Daniel Schall

TL;DR: In this paper, the authors focus on the notion of social trust in collaborative networks and show an interpretative rule-based approach to enable humans and services to establish trust based on interactions and experiences, considering their context and subjective perceptions.

TL;DR: In this article, a human-provided services (HPS) framework is proposed to allow humans to specify different interaction interfaces (services), which can be reused in various collaborations. But it does not support ad hoc and process-centric collaborations.

TL;DR: This work presents a crowdsourcing marketplace that matches complex tasks, requiring multiple skills, to suitable workers and presents auction mechanisms that help to correctly estimate workers and to evolve skills that are needed in the system.

TL;DR: This paper proposes techniques and algorithms enabling the prediction of trust even when only few or no ratings have been collected or interactions captured, and introduces the concepts of mirroring and teleportation of trust facilitating the evolution of cooperation between various actors.

TL;DR: InContext aggregates disparate collaboration services using Web services and Semantic Web technologies and provides a platform that captures diverse dynamic aspects of team collaborations and utilizing runtime and historical context and interaction information, adaptation techniques can be deployed to cope with the changes of emerging teams.