Abstract
The rise of cloud computing started a transition for software applications from local to remote infrastructures. This migration created an opportunity to aggregate and consolidate analogous data content. However, this data content usually come with very different data structures and data terminologies and is usually tightly coupled to one or more applications. With these disparities and restrictions, the analogous data ends up both centrally stored but spread over several disconnected heterogeneous data sources. In this article, we present an approach to aggregate data sources using live data consolidation. The approach preserves the original data sources; and by doing so, prevents associated applications from having to migrate to a new data source. The approach uses an ontology at its core to serve as a common semantic ground between data sources and leverage its stored knowledge to expand query capabilities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ali, M.G.: A multidatabase system as 4-tiered client-server distributed heterogeneous database system. Int. J. Comput. Sci. Inf. Secur. 6(2), 10–14 (2009)
Ashino, T.: Materials ontology: an infrastructure for exchanging materials information and knowledge. Data Sci. J. 9, 54–61 (2010)
Berners-lee, T., Hendler, J., Lassila, O.: The semantic web: a new form of web content that is meaningful to computers will unleash a revolution of new possibilities. Sci. Am. 284(5) (2001)
Cheung, K., Drennan, J., Hunter, J.: Towards an ontology for data-driven discovery of new materials. In: Semantic Scientific Knowledge Integration AAAI/SSS Workshop, pp. 9–14. Stanford University, Palo Alto (2008)
Duong, L., Kanayama, H., Ma, T., Bird, S., Cohn, T.: Multilingual training of crosslingual word embeddings. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp. 894–904 (2017)
Jurafsky, D., Martin, J.H.: Speech and language processing. https://web.stanford.edu/~jurafsky/slp3/
Konstantopoulos, S., Charalambidis, A., Mouchakis, G., Troumpoukis, A., Jakobitch, J., Karkaletsis, V.: Semantic web technologies and big data infrastructures: SPARQL federated querying of heterogeneous big data stores. In: International Semantic Web Conference (2016)
Liu, Z., Calve, A.L., Cretton, F., Glassey, N.: Using semantic web technologies in heterogeneous distributed database system a case study for managing energy data on mobile devices. Int. J. New Comput. Archit. Appl. 4(2), 56–59 (2014)
Mecca, G., Rull, G., Santoro, D., Teniente, E.: Semantic-based mappings. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 255–269. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41924-9_22
Muzny, G., Zettlemoyer, L.S.: Automatic idiom identification in wiktionary. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1417–1421 (2013)
Noaman, A., Essia, F., Salah, M.: Web services based integration tool for heterogeneous databases. Int. J. Res. Eng. Sci. 1(3), 16–26 (2013)
Premkumar, V., Krishamurty, S., Wileden, J.C., Grosse, I.R.: A semantic knowledge management system for laminated composites. Adv. Eng. Inform. 28, 91–101 (2014)
Reutter, J.L., Soto, A., Vrgoč, D.: Recursion in SPARQL. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 19–35. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25007-6_2
van der Vet, P.E., Speel, P.H., Mars, N.J.: The Plinius ontology of ceramic materials. In: Proceedings of Comparison of Implemented Ontologies Workshop (1994)
Xiao, G., et al.: Ontology-based data access: a survey. In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2108, pp. 5511–5519 (2018)
Zhang, R., Wang, J., Bu, W.: Research on attribute matching method in heterogeneous databases semantic integration. J. Chem. Pharm. Res. 7(3), 16–26 (2015)
Zhao, S., Qian, Q.: Ontology based heterogeneous materials database integration and semantic query. AIP Adv. 7(10) (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Mercier, D., Cheong, H., Tapaswi, C. (2018). Unified Access to Heterogeneous Data Sources Using an Ontology. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds) Semantic Technology. JIST 2018. Lecture Notes in Computer Science(), vol 11341. Springer, Cham. https://doi.org/10.1007/978-3-030-04284-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-04284-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-04283-7
Online ISBN: 978-3-030-04284-4
eBook Packages: Computer ScienceComputer Science (R0)