Abstract
Data gathered by organisations have diverse architecture and are based on various data models. Cooperation between organisations often requires data exchanging which, in heterogeneous environment, is not easy task. So, various integrating systems have been proposed to overcome problems concerning data exchange in such diverse systems. The field of data integration has expanded in many directions, including schema matching, record linkage, data fusion, and many more [5, 8]. In this paper various approaches to data integration are discussed and tasks that have to be fulfilled by integrating systems are identified. Because among integrating systems are also those based on ontology, their characteristics are identified. Next, the architecture of proposed system is presented, actions performing by individual modules during the process of queries execution are characterized and the process of designing integrating systems based on the proposed model is described.
The Project has been financed by the Ministry of Science and Higher Education within “Regional Initiative of Excellence” Programme for 2019-2022. Project no.: 021/RID/2018/19. Total financing: 11 897 131,40 PLN.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Asano, Y., Herr, D., Ishihara, Y., Kato, H., Nakano, K., Onizuka, M., Sasaki, Y.: Flexible framework for data integration and update propagation: System aspect. In: 2019 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 1–5 (2019)
Cotfas, L.-A., Delcea, C., Roxin, I., Paun, R.: New trends in intelligent information and database systems, In: Twitter Ontology-Driven Sentiment Analysis, pp. 131–139. Springer International Publishing, Cham (2015)
Dittrich, J.-P., Blunschi, L., Farber, M., Girard, O.R., Shant, K.K., Salles, V., Markos, A.: From personal desktops to personal dataspaces: a report on building the iMeMex personal dataspace management system, GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW), Aachen, Germany (2007)
Doan, A., Halevy, A.Y., Ives, Z.G.: Principles of Data Integration. Elsevier Inc. (2012)
Dong, X.L., Srivastava, D.: Big data integration. In: ICDE, pp. 1245–1248 (2013)
Fernandez, M.F., Florescu, D., Levy, A., Suciu, D.: Declarative specification of Web sites with STRUDEL. VLDB J. 9(1), 38–55 (2000)
Fernandez, R.C., Madden, S.: Termite: a system for tunneling through heterogeneous data. CoRR, abs/1903.05008 (2019)
Golshan, B., Halevy, A., Mihaila, G., Tan, W.C.: Data integration: after the teenage years. In: SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, pp. 101–106 (2017)
Halevy, A., Rajaraman, A., Ordille, J.: Data integration: the teenage years. In: Proceedings of the 32nd International Conference on Very Large Data Bases, VLDB 2006, pp. 9–16 (2006)
Lee, C.-H., Wu, C.-H.: Extracting entities of emergent events from social streams based on a data-cluster slicing approach for ontology engineering. Int. J. Inf. Retrieval Res. 5(3), 1–18 (2015)
Lupiani-Ruiz, E., Garcıa-Manotas, I., Valencia-Garcıa, R., Garcıa-Sanchez, F., Castellanos-Nieves, D., Fernandez-Breis, J.T., Camon-Herrero, J.B.: Financial news semantic search engine. Expert Syst. Appl. 38(12), 15565–15572 (2011)
Maedche, A., Staab, S., Studer, R., Sure-Vetter, Y., Volz, R.: SEAL – tying up information integration and web site management by ontologies, Technical report, Institute AIFB, University of Karlsruhe, Germany (2002)
Mellouli, S., Bouslama, F., Akande, A.: An ontology for representing financial headline news. In: Web Semantics: Science, Services and Agents on the World Wide Web, vol. 8, no. 2–3, pp. 203–208 (2010)
Novotný, T.: A content-oriented data model for semistructured data. In: Pokorný, J., Snášel, V., Richta, K. (eds.) Proceedings of the Dateso 2007 Workshop, Amphora Research Group, Czech Republic, pp. 55–66 (2007)
Offia, C.E., Crowe, M.K.: A theoretical exploration of data management and integration in organisation sectors. Int. J. Database Manag. Syst. (IJDMS) 11(1), 37–56 (2019)
Sardelich, M., Qomariyah, N.N., Kazakov, D.: Integrating time series with social media data in an ontology for the modelling of extreme financial events. White Rose University Consortium, Universities of Leeds, Sheffield & York (2019)
Shvaiko, P., Euzenat, J.: Ontology matching: state of the art and future challenges. IEEE Trans. Knowl. Data Eng. 25, 158–176 (2013)
Wang, X., Haas, L.M., Meliou, A.: Explaining data integration. IEEE Data Eng. Bull. 41, 47–58 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Put, D. (2020). Designing Information Integrating Systems Based on Co-shared Ontologies. In: Borzemski, L., Świątek, J., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. ISAT 2019. Advances in Intelligent Systems and Computing, vol 1050. Springer, Cham. https://doi.org/10.1007/978-3-030-30440-9_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-30440-9_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30439-3
Online ISBN: 978-3-030-30440-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)