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Journal Article

Challenges and strategies for the visual exploration of complex environmental data

Authors

Helbig,  Carolin
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/persons/resource/dransch

Dransch,  D.
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Böttinger,  Michael
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Devey,  Colin
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Haas,  Antonie
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Hlawitschka,  Mario
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Kuenzer,  Claudia
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Rink,  Karsten
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Schäfer-Neth,  Christian
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Scheuermann,  Gerik
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Kwasnitschka,  Tom
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/persons/resource/unger

Unger,  A.
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Citation

Helbig, C., Dransch, D., Böttinger, M., Devey, C., Haas, A., Hlawitschka, M., Kuenzer, C., Rink, K., Schäfer-Neth, C., Scheuermann, G., Kwasnitschka, T., Unger, A. (2017): Challenges and strategies for the visual exploration of complex environmental data. - International Journal of Digital Earth, 10, 10, 1070-1076.
https://doi.org/10.1080/17538947.2017.1327618


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_2230908
Abstract
In this opinion paper, we, a group of scientists from environmental-, geo-, ocean- and information science, argue visual data exploration should become a common analytics approach in Earth system science due to its potential for analysis and interpretation of large and complex spatio-temporal data. We discuss the challenges that appear such as synthesis of heterogeneous data from various sources, reducing the amount of information and facilitating multidisciplinary, collaborative research. We argue that to fully exploit the potential of visual data exploration, several bottlenecks and challenges have to be addressed: providing an efficient data management and an integrated modular workflow, developing and applying suitable visual exploration concepts and methods with the help of effective and tailored tools as well as generating and raising the awareness of visual data exploration and education. We are convinced visual data exploration is worth the effort since it significantly facilitates insight into environmental data and derivation of knowledge from it.