New report offers recommendations on improving GBIF-mediated data for distribution modelling

Images 
Detail of global distribution map of Aedes aegypti, Kraemer MUG, Sinka ME, Duda KA et al (2015)

Detail of global distribution map of Aedes aegypti, Kraemer MUG, Sinka ME, Duda KA et al (2015) The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictuseLife 2015;4:e08347 doi:10.7554/eLife.08347.

A group of experts tasked with helping to improve the usefulness of GBIF-mobilized data for distribution modelling research have presented their insights in a just-published report.

The report draws on survey results from the distribution modelling research community and the group’s own views as well as input gathered at ‘Frontiers of Biodiversity Informatics and Modelling Species Distributions’. The November 2015 symposium and panel discussion hosted by the Center for Biodiversity and Conservation at the American Museum of Natural History was part of was part of a three-day working meeting for the task group, held at both AMNH and the City College of New York, City University of New York.

The task group’s recommendations call for GBIF to:

  • provide users with known indicators about data precision, quality and uncertainty
  • include features that enable users to annotate data errors or issues
  • help train and guide users on the appropriate uses and interpretations of the data

“Initiatives like GBIF demonstrate clearly the huge value of open access to primary data, both for science and policy making. However, there is room for improvement,” said Jorge Soberón, the task force chair. “Our group has made suggestions for data publishers, users and for GBIF, and we hope the ideas will contribute to improvements in the GBIF infrastructure for biodiversity modelling.”

The Secretariat is providing the distribution modelling user community with opportunities to provide feedback on the report (user registration required) and to share their specific use cases and experiences in working with GBIF-mediated data. For more information, contact Dmitry Schigel, GBIF programme officer for content analysis and use.