A Framework for Improving Trust in Dynamic Service-Oriented Systems

Large-scale data processing systems frequently require users to make timely and high-value business decisions based upon information that is received from a variety of heterogeneous sources. Such heterogeneity is especially true of service-oriented systems, which are often dynamic in nature and composed of multiple interacting services. However, in order to establish user trust in such systems, there is a need to determine the validity and reliability of all the data sources that go into the making of a decision. This paper analyses the concept of provenance and discusses how the establishment of personalized provenance recording and retrieval systems can be used to increase the utility of data and engender user trust in complex service-based systems. An overview of current provenance research is presented, and a real-world project to address the abstract concepts of trust and data quality in industrial and clinical settings is presented. From this, we conclude that the addition of provenance into data processing and decision making systems can have a tangible benefit to improving the trust of system users.