License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.7.2.109
URN: urn:nbn:de:0030-drops-73567
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/7356/
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Camps-Valls, Gustau ; Hickler, Thomas ; König-Ries, Birgitta
Weitere Beteiligte (Hrsg. etc.): Gustau Camps-Valls and Thomas Hickler and Birgitta König-Ries

Computer Science Meets Ecology (Dagstuhl Seminar 17091)

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dagrep_v007_i002_p109_s17091.pdf (0.7 MB)

Abstract

This report summarizes the program and main outcomes of the Dagstuhl Seminar 17091 entitled ``Computer Science Meets Ecolog''. Ecology is a discipline that poses many challenging problems involving big data collection, provenance and integration, as well as difficulties in data analysis, prediction and understanding. All these issues are precisely the arena where computer science is concerned. The seminar motivation was rooted in the belief that ecology could largely benefit from modern computer science. The seminar attracted scientists from both fields who discussed important topics in ecology (e.g. botany, animal science, biogeochemistry) and how to approach them with machine learning, computer vision, pattern recognition and data mining. A set of specific problems and techniques were treated, and the main building blocks were set up. The important topics of education, outreach, data and models accessibility were also touched upon. The seminar proposed a distinctive perspective by promoting cross-fertilization in a unique environment and a unique set of individuals.

BibTeX - Entry

@Article{campsvalls_et_al:DR:2017:7356,
  author =	{Gustau Camps-Valls and Thomas Hickler and Birgitta K{\"o}nig-Ries},
  title =	{{Computer Science Meets Ecology (Dagstuhl Seminar 17091)}},
  pages =	{109--134},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{7},
  number =	{2},
  editor =	{Gustau Camps-Valls and Thomas Hickler and Birgitta K{\"o}nig-Ries},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/7356},
  URN =		{urn:nbn:de:0030-drops-73567},
  doi =		{10.4230/DagRep.7.2.109},
  annote =	{Keywords: ecology, biodiversity, earth observation, earth system, remote sensing, computer science, citizen science, big data, data integration, modeling, sema}
}

Keywords: ecology, biodiversity, earth observation, earth system, remote sensing, computer science, citizen science, big data, data integration, modeling, sema
Collection: Dagstuhl Reports, Volume 7, Issue 2
Issue Date: 2017
Date of publication: 20.09.2017

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