GBIF News

Collaboration aims at new journal option for biodiversity data publishers

A new collaboration aims to increase the options for researchers to gain visibility and recognition for biodiversity datasets published through the GBIF network.

GBIF is collaborating with the editors of Scientific Data, the new open access, online journal from Nature Publishing Group due to launch in May 2014.

The journal introduces a new type of content called the 'data descriptor', aimed at making scientifically valuable datasets more discoverable, interpretable and reusable.

Data descriptors closely resemble the data paper concept promoted by GBIF and Pensoft Publishers, and the collaboration will develop similar methods for authoring submissions to the new journal using the standard formats for metadata recommended for sharing data through the GBIF network.

The initiative was launched during a symposium at the recent Biodiversity Information Standards (TDWG) conference in Florence, Italy.

Susanna-Assunta Sansone, honorary academic editor of Scientific Data, explained: "We are exploring ways to help users of GBIF's Integrated Publishing Toolkit (IPT) submit data descriptors to Scientific Data, and ways to transfer important metadata between GBIF and Scientific Data."

In coming months, the collaboration will map data descriptors to the current GBIF metadata profile, and make the necessary adjustments to the IPT. The aim is to launch a call for submissions later in the year with a target of publishing the first GBIF-generated data descriptors in Scientific Data before the end of 2014.

The vice-chair of GBIF's Science Committee, Arturo Ariño, who chaired the symposium launching the initiative, commented: "The collaboration between GBIF and Scientific Data will bring interpretive research closer to the data that it uses. This will encourage other peer-reviewed journals to recognize data papers as a mechanism to incentivize data publishing."

For more details, contact:

GBIF Secretariat

Andrew Hufton, Managing Editor, Scientific Data.