Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally it is recognised that data are meaningless unless their provenance is preserved, through appropriate meta-data. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation, control of experiment or data-collection and that which analyses, modifies and draws value from raw data. In order to meet the aims of reproducibility we argue that data management alone is insufficient: it must be accompanied by good software practices, the training to facilitate it and the support of stakeholders, including appropriate recognition for software as a research output.
Original languageEnglish
Article number3
Pages (from-to)1-6
Number of pages6
JournalData Science Journal
Issue number1
Publication statusPublished - 22 Jan 2020
EventGöttingen-CODATA RDM Symposium 2018 - University of Gottingen, Gottingen, Germany
Duration: 18 Mar 201820 Mar 2018


  • data management
  • software management
  • Reproducibility
  • research software engineering

ASJC Scopus subject areas

  • General


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