Sample data and training modules for cleaning biodiversity information

Large-scale biodiversity databases have become crucial information sources in many analyses in biogeography, macroecology, and conservation biology, often involving development of empirical models of species’ ecological niches and predictions of their geographic distributions. These analyses, howeve...

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Bibliographic Details
Published inBiodiversity informatics Vol. 13; pp. 49 - 50
Main Authors Cobos, Marlon E, Jiménez, Laura, Nuñez-Penichet, Claudia, Romero-Alvarez, Daniel, Simoes, Marianna
Format Journal Article
LanguageEnglish
Published 24.10.2018
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Summary:Large-scale biodiversity databases have become crucial information sources in many analyses in biogeography, macroecology, and conservation biology, often involving development of empirical models of species’ ecological niches and predictions of their geographic distributions. These analyses, however, can be impaired by the presence of errors, particularly as regards taxonomic identifications and accurate geographic coordinates. Here, we present a detailed data-cleaning exercise based on two contrasting datasets; we link these example data with a step-by-step guide to overcoming these problems and improving data quality for analyses based on these data.
ISSN:1546-9735
1546-9735
DOI:10.17161/bi.v13i0.7600