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The need for standardisation in life science research - an approach to excellence and trust.

  • Hollmann, Susanne1, 2
  • Kremer, Andreas3
  • Baebler, Špela4
  • Trefois, Christophe5
  • Gruden, Kristina4
  • Rudnicki, Witold R.6
  • Tong, Weida7
  • Gruca, Aleksandra8
  • Bongcam-Rudloff, Erik9
  • Evelo, Chris T.10, 11
  • Nechyporenko, Alina12
  • Frohme, Marcus13
  • Šafránek, David14
  • Regierer, Babette2, 15
  • D'Elia, Domenica16
  • 1 Faculty of Science, University of Potsdam, Potsdam, Brandenburg, 14476, Germany
  • 2 SB Science Management UG (Haftungsbeschränkt), Berlin, Berlin, 12163, Germany
  • 3 Information Technology for Translational Medicine S.A. ITTM S.A., Esch-sur-Alzette, Esch, 4354, Luxembourg
  • 4 Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, 1000, Slovenia
  • 5 Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, 4367, Luxembourg
  • 6 Institute of Computer Science, University of Białystok, Białystok, 15-328, Poland
  • 7 Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, Jefferson, USA
  • 8 Department of Computer Networks and Systems, Silesian University of Technology, Gliwice, 44-100, Poland
  • 9 Department of Animal Breeding and Genetics, Bioinformatics section, University of Agricultural Sciences, Uppsala, 750 07, Sweden
  • 10 Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, 6229 ER, The Netherlands
  • 11 Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, 6229 ER, The Netherlands
  • 12 Department of Systems Engineering, Kharkiv National University of Radio Electronics, Kharkiv Oblast, 61000, Ukraine
  • 13 Division Molecular Biotechnology and Functional Genomics, Technical University of Applied Sciences Wildau, Wildau, Brandenburg, 15745, Germany
  • 14 Masaryk University, Brno, 601 77, Czech Republic
  • 15 Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Großbeeren, Brandenburg, 14979, Germany
  • 16 Institute for Biomedical Technologies, National Research Council, Italy, Bari, 70126, Italy
Published Article
"F1000 Research, Ltd."
Publication Date
May 10, 2021
DOI: 10.12688/f1000research.27500.2
PMID: 33604028
PMCID: PMC7863991
PubMed Central
  • Articles


Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However  for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.

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