Winner of DLN FAIR data award 2021

Centre for Digital Life Norway is thrilled to congratulate Ingvild Bjerke from the University of Oslo as winner of the first DLN FAIR data award 2021!  

To highlight leading examples of FAIR data management in Norwegian life science research, Centre for Digital Life Norway (DLN) announced the first DLN FAIR data award.

The ten nominations received for the award were from a diverse range of disciplines. DLN is very inspired to see the many cases of FAIR data management in our research environments.

The winner, Ingvild Bjerke, impressed the evaluation committee by showing a substantial effort in providing extensive sets of neuroscientific data FAIR through the EBRAINS infrastructure.

The committee found the metadata extensive and comprehensive, providing explanations of the experiment scope, methods, technical specifications (and errors), resulting data, and data correlation and analysis. Community standard vocabularies were implemented, and references to connected objects were provided. Finally, basic FAIR data features, such as persistent identifiers and licensing of data, were assigned.


The winner Ingvild Bjerke


From the winner, Ingvild Bjerke:

I am a postdoctoral researcher in the Neural Systems Laboratory (University of Oslo) combining my studies of the normal mouse brain development with neuroinformatics and digital atlasing. I am passionate about the open science movement and FAIR research, and strive to make all data from my research public. The datasets that received the FAIR data award are part of ongoing projects in our laboratory mapping the number and distribution of specific cell types in the developing and adult rodent brain using immunohistochemistry, digital brain atlases, and semi-automated workflows for quantification of labelled cells. We are hoping that these data, openly shared through the EBRAINS research infrastructure, will provide a lasting contribution to the neuroscience community. 







The data that rewarded Ingvild Bjerke and her colleagues this award:

  • Bjerke, I. E., & Leergaard, T. B. (2020). Distribution of calbindin positive neurons in the normal adult mouse brain [Data set]. EBRAINS. 
  • Bjerke, I. E., Yates, S. C., Puchades, M., Bjaalie, J. G., & Leergaard, T. B. (2020). Brain-wide quantitative data on calbindin positive neurons in the mouse [Data set]. EBRAINS.
  • Cullity, E. R., Bjerke, I. E., Kjelsberg, K., Leergaard, T. B., & Kim, J. H. (2020). Distribution of dopamine 1 receptor positive neurons in the adult female mouse brain [Data set]. EBRAINS.

About the evaluation:

The evaluation committee consisted of Kjersti Hasle Enerstvedt (Senior academic librarian, University of Bergen Library), Rasmus Kvaal Wardemann (PhD candidate in the FAIR principles, University of Vienna), Susanna Röblitz (Professor at Computational Biology Unit, UiB), Korbinian Bösl (ELIXIR Norway and DLN) and Marta Eide (DLN). We are particularly thankful for the external members active and thorough participation in evaluating the nominated candidates.

In order to evaluate the efforts of the FAIR data management, and not only the repository features, the committee manually evaluated the data sets as based on the Go-FAIR and FAIR-plus indicators. 


About FAIR data:

FAIR data management aims to increase the reuse and impact of research data and is an important part of the Open Science initiative. FAIR principles encourage making data Findable, Accessible, Interoperable and Reusable. This allows a wider community to use existing data and facilitate knowledge discovery. Following the principle of “as open as possible, as closed as necessary”, FAIR data should always be interoperable and reusable, but cannot always be possible to access openly (for example, patient sensitive data cannot be directly accessible, but it should be possible to know how to obtain access for specific research questions).

Published Feb. 23, 2022 4:12 PM - Last modified Feb. 24, 2022 10:08 AM