On-demand Data Integration for Decision-making Applications

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