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Document
Computer Science Meets Ecology (Dagstuhl Seminar 17091)

Authors: Gustau Camps-Valls, Thomas Hickler, and Birgitta König-Ries

Published in: Dagstuhl Reports, Volume 7, Issue 2 (2017)


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.

Cite as

Gustau Camps-Valls, Thomas Hickler, and Birgitta König-Ries. Computer Science Meets Ecology (Dagstuhl Seminar 17091). In Dagstuhl Reports, Volume 7, Issue 2, pp. 109-134, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@Article{campsvalls_et_al:DagRep.7.2.109,
  author =	{Camps-Valls, Gustau and Hickler, Thomas and K\"{o}nig-Ries, Birgitta},
  title =	{{Computer Science Meets Ecology (Dagstuhl Seminar 17091)}},
  pages =	{109--134},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{7},
  number =	{2},
  editor =	{Camps-Valls, Gustau and Hickler, Thomas and K\"{o}nig-Ries, Birgitta},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.2.109},
  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}
}
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