Article written by Nora Dörrenbächer & Mathias Bug, German Data Forum (RatSWD), institutional member of the EcoSoc IN
The eighth conference for social and economic data (8| KSWD) took place in Berlin from 02-03 March, 2020. With the motto “Society needs Science, Science needs Data,” the German Data Forum (RatSWD) addressed the challenges in changing the data culture, methods of data generation, and making data accessible for research. Around 300 participants discussed, in parallel sessions and plenary lectures, socially central issues relating to big data, online surveys, data collection with mobile devices, as well as evidence-based policy consultation, registry data, and innovative access to sensitive data.
One panel explicitly dealt with FAIR data access for social and economic sciences. Prof. Dr. Joachim Gassen (Humboldt University of Berlin; TRR 266 “Accounting for Transparency”), Prof. Dr. Iris Pigeot (Leibniz Institute for Prevention Research and Epidemiology – BIPS; University of Bremen), Dr. Pascal Siegers (GESIS – Leibniz Institute for the Social Sciences) and Prof. Dr. Klaus Tochtermann (Leibniz Information Centre for Economics (ZBW) spoke at the podium. The panel was moderated by Prof. Stefan Bender (Deutsche Bundesbank).
The panel discussion was structured around four key questions, beginning with the question of the FAIRness level already achieved in the represented disciplines. According to Iris Pigeot, research data centres (RDC) already make a significant contribution in the social and economic sciences. However, in health sciences and small research projects, this standard is not yet achieved in general.
Based on this, the question of what suitable steps are necessary to become FAIR was raised. Pascal Siegers suggests that metadata standards should describe the granularity of the data, and include domain-specific definitions. Furthermore, institutions should have transparent data policies and offer remote access for data analysis. Moreover, the data sets should be accompanied by accessible methods reports that specify how data was collected, and which steps were carried out e.g. for anonymisation. For the machine-readability of data, interfaces would need to be created with machine-readable access protocol and common exchange formats. Research projects should take into account resources for research data management in their project planning. Additionally, data must also be advertised to increase reusability.
The third key question focused on concrete steps to increase the reproducibility of research results. Klaus Tochtermann emphasised that the “R” in FAIR stands for “reusability” and not “reproducibility,” which surpasses observing the FAIR principles. In addition to research data, the codes and software versions are also required for reproducibility; the study design would also need to be published (if possible before data collection), e.g. with registered reports. This could counteract the possible publication bias towards the publication of highly significant results. During the discussion it became clear that data reviews require not only experts, but also infrastructure, algorithms, and interfaces to control the data.
Looking into the future, the panel closed with the question of whether the culture towards FAIR data is changing, and how this could be promoted. Joachim Gassen described a rather slow cultural change towards sharing data. Especially in economics, the commercialisation of data stands in the way of FAIR handling of data. Other obstacles were also mentioned in the discussion: Younger scientists fear theft of ideas, and the scientific system provides few career incentives to invest time and effort into preparing the data and making them available. The latter obstacle should be counteracted with transparent tenure tracks. Additionally, researchers should be aware that data and measurement methods are often only reused after several years. The discussion also focused on the question of why institutes often do not share their data. For example, there are fears that the institutes could suffer loss of reputation if there is a breach in data protection during the reuse of the data by third parties. However, the general agreement is that the cultural shift must be carried out primarily by science itself.
The presentations of the lectures at the 8| KSWD, photos, and short summaries of the sessions can be found here: https://www.ratswd.de/8kswd.
Photo credentials: RatSWD/Filipp Piontek