Agent-based Data Integration Framework
DOI:
https://doi.org/10.7494/csci.2014.15.4.389Keywords:
data integration, multi-agent systemsAbstract
Combining data from diverse, heterogeneous sources while facilitating a unified access to it is an important (albeit difficult) task. There are various possibilities of performing it. In this publication, we propose and describe an agent-based framework dedicated to acquiring and processing distributed, heterogeneous data collected from diverse sources (e.g., the Internet, external software, relational, and document databases). Using this multi-agent-based approach in the aspects of the general architecture (the organization and management of the framework), we create a proof-of-concept implementation. The approach is presented using a sample scenario in which the system is used to search for personal and professional profiles of scientists.Downloads
References
Agarwal S., Handschuh S., and Staab S.: Surfing the Service Web. In: International Semantic Web Conference 2003, pp. 211–226. Springer, 2003.
Byrski A., Kisiel-Dorohinicki M., Dajda J., Dobrowolski G., and Nawarecki E.: Hierarchical multi-agent system for heterogeneous data integration. In: J.K. Pascal Bouvry Horacio Gonzalez-Velez, ed., Intelligent decision systems in large-scale distributed environments. Springer Verlag, 2011.
Byrski A., Kisiel-Dorohinicki M., and Nawarecki E.: Agent-Based Evolution of Neural Network Architecture. In: M. Hamza, ed., Proc. of the IASTED Int. Symp.: Applied Informatics. IASTED/ACTA Press, 2002.
Cao L.: Introduction to agent mining interaction and integration. In: Data mining and multi-agent integration, pp. 3–36. Springer, 2009
Cao L., Gorodetsky V., and Mitkas P.A.: Agent mining: The synergy of agents and data mining. Intelligent Systems, IEEE, vol. 24(3), pp. 64–72, 2009.
Faber Ł., Piętak K., Byrski A., and Kisiel-Dorohinicki M.: Agent-Based Simulation in AgE Framework. In: Advances in Intelligent Modelling and Simulation,
pp. 55–83. Springer, 2012.
Gamma E., Helm R., Johnson R., and Vlissides J.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, 1995.
Gul O., Al-Qutayri M., Vu Q.H., and Yeun C.Y.: Data integration of electronic health records using artificial neural networks. In: Internet Technology And Secured Transactions, 2012 International Conferece For, pp. 313–317. 2012.
Li S., Zhang D.H., Zhou J.T., Ma G.H., and YangR H.: An XML-Based Middleware for Information Integration of Enterprise Heterogeneous Systems. Materials Science Forum, vol. 532, pp. 516–519, 2006.
Martín L., Anguita A., Maojo V., Bonsma E., Bucur A.I.D., Vrijnsen J., Brochhausen M., Cocos C., Stenzhorn H., Tsiknakis M., Doerr M., and Kondylakis H.: Ontology Based Integration of Distributed and Heterogeneous Data Sources in ACGT. In: L. Azevedo and A.R. Londral, eds., HEALTHINF (1), pp. 301–306. INSTICC - Institute for Systems and Technologies of Information, Control and Communication, 2008. ISBN 978-989-8111-16-6.
Myłka A., Myłka A., Kryza B., and Kitowski J.: Integration of Heterogeneous Data Sources in an Ontological Knowledge Base. Computing & Informatics, vol. 31(1), 2012.
Nawarecki E., Dobrowolski G., Byrski A., and Kisiel-Dorohinicki M.: Agent-based integration of data acquired from heterogeneous sources. In: Proc. of CISIS 2011, Seoul, Korea. 2011.
Paula A.C.M.P.d., Avila B.C., Scalabrin E., and Enembreck F.: Multiagent-Based Model Integration. In: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology, WIIATW ’06, pp. 11–14. IEEE Computer Society, Washington, DC, USA, 2006. ISBN 0-7695-2749-3. URL http://dx.doi.org/http://dx.doi.org/10.1109/ WI-IATW.2006.96.
Pietak K., Wos A., Byrski A., and Kisiel-Dorohinicki M.: Functional Integrity of Multi-Agent Computational System Supported By Component-Based Implementation. In: Proc. of Holomas 2009, Linz, Austria (accepted for printing). 2009.
Stevens W.P., Myers G.J., and Constantine L.L.: Structured design. IBM Systems Journal, vol. 13(2), pp. 115–139, 1974.