What is responsible and sustainable data science?

Linnet Taylor*, Nadezhda Purtova

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


In the expansion of health ecosystems, issues of responsibility and sustainability of the data science involved are central. The idea that these values should be central to the practice of data science is increasingly gaining traction, yet there is no agreement on what exactly makes data science responsible or sustainable because these concepts prove slippery when applied to a global field involving commercial, academic and governmental actors. This lack of clarity is causing problems in setting goals and boundaries for data scientific practice, and risks fundamental disagreement on governance principles for this emerging field. We will argue in this commentary for a commons analytical framework as one approach to this problem, since it offers useful signposts for how to establish governance principles for shared resources.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalBig Data & Society
Issue number2
Publication statusPublished - Jul 2019


  • Commons
  • health
  • responsibility
  • ethics
  • privacy
  • data protection


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