Provenance-Based Strategies to Develop Trust in Semantic Web Applications

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Citation: Li, X., Lebo, T., and McGuinness, D.L. 2010. Provenance-Based Strategies to Develop Trust in Semantic Web Applications. In Proceedings of International Provenance and Annotation Workshop 2010 (June 15-16 2010, Hefner Alumni House, Rensselaer Polytechnic Institute, Troy, NY, US), pages 182–197.

Presented at the International Provenance and Annotation Workshop 2010

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.

History

DateCreated ByLink
July 12, 2011
10:53:51
Tim LeboDownload

Related Projects:

Inference Web Project LogoInference Web
Principal Investigator: Deborah L. McGuinness
Description: The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust. Provenance - if users (humans and agents) are to use and integrate data from unknown, uncertain, or multiple sources, they need provenance metadata for evaluation Interoperability - more systems are using varied sources and multiple information manipulation engines, thus increasing interoperability requirements Explanation/Justification - if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust - if some sources are more trustworthy than others, trust ratings are desired The Inference Web consists of two important components: Proof Markup Language (PML) Ontology - Semantic Web based representation for exchanging explanations including provenance information - annotating the sources of knowledge justification information - annotating the steps for deriving the conclusions or executing workflows trust information - annotating trustworthiness assertions about knowledge and sources IW Toolkit - Web-based and standalone tools that facilitate human users to browse, debug, explain, and abstract the knowledge encoded in PML.
DCO-DS LogoLinking Open Government Data (LOGD)
Principal Investigator: Jim Hendler and Deborah L. McGuinness
Description: The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on Data.gov and other websites.
TW LogoSemantic Workflow and Management of Provenance (SWaMP)
Principal Investigator: Peter Fox
Description: A joint effort between the Tetherless World Constellation at Rensselaer Polytechnic Institute and the The Commonwealth Scientific and Industrial Research Organisation (CSIRO).
SeSF Project LogoSemantic eScience Framework (SeSF)
Principal Investigator: Peter Fox
Co Investigator: Jim Hendler and Deborah L. McGuinness
Description: Over the past few years, semantic technologies have evolved and new tools are appearing. Part of the effort in this project will be to accommodate these advances in the new framework and lay out a sustainable software path for the (certain) technical advances. In addition to a generalization of the current data science interface, we will include an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.
DCO-DS LogoTheory and Practice of Accountable Systems (TPAS)
Principal Investigator: Jim Hendler
Description: The TPAS Project investigates computational and social properties of information networks necessary to provide reliable assessments of compliance with rules and policies governing the use of information.

Related Research Areas:

Inference And Trust
Lead Professor: Deborah L. McGuinness
Description: Inference And Trust
Concepts: Semantic Web
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance, Semantic Web
Semantic Foundations
Lead Professor: Deborah L. McGuinness
Description: Semantic Foundations
Concepts: Semantic Web
X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: Semantic Web,