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@INPROCEEDINGS{Gtz:281239,
author = {Götz, Markus},
title = {{P}ractice $\&$ {E}xperience with {S}calable {C}lustering
{A}lgorithms for {S}tatistical {E}arth {S}cience {D}ata
{M}ining},
reportid = {FZJ-2016-00938},
year = {2015},
abstract = {Big Data has plausibly reached the peak of its technology
“hype” cycle, at least in geosciences. For a new
technology to evolve, mature, and realize its maximum
potential, it must successfully survive the transition
through the ensuing "trough of disillusionment". Currently,
the term “Big Data” seems to be subject to
individuals’ interpretations, especially in a community
such as ours, i.e. Earth Science, which has had a long, if
not the longest, history in trying to use, and make sense
out of, large volumes of data. Therefore, we seek abstracts
in this session that can help the community 1) to better
define the Big Data challenges in Earth Science, 2) to
report and describe on-going or up-coming “Big Data”
practices, or 3) to identify the opportunities for
addressing the challenges and reaping benefits, with an aim
to focus our collective efforts on the challenges and
nurture the maturation of Big Data in Earth Science.},
month = {Apr},
date = {2015-04-12},
organization = {European Geosciences Union General
Assembly 2015, Vienna (Austria), 12 Apr
2015 - 17 Apr 2015},
subtyp = {Other},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {512 - Data-Intensive Science and Federated Computing
(POF3-512)},
pid = {G:(DE-HGF)POF3-512},
typ = {PUB:(DE-HGF)6},
url = {https://juser.fz-juelich.de/record/281239},
}