Supporting Provenance in Service-oriented Computing Using the Semantic Web Technologies
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Abstract
The Web is evolving from a global information space to a collaborative problem solving environment in which services (resources) are dynamically discovered and composed into workflows for problem solving, and later disbanded. This gives rise to an increasing demand for provenance, which enables users to trace how a particular result has been arrived at by identifying the resources, configurations and execution settings. In this paper we analyse the nature of service-oriented computing and define a new conception called augmented provenance. Augmented provenance enhances conventional provenance data with extensive metadata and semantics, thus enabling large scale resource sharing and deep reuse. A Semantic Web Service (SWS) based, hybrid approach is proposed for the creation and management of augmented provenance in which semantic annotation is used to generate semantic provenance data and the database management system is used for execution data management. We present a general architecture for the approach and discuss mechanisms for modeling, capturing, recording and querying augmented provenance data. The approach has been applied to a real world application in which tools and GUIs are developed to facilitate provenance management and exploitation.