Gennady Andrienko - Visual Analytics of Movement
Dr. Gennady Andrienko, Fraunhofer Institute IAIS – Intelligent Analysis and Information Systems, Schloss Birlinghoven, Sankt-Augustin, Germany
Tid: 28 maj, kl 13:15
Plats: VR-arenan, Kopparhammaren
Titel: Visual Analytics of Movement
The mission of Visual Analytics is to find ways to fundamentally improve the division of labour between humans and machines so that the computational power could amplify the human perceptual and cognitive capabilities. The term “Visual Analytics” stresses the key role of visual representations as the most effective means to convey information to human’s mind and prompt human cognition and reasoning. Visual Analytics is defined as the science of analytical reasoning facilitated by interactive visual interfaces. It combines automated analysis techniques with interactive visualizations so that to support synergetic work of humans and computers.
In many areas of people’s life and activities it is important to understand movement behaviours and mobility patterns of people, animals, vehicles, or other objects. Thanks to the recent advent of inexpensive positioning technologies, data about movement of various mobile objects or agents are collected in rapidly growing amounts. There is a pressing need in adequate methods for analysing these data and extracting relevant information.
Movement data are inherently complex as they involve (geographical) space and time. In addition to their own intrinsic complexities, these components are interdependent, which multiplies the overall complexity. As a result, movement data cannot be adequately modelled (at least at the present time) for a fully automatic analysis. At the same time, movement data, which are mostly acquired by automatic position tracking, are usually very poor semantically. The records basically consist of time stamps and coordinates.
Semantic interpretations must emerge as a result of exploration and analysis where a human analyst plays the key role. Appropriate visual representations of movement data and outcomes from automated analysis procedures are paramount for this process.
The presentation gives an overview of how to analyse such data. For selected tasks, we propose scalable visual analytics methods. The work of the methods is illustrated using several examples of real-world datasets significantly differing in their properties
We analyse to what extent these and other existing methods cover the space of the types of movement data and the possible analysis tasks, identify the remaining gaps, and outline the directions for the future research.
Further details can be found in the forthcoming book Visual Analytics of Movement (Springer, 2013):
Senast uppdaterad: Mon Aug 05 10:52:04 CEST 2013