Organizers: Antony Galton, Mike Worboys, Matt Duckham, Jake Emerson

With the development of new sensor and communication technologies, there is an ever more pressing need for reliable and properly codified methods for deriving high-level information from masses of dynamic spatio-temporally distributed data. Data sources of relevance here include wireless sensor networks, CCTV, GPS, crowd-sourcing, and many others. The data may in some cases be understood as sample points from a continuous dynamic field, in other cases they may represent discrete objects forming crowds, swarms, or other collective entities. The desired high-level information can include the identification of objects or object-like aggregations, and the processes and events that they participate in, e.g., motion, expansion, contraction, splitting, or merging. Although much work is now being done on investigating such phenomena, there is still a need for a unified theoretical framework and common vocabulary to support the development of tools and techniques for handling them. This workshop is intended to provide a forum for researchers who are working in this area, with particular reference to representation techniques, algorithms, and applications.

Web site: http://nav.spatial.maine.edu/cosit/