Semantic Web-Based Data Service Discovery and Composition

Modern scientific research is generating daunting amount of data that is commonly required to be combined together to service daily research endeavors. This paper introduces an ontology-based approach to publishing and composing data intensive web service. The approach distinguishes itself by its capability of dynamically evolving service interface and a data service composition graph (DSCG for short) planner for service composition, enabled by richly describing service capability using the semantic web languages. The advantage of the proposed approach is that the data service (DS for short) can adapt itself with client request dynamically, greatly improving its query service capability. Experimental results show that the proposed algorithm is scalable, and provides a better performance on handling time.