Visualizing and animating large-scale spatiotemporal data with ELBAR explorer

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.

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Official URL: http://ceur-ws.org/Vol-1272/paper_126.pdf

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.

Item Type: Book Section
Additional Information: Poster/Paper originally presented at the 2014 International Conference on Posters & Demonstrations Track : 13th International Semantic Web Conference, Riva del Garda, Italy, October 21, 2014. Book series ISSN : 1613-0073
Departments: Faculty of Science, Technology and Arts > Computing
Depositing User: Suvodeep Mazumdar
Date Deposited: 19 Jan 2018 11:46
Last Modified: 28 Jan 2018 03:53
URI: http://shura.shu.ac.uk/id/eprint/16896

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