|Title / Titel||AniMOVE: animated visual analytics of movement|
|Abstract (PDF, 14 KB)|
|Summary / Zusammenfassung||With increasing interest in and use of dynamic depictions to present and explore complex spatiotemporal data, the research community has developed sophisticated visual analytics (VA) tools for experts coupled often with animated displays to mine databases of spatio-temporal patterns. The contended advantage of VA is the combination of computational methods with the outstanding human capabilities for pattern recognition, imagination, association, and analytical reasoning. However, this claim has not yet been supported by empirical evidence. We still know very little on how exactly dynamic and animated displays are understood by users. As VA tools are being created and disseminated, it will be important to specifically consider research on the kind of information that users can get from dynamic and animated displays. The (limited) perceptual and cognitive systems of the users will determine the salience of the patterns, and this will ultimately determine how effective they will be in detecting and reasoning about spatio-temporal phenomena.
The proposed work is firstly aimed at better understanding of how users explore and extract knowledge from dynamic (interactive) and animated visual analytics (VA) displays including moving objects, and secondly, at deriving empirically based design guidelines for the construction of cognitively adequate animations for the effective and efficient depiction and visual analysis of time-referenced spatial data sets at high resolution. We aim at guidelines that are generic enough to be useful for all types of moving entity types, including various geographically relevant application domains (e.g., human trajectories and lifelines tracked with location-based services, habitat analyses with tagged animals in wildlife biology, eye movements analyses in geographic visualization experiments, etc.).
Key outputs are expected along three cyclic work phases. First, knowledge integration across complementary research fields is carried out at the theoretical level (event perception, space-time cognition, and animation design). Second, an experimental VA platform is implemented, and thirdly, interaction methods and animated displays are evaluated with users (i.e., empirical evaluation of usefulness and usability).
With the results of this work we hope to provide perceptually salient and cognitively inspired animated displays that enable humans to more effectively and efficiently detect relationships in complex space-time data displays for effective and efficient spatio-temporal decision-making.
|Publications / Publikationen||Weitere Informationen|
|Keywords / Suchbegriffe||space-time, visual analytics, empirical evaluation, animation|
|Project leadership and contacts /
Projektleitung und Kontakte
|Other links to external web pages||http://p3.snf.ch/Project-134646|
|Funding source(s) /
|SNF (Personen- und Projektförderung)
|In collaboration with /
In Zusammenarbeit mit
|Duration of Project / Projektdauer||Jan 2013 to Jan 2015|