Abstract
In any combination of database, a common agreement of the underlying instances concerned to a schema attribute may exist. A distributed database may therefore contain different schemas of same data attributes or different attributes classified from the same population. In this paper, we propose a common schema integration approach to integrating different autonomous agricultural databases of biorefining field of Miscanthus plants. We adopt a model, which is basically relational to some object-oriented properties. We describe methodologies to integrate heterogeneous distributed databases by using this model and show how attribute conflicts and missing attributes can be resolved. We also describe how a query on integrated global schema is managed in heterogeneous agricultural distributed database environment. We give a formal definition and perform extensive experiments to make this integration process strong enough.
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Wang, J.; Zhang, Y.; Lu, J.; Miao, Z.; Zhou, B.: Query processing for heterogeneous relational data integration. In: IEEE International Conference on Intelligent Computing and Integrated Systems (ICISS), pp. 777–781 (2010)
Hsiao, D.K.; Neuhold, E.J.; Sacks-Davis, R.: Knowledge based integration of heterogeneous databases. In: Interoperable Database Systems (DS-5): Proceedings of the Sixth IFIP WG2 Database Semantics Conference on Interoperable Database Systems (DS-5), Lorne, VIC, Australia, 16–20 November, 1992, p. 155. Elsevier (2014)
Algergawy A., Schallehn E., Saake G.: Improving XML schema matching performance using Prüfer sequences. Data Knowl. Eng. 68(8), 728–747 (2009)
Kim, W.: Introduction to SQL/X. In: Proceedings of the Second Far-East Workshop on Future Database Systems, pp. 2–7 (1992)
Magnani, M.; Montesi, D.: Uncertainty in data integration: current approaches and open problems. In: MUD, pp. 18–32 (2007)
Jayram T.S., Krishnamurthy R., Raghavan S., Vaithyanathan S., Zhu H.: Avatar information extraction system. IEEE Data Eng. Bull. 29(1), 40–48 (2006)
Antova, L.; Koch, C.; Olteanu, D.: 10(106) worlds and beyond: efficient representation and processing incomplete information. VLDB J. 18(5), 1021–1040 (2009)
Benjelloun, O.; Sarma, A.D.; Halevy, A.; Widom, J.: ULDBs: databases with uncertainty and lineage. In: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 953–964. VLDB Endowment (2006)
Dalvi N., Suciu D.: Efficient query evaluation on probabilistic databases. VLDB J. 16(4), 523–544 (2007)
Sarma, A.D.; Benjelloun, O.; Halevy, A.Y.; Widom, J.: Working models for uncertain data. In: Proceedings of the ICDE (2006)
Singh, S.; Mayfield, C.; Mittal, S.; Prabhakar, S.; Hambrusch, S.E.; Shah, R.: Orion 2.0: native support for uncertain data. In: Proceedings of the SIGMOD (2008)
Hua, M.; Pei, J.; Zhang, W.; Lin, X.: Ranking queries on uncertain data: a probabilistic threshold approach. In: Proceedings of the SIGMOD Conference (2008)
Soliman, M.A.; Ilyas, I.F.; Chang, K.C.C.: Top-k query processing in uncertain databases. In: Proceedings of the ICDE (2007)
Yiu, M.L.; Mamoulis, N.; Dai, X.; Tao, Y.; Vaitis, M.: Efficient evaluation of probabilistic advanced spatial queries on existentially uncertain data. IEEE Trans. Knowl. Data Eng. 21(1), 108–122 (2009)
Frank, L.: Architecture for integrating heterogeneous distributed databases using supplier integrated e-commerce systems as an example. In: Proceedings of IEEE International Conference on Computer and Management (CAMAN), pp. 1–4 (2011)
Mangnani M., Rizopouls N., McBrien P., Montesi D.: Schema Integration Based Semantic Mappings, pp. 31–46. Springer, Berlin (2005)
Sun, Y.; Liu, J.; Yang, L.; Geng, X.; Cao, X.: A new heterogeneous database integration model based on multi-agent. In: IEEE Fourth International Conference on Computational and Information Sciences (ICCIS), 2012, pp. 421–424 (2012)
