Abstract
Data-intensive science comes with increased risks concerning quality and reliability of data, and while trust in science has traditionally been framed as a matter of scientists being expected to adhere to certain technical and moral norms for behaviour, emerging discourses of open science present openness and transparency as substitutes for established trust mechanisms. By ensuring access to all available information, quality becomes a matter of informed judgement by the users, and trust no longer seems necessary. This strategy does not, however, take into consideration the networks of professionals already enabling data-intensive science by providing high-quality data. In the life sciences, biological data- and knowledge bases managed by expert biocurators have become crucial for data-intensive research. In this paper, I will use the case of biocurators to argue that openness and transparency will not diminish the need for trust in data-intensive science. On the contrary, data-intensive science requires a reconfiguration of existing trust mechanisms in order to include those who take care of and manage scientific data after its production.
Highlights
In 2010, the European Commision’s High-Level Group on Scientific Data stated that “[w]e are on the verge of a great new leap in scientific capability, fueled by data” (European Commission 2010, p. 9)
Terms like “datadriven science”, “data-intensive science”, and “e-science” are gaining traction within what is sometimes described as a paradigmatic shift in the conditions for knowledge production
The claims of a new and “theory-free” science generating knowledge from Big Data have been questioned by both scientists and philosophers of science (e.g., Kitchin 2014; Leonelli 2016), there are still enough changes taking place to warrant the label “data intensive” science
Summary
In 2010, the European Commision’s High-Level Group on Scientific Data stated that “[w]e are on the verge of a great new leap in scientific capability, fueled by data” (European Commission 2010, p. 9). I will use the example of biocurators to argue that data-intensive science requires not a dismissal, but a reconfiguration of scientific trust.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
