Search the Dagstuhl Website
Looking for information on the websites of the individual seminars? - Then please:
Not found what you are looking for? - Some of our services have separate websites, each with its own search option. Please check the following list:
Schloss Dagstuhl - LZI - Logo
Schloss Dagstuhl Services
Within this website:
External resources:
  • DOOR (for registering your stay at Dagstuhl)
  • DOSA (for proposing future Dagstuhl Seminars or Dagstuhl Perspectives Workshops)
Within this website:
External resources:
Within this website:
External resources:
  • the dblp Computer Science Bibliography

Dagstuhl Seminar 10491

Representation, Analysis and Visualization of Moving Objects

( Dec 05 – Dec 10, 2010 )

(Click in the middle of the image to enlarge)

Please use the following short url to reference this page:




This seminar is a successor to the Representation, Analysis and Visualization of Moving Objects seminar in 2008 (seminar 08451). The major goal has been to bring together the diverse and fast growing, research community that is involved in developing better computational techniques for spatio-temporal object representation, data mining, and visualization of massive amounts of moving object data. The participants included experts from fields such as computational geometry, data mining, visual analytics, GIS science, transportation science, urban planning and movement ecology. Most of the participants came from academic institutions, some from government agencies and industry. The seminar has led to a fruitful exchange of ideas between different disciplines, to the creation of new interdisciplinary collaborations, concrete plans for a data challenge in an upcoming conference, and to recommendations for future research directions

People, wildlife, material, food, data and even ideas move in increasing volumes at increasing speeds over increasing distances, hence mobility and movement are key processes in our present world. Understanding of mobility patterns is essential to substantiate decision making in public and private sectors, in application domains such as fleet management, transportation modeling, urban planning, tourism, wildlife ecology, spatial epidemiology, location-based services, flight safety, and marine safety. It is needed, for instance, for the prediction and monitoring of individual and group behaviors in response to and mitigation of security threats over short and long time scales. Traffic management can greatly benefit from the analysis of movement data, for example through better movement simulation (leading to better road network designs) but also by incorporating advanced detection sensors in vehicles. As a final example, mobility patterns of endangered species are prerequisites to devising protective measures in nature conservation and successfully managing interactions between tourism and conservation.

Moving object data typically include trajectories of concrete spatial 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 records are nowadays generated in huge volumes on a routine basis, using diverse technologies such as radio telemetry, GPS, analysis of video sequences, Doppler radar, or infrared eye tracking. 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 monodisciplinary approaches. Overcoming these limitations calls for improved networking of the type that can be facilitated by Dagstuhl seminars.

The main obstacle in movement research is that it is still a young field, facing problems of a predominantly interdisciplinary nature. The fact that the field is still young is illustrated by the fast development of new analysis algorithms and the ever increasing data availability (in terms of diversity as well as quantity). At the preceding seminar 08451, many interesting research results were presented, demonstrating the progress in this field, and an agenda for future research was compiled. While the participants were highly satisfied with that seminar, it was also felt that future meetings should involve an increased representation of domain specialists from relevant application domains. This need has been addressed by inviting representatives from diverse applications domains, including animal ecology, transportation, urbanism, tourism, and mobile information systems.

Interdisciplinary collaboration requires a long-term investment from the different disciplinary experts to learn about the problems at hand and the terminology used by their counterparts from other disciplines. Bringing together computing scientists with domain experts at this seminar helped to develop concrete case studies, identify suitable example data sets, and sketch out guidelines for benchmarking. The availability of example data, as well as concrete case studies help to speed up the process of bridge-building between different disciplines. This seminar has served as a catalyst in this respect, and has stimulated research on interdisciplinary topics. Nevertheless, continuity over a sufficiently long period is still important to achieve real progress. The establishment of sustainable and long-term projects (and project funding) for this type of research remains a challenge and deserves utmost attention. This seminar thus also paid specific attention to informing the participants about potential funding opportunities, and to stimulating joint grant proposals. A long-term perspective is also provided by the recently established network of the COST action IC0903 MOVE (, which was joined by many of the participants, owing to the open participation framework of COST actions.

  • Kevin Buchin (TU Eindhoven, NL) [dblp]
  • Maike Buchin (TU Eindhoven, NL) [dblp]
  • Mark de Berg (TU Eindhoven, NL) [dblp]
  • Urska Demsar (NUI Maynooth, IE) [dblp]
  • Eduardo Dias (VU University of Amsterdam, NL)
  • Anne Driemel (Utrecht University, NL) [dblp]
  • Sándor Fekete (TU Braunschweig, DE) [dblp]
  • Joachim Gudmundsson (The University of Sydney, AU) [dblp]
  • Patrick Laube (Universität Zürich, CH) [dblp]
  • Harvey J. Miller (University of Utah, US) [dblp]
  • David M. Mountain (City University - London, GB)
  • Ross Purves (Universität Zürich, CH) [dblp]
  • Jörg-Rüdiger Sack (Carleton University - Ottawa, CA) [dblp]
  • Monika Sester (Leibniz Universität Hannover, DE) [dblp]
  • Rodrigo I. Silveira (UPC - Barcelona, ES) [dblp]
  • Aidan Slingsby (City University - London, GB) [dblp]
  • Jack Snoeyink (University of North Carolina at Chapel Hill, US) [dblp]
  • Bettina Speckmann (TU Eindhoven, NL) [dblp]
  • Sabine Timpf (Universität Augsburg, DE) [dblp]
  • Stefan van der Spek (TU Delft, NL) [dblp]
  • Marc van Kreveld (Utrecht University, NL) [dblp]
  • Emiel Van Loon (University of Amsterdam, NL)
  • Mathias Versichele (Ghent University, BE)
  • Robert Weibel (Universität Zürich, CH) [dblp]
  • Erik Willems (Universität Zürich, CH)

Related Seminars
  • Dagstuhl Seminar 08451: Representation, Analysis and Visualization of Moving Objects (2008-11-02 - 2008-11-07) (Details)
  • Dagstuhl Seminar 12512: Representation, Analysis and Visualization of Moving Objects (2012-12-16 - 2012-12-21) (Details)
  • Dagstuhl Seminar 14132: Interaction and Collective Movement Processing (2014-03-23 - 2014-03-28) (Details)
  • Dagstuhl Seminar 16022: Geometric and Graph-based Approaches to Collective Motion (2016-01-10 - 2016-01-15) (Details)
  • Dagstuhl Seminar 17282: From Observations to Prediction of Movement (2017-07-09 - 2017-07-14) (Details)

  • data bases / information retrieval
  • data structures / algorithms / complexity
  • mobile
  • modelling / simulation
  • society / human computer interaction
  • interdisciplinary: Cartography

  • moving objects
  • spatio-temporal databases
  • spatio-temporal analysis
  • movement analysis
  • spatial data mining
  • KDD
  • computational geometry
  • visual analytics