Abstract
Data sourcing or integration is inevitable in current business scenario. Major issues of data sourcing from heterogeneous data sources are lack of semantic richness and deprived querying. To overcome these issues, an Ontology Based Data federation using Object Relational Database (OBDF-ORDB) architecture has been proposed and implemented. This OBDF-ORDB architecture consists of semantic layer and transformation & query layer. In semantic layer the ontology used to create local and global schema to enrich the semantics. In transformation & querying layer, Object Relational Database (ORDB) is used for storing the local ontology, global ontology to improve storage, maintenance and retrieval. The transformation rule engine proposed for the architecture converts and stores the local ontology and global ontology from flat OWL file to ORDB. The user queries are passed to ORDB for result extraction. To analyze the performance of the OBDF-ORDB architecture E-shopping application is selected. Experimental results shows that the proposed OBDF-ORDB architecture is relatively better than the traditional data access and ontology based data access in recall and response time. It is observed that the recall mechanism in OBDF-ORDB architecture has been improved by 25% compared to traditional data federation and response time is reduced by 15% compared to ontology based data federation.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Lenzerini, M.: Data integration a theoretical perspective. In: Proceedings of the Twenty-First Symposium on Principles of Database Systems, pp. 233–246. ACM SIGMOD-SIGACT-SIGART, New York (2002)
Hema, M.S., Chandramathi, S.: Federated query processing service in service oriented business intelligence. In: Das, V.V., Stephen, J., Chaba, Y. (eds.) CNC 2011. CCIS, vol. 142, pp. 337–340. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19542-6_62
Busse, S., Kutsche, R.D., Leser, U., Weber, H.: Federated information systems: concepts, terminology and architectures. Forschungsberichte des Fachbereichs Informatik 99(9), 1–38 (1999)
Gagnon, M.: Ontology-based integration of data sources. In: 10th International Conference on Information Fusion, pp. 1–8. IEEE (2007)
Xiao, H.: Query processing for heterogeneous data integration using ontologies, Ph.D. thesis, University of Illinois, Chicago (2006)
Hu, G.: Global schema as an inversed view of local schemas for integration. In: International Conference on Software Engineering Research, pp. 206–212. SERA (2006)
Song, F., Zacharewicz, G., Chen, D.: An ontology-driven framework towards building enterprise semantic information layer. J. Adv. Eng. Inform. 27(1), 38–50 (2013). Elsevier
Konstantinou, N., Spanos, D.E., Chalas, M., Solidakis, E., Mitrou, N.: VisAVis: an approach to an intermediate layer between ontologies and relational database contents. In: WISM, p. 239 (2006)
Vysniauskas, E., Nemuraite, L., Paradauskas, B.: Hybrid method for storing and querying ontologies in databases. J. Electron. Electr. Eng. 9, 67–72 (2011)
Sheth, A.P., Larson, J.A.: Federated database systems for managing distributed, heterogeneous, and autonomous databases. ACM Comput. Surv. 22(3), 183–236 (1990). ACM
Kashyap, V., Sheth, A.: Semantic and schematic similarities between: a context-based approach. Int. J. Very Large Data Bases 5(4), 276–304 (1996)
Hull, R., King, R.: Semantic database modeling: survey, applications, and research issues. ACM Comput. Surv. 19, 202–260 (1987)
Fernandez, M., Cantador, I., Lopez, V.: Semantically enhanced information retrieval: an ontology-based approach. J. Web Semant.: Sci. Serv. Agents World Wide Web 9(4), 434–452 (2011)
Wiederhold, G.: Mediators in the architecture of future information systems. IEEE Comput. 25(3), 38–49 (1992). IEEE
Langegger, A.: Virtual data integration on the web-novel methods for accessing heterogeneous and distributed data with rich semantics. In: International Conference on Information Integration and Web based Integration System, WAS 2008, pp. 559–562. ACM (2008)
Hua, Z., Ban, J.: Ontology-based integration and interoperation of XML data. In: Sixth International Conference on Semantics, Knowledge and Grids, Beijing, pp. 422–423. IEEE (2010)
