Description and aim
Mobility is key in a globalised world where people, goods, data and even ideas move in increasing volumes at increasing speeds over increasing distances. Knowledge about movement is essential to substantiate decision making in public and private sectors, in application domains as diverse as fleet management, transportation modeling, urban planning, tourism, wildlife ecology, spatial epidemiology, location-based services, flight safety, or marine safety. Moving object data typically include trajectories of tangible objects (e.g. humans, vehicles, animals, and goods), as well as trajectories of abstract concepts (e.g. spreading diseases, gaze points in eye movement tracking). Technologies for object tracking have recently become affordable and reliable and hence movement data are now generated in huge volumes on a routine basis, using diverse technologies. Despite this plethora of readily available tracking data, methods for extracting useful information are still immature, due to fragmentation of research and lack of comprehensiveness from mono-disciplinary approaches. To overcome some of these difficulties this interdisciplinary workshop aims to create a forum for methodologically oriented as well as application oriented researchers to share their knowledge.
The main goals of the workshop are threefold. First of all, we want to facilitate the exchange of knowledge among quite diverse disciplines. Second, we aim to identify important cross-cutting concerns and research questions culminating in the formulation of a research agenda for the next years. Finally, we hope to create new research directions and collaborations. Ideally this will lead to future joint research projects.
The following is a list of topics which are likely to be addressed during the workshop:application requirements: what type of information should be extracted from movement data, what are the needs of real-world applications … common characteristics of movement patterns generated by different types of moving objects efficient methods for storing, indexing, and querying moving objects algorithms for detecting, aggregating, and generalizing movement patterns; algorithms for cluster analysis, outlier detection, … methods for exploratory visualization of large amounts of moving objects comparison of computational vs. visualization methods for knowledge discovery
The workshop is partially supported by the ESF COST action IC0903 MOVE (Knowledge Discovery from Moving Objects).