Visualizing and Animating Large-scale Spatiotemporal Data
Research summary
Visual exploration of data enables users and analysts observe interesting patterns that can trigger new research for further investigation. With the increasing availability of Linked Data, facilitating support for making sense of the data via visual exploration tools for hypothesis generation is critical. Time and space play important roles in this because of their ability to illustrate dynamicity, from a spatial context. Yet, Linked Data visualization approaches typically have not made efficient use of time and space together, apart from typical rather static multivisualization approaches and mashups. We developed ELBAR explorer that visualizes a vast amount of scientific observational data about the Brazilian Amazon Rainforest. The core contribution is a novel mechanism for animating between the different observed values, thus illustrating the observed changes themselves.
Description
ELBAR explorer employs generic visualization and animation techniques to support analysts and decision makers explore spatial and temporal data. We provided a demonstration of the system and the architecture, along with a description of the data. This was accompanied with a guided example of how such techniques can be used. We also invite other interested organizations to work with us to build custom transitions on other interesting datasets.
Future work will include development and evaluation of ELBAR with different kinds of spatiotemporal data. Moreover, we investigate other novel mechanisms for exploring the spatiotemporal and topical aspects of Linked Data. We foresee the potential for the use of the community is the expansion of the background data, such as census data from individual municipalities and other authorities could support for gaining insight of social, economical and ecological processes.
More information
Research info
Research title
Visualizing and Animating Large-scale Spatiotemporal Data
Research timeline
1.5.2015 - 1.11.2015
Region
Latin America
Countries
Brazil, Finland
Institution
Aalto University
Department of Computer Science
Espoo, Finland
Funding instrument
Other
Project budget
0 - 200,000 euros
Head of research
Tomi Kauppinen
Research team
Tomi Kauppinen, Suvodeep Mazumdar
Partners
University of Sheffield, University of Bremen, Aalto University
Contact information
Tomi Kauppinen
tomi.kauppinen@aalto.fi
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Record last updated
23.10.2015