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Section: Partnerships and Cooperations

International Initiatives

Inria Associate Teams Not Involved in an Inria International Labs

USCoast2
  • Title: User Studies on Trustworthy Collaborative Systems

  • International Partner (Institution - Laboratory - Researcher):

    • Wright State University (United States) - Department of Psychology, Knoesis - Valerie Shalin

  • Start year: 2016

  • See also: http://usCoast.loria.fr

  • The proposed project addresses the perception of trust by users, the appropriateness of a trust-based security approach and the role of trust metrics in the management of distributed work. The main challenge of this project is how to measure trust based on user behaviour and to verify by means of experimental studies with users that the trust-based mechanism is acceptable by users. We plan to apply this trust-based mechanism for two types of applications. The first one is collaborative editing where user trust will be computed based on the quality of user contributions for a document or project. The second type of application is in the management of work over a large group of people in order to conduct efficient, high-yield, high-density real time crowdsourcing activities. Partners of USCoast2 project have complementary expertise. Coast provides expertise in collaborative methods, systems and related technologies. Coast will propose algorithms that track and manipulate trust metrics.Knoesis provides expertise on the analysis of human work-related behaviour, including methods of data collection and data analysis, as well as a theoretical foundation for the evaluation of human performance. Knoesis will analyse trust from a psychological phenomenon point of view.

Inria International Partners

Informal International Partners

As part of our work on elastic business processes execution, we started a collaboration with Professor Cesare Pautasso from the University of Lugano. We developed a benchmarking framework for business process execution in the cloud, including hot migration of process engine in a multi-tenant setting. This collaboration resulted in a framework that allows repeatable evaluation of process execution.