A Semantic Web Service Based Approach for Augmented Provenance

Abstract

Provenance is becoming increasingly important in service-oriented distributed computing environments in which services are dynamically discovered and composed into workflows for problem solving, and disbanded later. This paper proposes a Semantic Web Service (SWS) based approach to creating and exploiting rich provenance data -- the so-called augmented provenance. Augmented provenance enhances conventional provenance data with extensive metadata and semantics, enabling large scale sharing and deep reuse. We present a general architecture for the approach and discuss mechanisms for modelling, capturing, recording and querying provenance data. The approach has been applied to a real world application in which tools and GUIs are developed to facilitate provenance management. Application experiences are discussed.