Morik/etal/2017a: Big Data Science

Bibtype Inproceedings
Bibkey Morik/etal/2017a
Author Morik, Katharina and Bockermann, Christian and Buschjäger, Sebastian
Ls8autor Bockermann, Christian
Buschjäger, Sebastian
Morik, Katharina
Title Big Data Science
Booktitle German Conference on Artificial Intelligence (KI 2017)
Volume 32
Number 1
Pages 27--36
Abstract In ever more disciplines, science is driven by data, which leads to data analytics becoming a primary skill for researchers. This includes the complete process from data acquisition at sensors, over pre-processing and feature extraction to the use and application of machine learning. Sensors here often produce a plethora of data that needs to be dealt with in near-realtime, which requires a combined effort of implementations at the hardware level to high-level design of data flows. In this paper we outline two use-cases of this wide span of data analysis for science in a real-world example in astroparticle physics. We outline a high-level design approach which is capable of defining the complete data flow from sensor hardware to final analysis.
Month 12
Year 2017
Projekt SFB876-A1,SFB876-C3
Url https://doi.org/10.1007/s13218-017-0522-8

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