Section: Application Domains

Collaborative workflows

A current trend is to involve end-users in collection and analysis of data. Exemples of this trend are contributive science, crisis management systems, and crowds. All these applications are data-centric and user-driven. They are often distributed and involve complex and sometimes dynamic workflows. In many cases, there are strong interactions between data and control flows: indeed, decisons taken to decide of the next tasks to be launched highly depend on collected data. For instance, in an epidemic surveillance system, the aggregation of various reported disease cases may trigger alerts. Another example is crowds where user skills are used to complete tasks that are better performed by humans than computers. In return, this needs to address imprecise and sometimes unreliable answers. We address several issues related to complex workflows and data. We study declarative and dynamic models that can handle workflows, data, uncertainty, and competences management. Once these models are mature enough, we plan to experiment them on real use cases from contributive science, health management systems, and crowd platforms using prototypes. We also plan to define abstaction schemes allowing formal reasonning on these systems.