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dc.contributor.authorCobos, Marlon E.
dc.contributor.authorJiménez, Laura
dc.contributor.authorNuñez-Penichet, Claudia
dc.contributor.authorRomero-Alvarez, Daniel
dc.contributor.authorSimões, Marianna
dc.identifier.citationCobos, M.E., Jiménez, L., Nuñez-Penichet, C., Romero-Alvarez, D., Simoes, M. 2018. Sample data and training modules for cleaning biodiversity information. Biodiversity Informatics 13:49–50.
dc.descriptionThis presentation was given as part of the GIS Day@KU symposium on November 14, 2018. For more information about GIS Day@KU activities, please see
dc.description.abstractThe recent appreciation of rapid global losses of biodiversity has created a growing demand for quick and reliable access to high-quality primary biodiversity data, essential for conservation and evolutionary science, among other applications. As a consequence, biodiversity databases have become increasingly available, allowing large-scale assessment of patterns and processes influencing the evolution of life on Earth. However, data quantity is often compromised by low data quality, and, even though working with plenty of records could be tempting, building ecological models with inaccurate data mislead researchers in driving conclusions about reality. The most common types of errors in biodiversity data are those related to georeferencing, which vary from obvious to barely noticeable, making them challenging to recognize. Fortunately, Geographic Information Systems (GIS) have increasingly allowed identification of georeferencing mistakes. Here, we provide a hands-on exercise for data cleaning that allows easy and prompt detection of inaccurate information. We focus on the use of GIS software for fixing problems related to the geographic coordinates of the data, such as changes in the order or the sign of latitude-longitude values, and records placed outside the study region, or outside continents.en_US
dc.description.sponsorshipPLATINUM SPONSORS: KU Department of Geography and Atmospheric Science KU Institute for Policy & Social Research

GOLD SPONSORS: KU Libraries State of Kansas Data Access & Support Center (DASC)

SILVER SPONSORS: Bartlett & West Kansas Applied Remote Sensing Program KU Center for Global and International Studies

dc.publisherGIS Day @ KU Planning Committeeen_US
dc.subjectGIS Dayen_US
dc.titleSample Data and Training Modules for Cleaning Biodiversity Informationen_US
kusw.kuauthorJiménez, Laura
kusw.kudepartmentEcology and Evolutionary Biologyen_US

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