On-demand Data Integration for Decision-making Applications

Jānis Grabis, Jānis Kampars


Decision-making efficiency depends upon timely availability of appropriate data. On-demand data integration from web based data sources provides an attractive solution to data gathering. The two major challenges associate with on-demand data integration are selection of appropriate data services and efficient implementation of the data integration process. In this paper, it is proposed to use service’s business value as a service selection criterion and to elaborate a lightweight method for XML based definition of the integration processes. The business value driven approach implies that services are selected according to their impact on quality of decisions made rather than solely according to their QoS characteristics. The data integration process definition methods partitions the data integration process into atomic data integration tasks, thus allowing for high level of data retrieval parallelization, accommodating data interdependencies and enabling error recoverability without delaying the whole data integration process. The data integration methods are evaluated using a case study, which investigates on-line decision making at a taxi company.


  1. Abrahiem, R., 2007. A new generation of middleware solutions for a near-real-time data warehousing architecture. In: 2007 IEEE International Conference on Electro/Information Technology, 192-197.
  2. Ali, M. I., Pichler, R., Truong, H. L., Dustdar, S., 2009. On using distributed extended xquery for web data sources as services. In: 9th International Conference on Web Engineering, 497-500.
  3. Bhide, M., Agarwal, M. K., Bar-Or, A., Padmanabhan, S., Mittapalli, S. K. , Venkatachaliah, G., 2009. XPEDIA: XML processing for data integration. In Proceedings of the VLDB Endowment, 2, 1330-1341.
  4. Bonders, M., Grabis, J. , Kampars, J., 2011. Combining Functional and Nonfunctional Attributes for Cost Driven Web Service Selection. In Frontiers in Artificial Intelligence and Applications, 224, 227-239.
  5. Canfora, G., Di Penta, M., Esposito, R. & Villani, M.L., 2008. A framework for QoS-aware binding and rebinding of composite web services. Journal of Systems and Software, 81, 1754-1769.
  6. Delen, D., Demirkan, H., 2013. Data, information and analytics as services. Decision Support Systems, In Press
  7. Ehmke, J. F., Meisel, S., Mattfeld, D. C., 2012. Floating car based travel times for city logistics. Transportation Research Part C: Emerging Technologies, 21, 338- 352.
  8. Frehner, M. , Brändli, M., 2006. Virtual database: Spatial analysis in a Web-based data management system for distributed ecological data. Environmental Modelling and Software, 21, 1544-1554.
  9. Jeong, B., Cho, H., Lee, C., 2009. On the functional quality of service (FQoS) to discover and compose interoperable web services. Expert Systems with Applications, 36, 5411-5418.
  10. Strunk, A., 2010. QoS-aware service composition: A survey. In: 8th European Conference on Web Services, ECOWS, 67-74.
  11. Tsesmetzis, D., Roussaki, I. , Sykas, E., 2008. QoS-aware service evaluation and selection. European Journal of Operational Research, 191, 1101-1112.
  12. Wang, J., Yu, A., Zhang, X., Qu, L., 2009. A dynamic data integration model based on SOA. In: Second ISECS International Colloquium on Computing, Communication, Control, and Management, 196-199.
  13. Wang, H.C., Chang, S. L., Tsung, H. H., 2007. Combining subjective and objective QoS factors for personalized web service selection. Expert Systems with Applications, 32, 571-584.
  14. Yang, K., Steele, R., 2008. A system for service-oriented data aggregation. International Journal of Services and Standards, 4, 119-140.
  15. Yue, G, Wang, J., 2010. The design and implementation of XML semi-structured data extraction and loading into the data Warehouse, International Forum on Information Technology and Applications, 30-33.Zhu, F., Turner, M., Kotsiopoulos, I., Bennett, K., Russell, M., Budgen, D., Brereton, P., Keane, J., Layzell, P., Rigby, M., Xu, T., 2004. Dynamic data integration using web services. In: IEEE International Conference on Web Services, 262-269.

Paper Citation

in Harvard Style

Grabis J. and Kampars J. (2013). On-demand Data Integration for Decision-making Applications . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8565-59-4, pages 201-208. DOI: 10.5220/0004445802010208

in Bibtex Style

author={Jānis Grabis and Jānis Kampars},
title={On-demand Data Integration for Decision-making Applications},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},

in EndNote Style

JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - On-demand Data Integration for Decision-making Applications
SN - 978-989-8565-59-4
AU - Grabis J.
AU - Kampars J.
PY - 2013
SP - 201
EP - 208
DO - 10.5220/0004445802010208