Towards a Semantic Based Workflow Model for Composition of OWL-S Based Atomic Processes

Due to the insertion of semantics to the Web services, meeting user demands will be possible through logical deductions and achieving resolutions automatically. With the application of semantic description in content of Web services it is easier to discover and compose suitable Web services during analyzing, searching and matching processes. We proposed a framework of an Inference-based Semantic Composition Agent (SCA) of atomic processes that employs process similarity matching and inference techniques. SCA synthesizes new services from existing ones in an automatic fashion. A powerful matching mechanism is needed to find fitting tasks in order to attain the required composition by each client. An innovative Semantic Matching Step (SMS) of SCA helps to find the fitting tasks while constituting workflow to achieve required composition. Additionally, SCA composes available OWL-S atomic processes utilizing Revised Armstrong's Axioms (RAA) in inferring functional dependencies. Experiments show that SCA System produces atomic process sequences as a workflow in achieving the required composition plan that satisfies user's requirements as a complex task. The novelty of the SCA System is that for the first time Armstrong's Axioms are revised and used for semantic-based planning and inferencing of services.