Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. In order to further promote the diffusion of such an approach it is fundamental to develop a flexible, comprehensive, and robust environment enabling practitioners to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data and services. We describe an approach to species distribution modeling based on the D4Science Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud), by discussing the services needed to support the phases of such a complex process.

IMARINE - Cloud Computing for Ecological Modeling in the D4Science Infrastructure

Pagano P;Coro G;Castelli D;Candela L;Sinibaldi F
2013

Abstract

Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. In order to further promote the diffusion of such an approach it is fundamental to develop a flexible, comprehensive, and robust environment enabling practitioners to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data and services. We describe an approach to species distribution modeling based on the D4Science Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud), by discussing the services needed to support the phases of such a complex process.
2013
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Ecological Modeling
Cloud Computing
H.3.7 Digital Libraries
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/254489
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