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The University of Kansas’ Biodiversity Institute joins DataONE as a Member Node

Thursday, February 20, 2014

DataONE further extends the provision of biodiversity informatics, systematics and ecology and evolutionary biology data with the recent addition of the University of Kansas’ Biodiversity Institute (KUBI) Member Node. The KUBI brings its focus on biodiversity education, research, documentation and service to support DataONE’s vision to enable “researchers, educators, and the public to better understand and conserve life on earth and the environment that sustains it”. As one of 18 Member Nodes currently participating in DataONE, the KUBI MN contributes to over 135,000 diverse data objects curated by institutions across North America, Africa, and Asia that are discoverable through ONEMercury, the DataONE search tool. More information about KUBI and other DataONE Member Nodes can be found at http://www.dataone.org/current-member-nodes

About KUBI: The University of Kansas Biodiversity Institute studies the life of the planet for the benefit of the Earth and its inhabitants. With a globally-sourced collection of more than 8 million plants and animals, the Institute accomplishes its mission by employing its specimens for university and public education and research. Its biological museum software, Specify (www.specifysoftware.org), is used in 500 biological collections to manage research data associated with specimens, and the KUBI’s Lifemapper Project (www.lifemapper.org) is a computational platform which forecasts the impact of climate change on species ranges and global patterns of biological diversity, and is the basis for a secondary school curriculum on the biological impacts of global climate change.

About DataONE: DataONE enables universal access to data and also facilitates researchers in fulfilling their need for data management and in providing secure and permanent access to their data. These needs are filled by offering the scientific community a suite of tools and training materials that cover all aspects of the data life-cycle; from data collection to management, analysis and publication.