Published April 9, 2019 | Version v1

OPEN SCIENCE: SHARING DATA, TOOLS AND WORKFLOWS A STRATEGY TO INSPIRE EFFICIENT COLLABORATION

  • 1. Technical University of Denmark, Department of Wind Energy
  • 2. Technical University of Denmark

Description

The H2020 Work Programme is a milestone for the transition to Science 2.0: the era of  Open Science (OS) will increase the drive towards collaboration through knowledge sharing across the European Research Area.

In particular, the Open Data (OD) policy aims at making digital assets, i.e. data, tools and workflows FAIR (Findable, Accessible, Interoperable and Re-usable) [1]: available to everyone in Europe.

FAIR assets allow to reuse data in multiple applications which multiplies the data value thus optimizing the impact of projects funded by public money.  NO PANIC: to respect Industry foregrounds Research data must be as open as possible and as closed s necessary!

The wind energy community generally agrees that sharing assets would shorten the time from new ideas to innovation, making the work more efficient; BUT assets provide a competitive advantage, leading to a reluctance to sharing important data.  WHAT TO DO THEN?

We suggest a simple strategy to energize the free flow of information amongst the European wind energy stakeholders, increasing collaboration by sharing research data including data, software and workflows.

Notes

Poster Award in section Wind Energy Digitalization at the WindEurope 2019 Conference, Pamplona, 2-4 April 2019. The authors acknowledge DTU Wind Energy funding from the Cross-cutting actions on digitalization

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Additional details

Related works

Is supplemented by
10.5281/zenodo.1199489 (DOI)

Funding

European Commission
IRPWIND - Integrated Research Programme on Wind Energy 609795

References

  • Sempreviva, A. M., Vesth, A., Bak, C., Verelst, R. D., Giebel, G., Danielsen, K. H., et al. (2017). Taxonomy and metadata for wind energy Research & Development (p. 28).
  • Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016).