Pinheiro, J.C., Vidal, V.M., Macêdo, J.A., Sacramento, E.R., Casanova, M.A., Porto, F.A.: Query processing in a three-level ontology-based data integration system. In: Proceedings of the 12th International Conference on Information Integration and Web-Based Applications & Services, pp. 283–290. ACM (2010)
Zhang, L., Ma, Y., Wang, G.: An extended hybrid ontology approach to data integration. In: International Conference on Biomedical Engineering and Informatics, BMEI 2009, pp. 1–4 (2009)
Zhao, Y., Zhang, S., Yan, Z.: Ontology – based model for resolving the data-level and semantic-level conflict. In: International Conference on Information and Automation. IEEE (2009)
Rodriguez, M.A., Egenhofer, M.J.: Determining semantic similarity among entity classes from different ontologies. IEEE Trans. Knowl. Data Eng. 15(2), 442–456 (2003). IEEE
Harrison, R., Chan, C.: Distributed ontology management system. In: Proceedings of 18th Annual Canadian Conference on Electrical and Computer Engineering, Saskatoon, Canada, pp. 661–664 (2005)
Glimm, B., Horrocks, I., Motik, B., Shearer, R., Stoilos, G.: A novel approach to ontology classification. Web Semant.: Sci. Serv. Agents World Wide Web 14, 84–101 (2012)
Stojanovic, L., Stojanovic, N., Volz, R.: Migrating data-intensive web sites into the semantic web. In: Proceedings of the 2002 ACM Symposium on Applied Computing, pp. 1100–1107. ACM (2002)
Dou, D., LePendu, P., Kim, S., Qi, P.: Integrating databases into the semantic web through an ontology-based framework. In: 22nd International Conference on Data Engineering Workshops Proceedings, p. 54. IEEE (2006)
Ghawi, R., Cullot, N.: Database-to-ontology mapping generation for semantic interoperability. In: Third International Workshop on Database Interoperability (InterDB 2007), vol. 91 (2007)
Xu, Z., Zhang, S., Dong, Y.: Mapping between relational database schema and OWL ontology for deep annotation. In: International Conference on Web Intelligence, IEEE/WIC/ACM, pp. 548–552. IEEE, December 2006
Wang, S., Zhang, X.: A high efficiency ontology storage and query based on relational database. In: International conference on Electrical and Control Engineering, pp. 4253–4256 (2011)
Al-Jadir, L., Parent, C., Spaccapietra, S.: Reasoning with large ontologies stored in relational databases: the OntoMinD approach. Data Knowl. Eng. 69(11), 1158–1180 (2010)
Astrova, I., Kalja, A., Korda, N.: Automatic transformation of OWL ontologies to SQL relational databases. In: IADIS European Conference on Data Mining (MCCSIS), pp. 5–7 (2007)
Jia, C., Yue, W.: Rules-based object-relational databases ontology construction. J. Syst. Eng. Electron. 20(1), 211–215 (2009)
Denaux, R., Dolbear, C., Hart, G., Dimitrova, V., Cohn, A.G.: Supporting domain experts to construct conceptual ontologies: a holistic approach. Web Semant.: Sci. Serv. Agents World Wide Web 9(2), 113–127 (2011)
Wang, J., Zhang, Y., Miao, Z., Lu, J.: Query transformation in ontology-based relational data integration. In: Asia-Pacific Conference on Wearable Computing Systems (APWCS), pp. 303–306. IEEE (2010)
Calhau, R.F., de Almeida Falbo, R.: An ontology-based approach for semantic integration. In: 14th IEEE International Conference on Enterprise Distributed Object Computing (EDOC), pp. 111–120. IEEE (2010)
De Giacomo, G., Lembo, D., Lenzerini, M., Poggi, A., Rosati, R.: Using ontologies for semantic data integration. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds.) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. SBD, vol. 31, pp. 187–202. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-61893-7_11
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Hema, M.S., Maheshprabhu, R., Nageswara Guptha, M. (2018). Data Access in Heterogeneous Data Sources Using Object Relational Database. In: Venkataramani, G., Sankaranarayanan, K., Mukherjee, S., Arputharaj, K., Sankara Narayanan, S. (eds) Smart Secure Systems – IoT and Analytics Perspective. ICIIT 2017. Communications in Computer and Information Science, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-10-7635-0_3
Download citation
DOI: https://doi.org/10.1007/978-981-10-7635-0_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7634-3
Online ISBN: 978-981-10-7635-0
eBook Packages: Computer ScienceComputer Science (R0)