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Journal Article

Big-Data-Ansätze für die schnelle Extraktion relevanter Informationen und Muster aus großen Datenmengen

Authors
/persons/resource/sips

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

/persons/resource/danschef

Scheffler,  D.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;

/persons/resource/trawald

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

/persons/resource/eggi

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

/persons/resource/hollstei

Hollstein,  Andre
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;

/persons/resource/segl

Segl,  K.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
Vol. 8, Issue 1 (2018), GFZ Journal 2018, System Erde : GFZ Journal, Deutsches GeoForschungsZentrum;

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Fulltext (public)

GFZ_syserde.08.01.6.pdf
(Publisher version), 650KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Sips, M., Scheffler, D., Rawald, T., Eggert, D., Hollstein, A., Segl, K. (2018): Big-Data-Ansätze für die schnelle Extraktion relevanter Informationen und Muster aus großen Datenmengen. - System Erde, 8, 1, 40-45.
https://doi.org/10.2312/GFZ.syserde.08.01.6


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_3543899
Abstract
Progress in sensor systems and computer simulation create large volumes of data with a variety of parameters. This development brings Big Data and the related challenges for data processing and data analysis also into the focus of geoscience. Computer science has developed concepts and technologies to handle Big Data. Geoscience can benefit from them since they facilitate efficient information extraction from big data, such as data from satellite-based remote sensing systems, or data from seismological or meteorological observation systems. To make use of computer science concepts and technologies, they have to be adapted into geoscience. Examples for this adaption are the development of efficient scalable geoscientific analysis methods by applying the divide-and-recombine concept, or the adaption of geoscientific methods to existing Big Data technologies.