Xu, H.; Tian, Y.; Dong, G.: A schema of data exchange for heterogeneous data. In: IEEE 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), pp. 5324–5327 (2011)
Brodie, M.L.: Data integration at scale: from relational data integration to information ecosystems. In: IEEE 24th IEEE International Conference on Advanced Information Networking and Applications (AINA), pp. 2–3 (2010)
Chen, W.; Guo, H.; Zhang, F.; Pu, X.; Liu, X.: Mining schema matching between heterogeneous databases. In: IEEE 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), pp. 1128–1131 (2012)
Sundaresan, S.; Hu, G.: Schema integration of distributed databases using hyper graph data model. In: IEEE International Conference on Information Reuse and Integration (IRI), pp. 548–553 (2005)
Falconer, S.M.; Noy, N.F.: Interactive techniques to support ontology matching. In: Schema Matching and Mapping, pp. 29–51. Springer, Berlin (2011)
Peukert, E.; Berthold, H.; Rahm, E.: Rewrite techniques for performance optimization of schema matching processes. In: Proceedings of the 13th International Conference on Extending Database Technology, pp. 453–464. ACM (2010)
Gross, A.; Hartung, M.; Kirsten, T.; Rahm, E.: On matching large life science ontologies in parallel. In: Data Integration in the Life Sciences, pp. 35–49. Springer, Berlin (2010)
Hartung, M.; Terwilliger, J.; Rahm, E.: Recent advances in schema and ontology evolution. In: Schema Matching and Mapping, pp. 149–190. Springer, Berlin (2011)
Parundekar, R.; Knoblock, C.A.; Ambite, J.L.: Linking and building ontologies of linked data. In: The Semantic Web—ISWC, pp. 598–614. Springer, Berlin (2010)
Pottinger, R.: Mapping-based merging of schemas. In: Schema Matching and Mapping, pp. 223–249. Springer, Berlin (2011)
Seligman, L.; Mork, P.; Halevy, A.; Smith, K.; Carey, M.J.; Chen, K.; Burdick, D.: Openii: an open source information integration toolkit. In: Proceedings of the ACM SIGMOD International Conference on Management of data, pp. 1057–1060. ACM (2010)
Bellahsene Z., Bonifati A., Rahm E.: Schema Matching and Mapping, vol. 20. Springer, Heidelberg (2011)
Saha, B.; Stanoi, I.; Clarkson, K.L.: Schema covering: a step towards enabling reuse in information integration. In: IEEE 26th International Conference on Data Engineering (ICDE), pp. 285–296. IEEE (2010)
Raunich, S.; Rahm, E.: ATOM: automatic target-driven ontology merging. In: IEEE 27th International Conference on Data Engineering (ICDE), pp. 1276–1279. IEEE (2011)
Gal, A.: Enhancing the capabilities of attribute correspondences. In: Schema Matching and Mapping, pp. 53–73. Springer, Berlin (2011)
Fagin, R.; Kolaitis, P.G.; Popa, L.; Tan, W.C.: Schema mapping evolution through composition and inversion. In: Schema Matching and Mapping, pp. 191–222. Springer, Berlin (2011)
Cruz I.F., Antonelli F.P., Stroe C.: AgreementMaker: efficient matching for large real-world schemas and ontologies. Proc. VLDB Endow. 2(2), 1586–1589 (2009)
Rahm, E.: Towards large-scale schema and ontology matching. In: Schema Matching and Mapping, pp. 3–27. Springer, Berlin (2011)
Landers, T.; Rosenberg, R.L.: An overview of Multibase. In: Distributed systems, distributed data base systems, vol II. Artech House, Inc., pp. 391–421 (1986)
Elmasri, R.; Navathe, S.B.: Fundamentals of Database Systems, 4th edn. Benjamin/Cummings, Mento Park (1994)
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Ramesh, D., Kumar, C. Schema Integration Based Merging and Matching Algorithm for Agricultural HDDBs. Arab J Sci Eng 40, 2555–2569 (2015). https://doi.org/10.1007/s13369-015-1735-5
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DOI: https://doi.org/10.1007/s13369-015-1735-5