Dag Endresen

Senior Engineer - Geo-Ecology Research Group
Image of Dag Endresen
Norwegian version of this page
Phone +47-22851654
Mobile phone +47-40612982
Room 412
Username
Visiting address Geological Museum
Postal address Postboks 1172, Blindern 0318 OSLO

Academic interests

I am the manager for the Norwegian participant node of the Global Biodiversity Information Facility (GBIF). The secretariat for GBIF Norway is hosted by the Natural History Museum of the University in Oslo. I provide support and teaching related to geographic information management and predictive modeling of biodiversity information resources. My academic interests include biodiversity informatics, including data publishing standards, knowledge organization systems and geographic information management; and predictive modeling of biodiversity data in an ecological setting, including modeling of traits useful for plant breeding programs in agriculture.

Background

Before joining the Natural History Museum in Oslo and GBIF Norway, I was the Knowledge Systems Engineer at the GBIF secretariat. I also have previous experience as the GBIF Node Manager for the Nordic Genetic Resources Center (NordGen) from 2004 to 2010 and as the vice chair of the GBIF Nodes Committee between 2006 and 2010. At the Nordic Gene Bank (NGB) and Nordic Genetic Resources Center (NordGen, Alnarp, Sweden) I was the IT manager and responsible for documentation of plant genetic resources. My Ph.D. research at Copenhagen University (KU LIFE, Denmark) was organized in close collaboration with Bioversity International (CGIAR, Rome, Italy), the International Center for Agricultural Research in Dry Areas (ICARDA, CGIAR, Aleppo, Syria) and NordGen. My research contributed to a new approach for “focused identification of germplasm strategy” (FIGS) using predictive computer modeling methods to identify useful genetic resources. The FIGS approach identifies and utilizes a predictive link between the environmental patterns and ecology of locations where traditional cultivars and landraces where developed during long-term farming and target trait properties of interest for plant breeding and crop research programs. By using such predictive models we can substantially reduce the number of cultivars crop scientists need to screen to identify novel genetic diversity required to maintain and improve food crops.

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Published Oct. 10, 2012 5:33 PM - Last modified Nov. 28, 2014 8:48 AM

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