Provenance-Based Strategies to Develop Trust in Semantic Web Applications

Abstract

Linked data and Semantic Web technologies enable people to navigate across heterogeneous sources of data thus making it easier for them to explore and develop multiple perspectives for use in making decisions and solving problems. While the Semantic Web offers benefits for developers and users, several new challenges are emerging that may negatively impact users’ trust in Web-based collaborative systems. This paper describes several use cases to illustrate potential trust issues faced by Semantic Web applications, and provides a concrete example for each using a specific system we built to investigate United States Supreme Court decision making. Provenance-based solutions are proposed to develop trust and/or minimize the distrust that is provoked by the situation. While these use cases address distinct situations, they are all described in terms of how a contradiction can arise between the user’s mental model and the statements presented in the display. This commonality may be used to develop additional classes of trust-threatening use cases, and the proposed provenance-based solutions can be applied to many other Semantic Web Applications.