During the last years, considerable progresses have been made in developing on-line species occurrence databases. These are crucial in environmental and agricultural challenges, e.g., they are a basic element in the generation of species distribution models. Unfortunately, their exploitation is still difficult and time consuming for many scientists. No database currently exists that can claim to host, and make available in a seamless way, all the species occurrence data needed by the ecology scientific community. Occurrence data are scattered among several databases and information systems. It is not easy to retrieve records from them, because of differences in the adopted protocols, formats and granularity. Once collected, datasets have to be selected, homogenised and pre-processed before being ready-to-use in scientific analysis and modelling. This paper introduces a set of facilities offered by the D4Science Data Infrastructure to support these phases of the scientific process. It also exemplifies how they contribute to reduce the time spent in data quality assessment and curation thus improving the overall performance of the scientific investigation.

An infrastructure-oriented approach for supporting biodiversity research

Candela L;Castelli D;Coro G;Lelii L;Mangiacrapa F;Marioli V;Pagano P
2014

Abstract

During the last years, considerable progresses have been made in developing on-line species occurrence databases. These are crucial in environmental and agricultural challenges, e.g., they are a basic element in the generation of species distribution models. Unfortunately, their exploitation is still difficult and time consuming for many scientists. No database currently exists that can claim to host, and make available in a seamless way, all the species occurrence data needed by the ecology scientific community. Occurrence data are scattered among several databases and information systems. It is not easy to retrieve records from them, because of differences in the adopted protocols, formats and granularity. Once collected, datasets have to be selected, homogenised and pre-processed before being ready-to-use in scientific analysis and modelling. This paper introduces a set of facilities offered by the D4Science Data Infrastructure to support these phases of the scientific process. It also exemplifies how they contribute to reduce the time spent in data quality assessment and curation thus improving the overall performance of the scientific investigation.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Data Integration
Data Sharing
Data Processing
Species Occurrence Data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/298055
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