Let me start this new edition of the EASST Review by thanking Ignacio for his superb work in leading its recent transformations, and making it such an exciting platform for information and exchange about the STS community in Europe and beyond, while also rejuvenating the outlook. As such, I did not hesitate for a second when he asked me to join the editorial board, and it is a pleasure to work with him and the others of the Review and EASST to generate ideas and topics for future publications. This edition features the PAST centre in Syberia, the feminist journal Catalyst, Latour’s Reset Modernity! exhibition, as well as two events partially funded by EASST. Many thanks to everyone contributing and we hope you will enjoy reading.
Building on Ignacio’s previous editorial that diagnosed a collaborative turn in STS, I would like to point at the important new development of data sharing in STS, which can also enhance the collaborative spirit of our field. Many STS scholars are studying transforming scientific practices around data collection, curation and preservation, and how these are changing scientific collaboration and data sharing, but we are just starting to think of the implications of this for our own research practice. How do we as STS colleagues share our data, not only with our close collaborators, but also within our field – with current colleagues and future generations of scholars – and beyond the borders of our own community, with stakeholders and various publics?
This topic has been on the agenda of the science and technology studies community for a while, especially since the US National Science Foundation now requires proposal applicants to include a data management plan. This resulted in a workshop in which colleagues from history, philosophy, and social studies of science and technology1 met last year at the National Science Foundation to discuss the opportunities and challenges of storing and sharing data in science and technology studies (involving two EASST members, Sally Wyatt and I). Workshop members reported on their work during the Denver 4S meeting and also discussed the need for a European discussion on this topic, in line with requests from various national councils and European funding bodies regarding data management and our own wishes as a community. However, as the European STS landscape and its funding sources are quite diverse, we will need to find ways to deal with national diversity, so national STS organization may also provide a role in forwarding these discussions, along with EASST.
What follows is a short summary of findings from the US National Science Foundation workshop2 to serve as a starting point for framing European discussions within this more global initiative on data sharing in STS.
The 4S/NSF Workshop participants identified four main benefits of data sharing for STS which are summarized as follows in the report:
The National Science Foundation Report on Data Sharing in Science and Technology Studies (2015).
First, data sharing has the potential to transform the practice, substance, and scope of science and technology studies. This includes allowing scholars to ask broader research questions, conduct large-scale and cross-case comparisons, and create more rigorous and replicable methods, while also enabling the systematic accumulation of STS knowledge via analysis and synthesis of existing data. Such efforts may also enhance the value of STS data and scholarship for policymakers.
Second, data sharing has the potential to advance STS methodology and data curation practices. This includes improvement of measurement and data collection methods to ensure reuse and replicability, protection against faulty data, and archiving and making sustainable STS data rather than allowing them to decay and disappear at the end of a research project or professional career.
Third, data sharing has the potential to provide professional development opportunities. This includes new research training opportunities for advanced techniques for data sharing, synthesis, and reuse, and facilitating scholars’ abilities to meet granting requirements. New training programs may also help establish a cultural shift in STS whereby datasets, data preparation, and data sharing come to be valued as important scholarly products worthy of professional recognition.
Fourth, data sharing has the potential to make STS research more engaged, democratic, and practically relevant by making data and research findings available to scholars and citizens without access to funding and research materials.
We also discussed ways in which this cultural shift towards sharing can be stimulated, recognizing the value of data sharing while also safeguarding the diversity of data produced in different fields and specialties, and via different research methods. Most importantly, it seems necessary that different forms of data can have different levels of openness or access, with some data not being suited for actual sharing due to ethical considerations and anonymity. Moreover, and to promote a culture of data sharing within STS, the topic should become part of the agenda of workshops and projects in STS, as well as the training of (young) scholars. In this context, the development and sharing of example data management plans might also be helpful. In order to enable sharing efforts, alliances with publishers, libraries, archives, and museums can be useful to share expertise about data curation and management.
Last but not least, the topic of data sharing within STS is deeply embedded in existing discussions about open data that are taking place in our EASST community, and it is also quite visible in the 4S/EASST Barcelona programme. Tracks on ‘The Lives and Deaths of Data’, ‘Open science in practice’ and ‘Critical data studies’ will certainly be showing various ways in which we are already engaging with this topic, and can perhaps also provide opportunities to discuss these topics in relation to our own work and interests.