MAZUMDAR, Suvodeep and KAUPPINEN, Tomi (2014). Visualizing and animating large-scale spatiotemporal data with ELBAR explorer. In: HORRIDGE, Matthew, ROSPOCHER, Marco and VAN OSSENBRUGGER, Jacco, (eds.) Proceedings of the ISWC 2014 Posters & Demonstrations Track. CEUR Workshop Proceedings (1272). CEUR Workshop Proceedings, 161-164. [Book Section]
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Mazumdar-VisualizingAndAnimatingLarge-ScaleSpatiotemporalDate(VoR).pdf - Published Version
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Mazumdar-VisualizingAndAnimatingLarge-ScaleSpatiotemporalDate(VoR).pdf - Published Version
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Abstract
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. In this paper we demonstrate
ELBAR explorer that visualizes a vast amount of scientific observational
data about the Brazilian Amazon Rainforest. Our core contribution is
a novel mechanism for animating between the di↵erent observed values,
thus illustrating the observed changes themselves.
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