Bayreuth, AI4. 2008.
[15]
S. Jablonski, M. A. Rehman, B. Volz, O. Curé. DaltOn: An Infrastructure for Scientific Data Management. Proc. AWCS08, Int. Conference on Computational Science (ICCS), 2008.
[16]
S. Jablonski, M. A. Rehman, B. Volz. A Conceptual Modeling and Execution Framework for Process Based Scientific Applications. Proc. CIMS07, ACM 16th Conf. on Information and Knowledge Management (CIKM), Lisboa, Portugal, November 2007.
[17]
S. Jablonski, M. A. Rehman, B. Volz. A Modeling Methodology for Scientific Processes. Workshop for Environmental Databases, Hamburg, Germany, May 2007.
[18]
S. Jablonski, C. Bussler. Workflow Management -- Modeling Concepts, Architecture and Implementation. London: Int. Thomson Computer Press, 1996
[19]
S. Staab, R. Studer. Handbook of Ontologies. Springer, 2004.
[20]
U. Visser, H. Stuckenschmidt, H. Wache, T. Vögele. Using environmental information efficiently: Sharing data and knowledge from heterogeneous sources. EISIPA, pp. 41--73, IDEA Group, Hershey, USA & London, UK, 2001.
[21]
Website BayCEER, http://www.bayceer.uni-bayreuth.de/, Aug 2009.
[22]
Website Protégé, http://protege.stanford.edu/, 2009-07-20
[23]
X. Dong, A. Y. Halevy, J. Madhavan. Reference Reconciliation in Complex Information Spaces. In Proc. SIGMOD Conference 2005.
[24]
Y. An, A. Borgida, R. J. Miller, J. Mylopoulos. A Semantic Approach to Schema Mapping. 23rd IEEE ICDE07, April 2007.
[25]
Y. Kalfoglou, M. Schorlemmer. IF-Map: An Ontology-Mapping Method Based on Information-Flow Theory, Journal on Data Semantics, Vol. 1, pp 98--127, 2003.
[26]
Z. Ben-Miled, N. Li, M. Baumgartner, Y. Liu. A decentralized approach to the integration of life science web databases. Informatica (Slovenia), 27(1):3--14, 2003.
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Published: 16 December 2009
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