Ten simple rules for a successful cross-disciplinary collaboration

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Bernhartd Knapp
  • Rémi Bardenet
  • Miguel O Bernabeu
  • Rafael Bordas
  • Marina Bruna
  • Ben Calderhead
  • Jonathan Cooper
  • Alexander G Fletcher
  • Derek Groen
  • Bram Kuijper
  • Joanna Lewis
  • Gregg McInemy
  • Minssen, Timo
  • James Osborne
  • Verena Paulitschke
  • Joe Pitt-Francis
  • Jelena Todoric
  • Christian A Yates
  • David Gavaghan
  • Charlotte M Deane
Cross-disciplinary collaborations have become an increasingly important part of science. They are seen as a key factor for finding solutions to pressing societal challenges on a global scale including green technologies, sustainable food production and drug development. This has also been realized by regulators and policy-makers, as it is reflected in the 80 billion Euro "Horizon 2020" EU Framework Programme for Research and Innovation. This programme puts special emphasis at breaking down barriers between fields to create a path breaking environment for knowledge, research and innovation.

However, igniting and successfully maintaining cross-disciplinary collaborations can be a delicate task. In this article we focus on the specific challenges associated with cross-disciplinary research in particular from the perspective of the theoretician. As research fellows of the 2020 Science project (http://www.2020science.net) and collaboration partners, we bring broad experience of developing interdisciplinary collaborations [2–12]. We intend this guide for early career computational researchers as well as more senior scientists who are entering a cross disciplinary setting for the first time. We describe the key benefits, as well as some possible pitfalls, arising from collaborations between scientists with backgrounds in very different fields.

This paper has inter alia been cited by Times Higher education: http://www.timeshighereducation.co.uk/news/people/the-secrets-to-successful-interdisciplinary-work/2020267.article .
TidsskriftPLoS Computational Biology
Udgave nummer4
Antal sider4
StatusUdgivet - 30 apr. 2015

ID: 110234360