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

Susanne Hollmann*, Andreas Kremer, Špela Baebler, Christophe Trefois, Kristina Gruden, Witold R Rudnicki, Weida Tong, Aleksandra Gruca, Erik Bongcam-Rudloff, Chris T Evelo, Alina Nechyporenko, Marcus Frohme, David Šafránek, Babette Regierer, Domenica D'Elia

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.

Original languageEnglish
Pages (from-to)1398
Publication statusPublished - 2020

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