Many research communities working in biology and related fields are deeply interested in having a wide collection of environmental and species distribution data. Obviously, for these communities to be able to carry out their studies in a fast and efficient manner, these data need to be well organized, meticulously described and possibly represented in a standard format that allows for a direct usage. In fact, being the final goal of these communities to extract information from the data and applying some kind of data processing workflows, cutting down the data preparation and preprocessing time is key. This is the main reason that triggered the activity presented in this paper that aimed at converting the whole collection of 10,385 species distribution models published by the AquaMaps consortium (AquaMaps Native Distributions) into NetCDF files, creating a re-usable, portable and self-describing collection of native habitat datasets.

A collection of aquamaps native layers in NetCDF format

Scarponi P;Coro G;Pagano P
2018

Abstract

Many research communities working in biology and related fields are deeply interested in having a wide collection of environmental and species distribution data. Obviously, for these communities to be able to carry out their studies in a fast and efficient manner, these data need to be well organized, meticulously described and possibly represented in a standard format that allows for a direct usage. In fact, being the final goal of these communities to extract information from the data and applying some kind of data processing workflows, cutting down the data preparation and preprocessing time is key. This is the main reason that triggered the activity presented in this paper that aimed at converting the whole collection of 10,385 species distribution models published by the AquaMaps consortium (AquaMaps Native Distributions) into NetCDF files, creating a re-usable, portable and self-describing collection of native habitat datasets.
2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
17
292
296
6
https://www.sciencedirect.com/science/article/pii/S2352340918300295
Sì, ma tipo non specificato
Big Data
Ecological Modelling
Ecological Niche Modelling
Statistics
Cloud computing
GIS
Raster Data
Available online 31 January 2018
3
info:eu-repo/semantics/article
262
Scarponi, P; Coro, G; Pagano, P
01 Contributo su Rivista::01.01 Articolo in rivista
open
   Building Research environments for fostering Innovation, Decision making, Governance and Education to support Blue growth
   BlueBRIDGE
   H2020
   675680
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/374127
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