Automatic composition of WSMO based geospatial semantic web services using artificial intelligence planning

Geospatial web services are widely utilised to disseminate spatial data and processing capability over the internet. Combining geospatial web services and generating composite web services out of atomic services can provide users with a higher level of functionality. This paper presents a solution for the automatic composition of geospatial web services. The solution relies on semantic web services technology and Artificial Intelligence (AI) planning techniques to generate composite geospatial web services. Web Service Modelling Ontology (WSMO) is selected as the underlying semantic web service framework. A neoclassical planning algorithm called Graphplan is used as the AI planner. The applicability of the proposed solution for composing web services is illustrated in a case study. The result shows that the proposed approach is well suited for the automatic composition of web services. The future requirements for adaptation of the approach in real world problems are broadly described.