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Visual Analytics : eine interaktive Methode für die Interpretation geowissenschaftlicher Daten

Urheber*innen
/persons/resource/unger

Unger,  A.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/dransch

Dransch,  D.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/janisj

Jatnieks,  Janis
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/sips

Sips,  M.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
1.5 Geoinformatics, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/ndraeger

Dräger,  N.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
5.2 Climate Dynamics and Landscape Evolution, 5.0 Geoarchives, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/brau

Brauer,  A.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
5.2 Climate Dynamics and Landscape Evolution, 5.0 Geoarchives, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/volkerk

Klemann,  V.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
1.3 Earth System Modelling, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/kempka

Kempka,  T.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
3.4 Fluid Systems Modelling, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/delucia

De Lucia,  M.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
3.4 Fluid Systems Modelling, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/mkuehn

Kühn,  M.
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;
3.4 Fluid Systems Modelling, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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GFZ_syserde.08.01.4.pdf
(Verlagsversion), 454KB

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Zitation

Unger, A., Dransch, D., Jatnieks, J., Sips, M., Dräger, N., Brauer, A., Klemann, V., Kempka, T., De Lucia, M., Kühn, M. (2018): Visual Analytics: eine interaktive Methode für die Interpretation geowissenschaftlicher Daten. - System Erde, 8, 1, 26-31.
https://doi.org/10.2312/GFZ.syserde.08.01.4


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_3543891
Zusammenfassung
Visual Analytics is a method that combines visualization and automated analysis in highly interactive interfaces. These systems enable geoscientists to explore their data sets, to steer the analysis process and assess results. In this article, we explain the potential of Visual Analytics with three examples that were developed at the GFZ in recent years in close cooperation between computer scientists and geoscientists. They include (1) the analysis of lake sediments to understand climate and landscape developments in the past, (2) the analysis of complex geochemical simulation models in fluid systems modeling, and (3) the validation of simulation models in Earth system modeling. The developed Visual Analytics concepts largely differ from each other due to the variety of analytical tasks and data characteristics across the applications. Nevertheless, the examples reveal common benefits of using Visual Analytics for data interpretation in geoscientific research. The method supports the full exploration of complex data sets rather than relying on small sample sets. Geoscientists can employ their expert knowledge to correctly interpret data where automatic methods alone are not sufficient. Yet, the close linking with automated methods enables the handling of large and complex data sets. In sum, the novel Visual Analytics concepts contribute to data interpretation and thereby to answering relevant geoscientific questions.