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Integrating Ethics into Research Data Infrastructures: Proposal for a Webinar Series on Data Ethics

Authors: Bruns, Andreas; Christoforaki, Maria; Schembera, Björn;

Integrating Ethics into Research Data Infrastructures: Proposal for a Webinar Series on Data Ethics

Abstract

Research Data Infrastructures (RDIs) increasingly impact and shape the way we live. As the main enablers of research data management (RDM), they can promote scientific progress, good healthcare, and effective public services. If used well, RDIs can positively impact our abilities to live good lives. At the same time, RDIs come not only with increased management and organisational requirements but with advanced ethical responsibilities to prevent data from being handled or used in ways that threaten people's privacy, perpetuate social injustices, biases, or discriminatory practices, and erode trust in the research system. There is a growing consensus that, in order to safeguard RDIs, ethics must be integrated into the design and operations of RDIs. This corresponds to the rise of approaches of "embedded ethics" and "ethics by design" [1], [2], [3]. One central requirement to achieve this integration is that ethics "must become part of the language that technologists are comfortable using" [4]. In addition, the RDM objectives matrix identifies ethical aspects as relevant teaching content [5]. Yet, existing training schemes such as the "train-the-trainer" concept of the FDM Mentor project [6] do not include anything on the topic of ethics. In February 2024, the ELSA Section of the NFDI created a Working Group Ethics (WGE) to provide a space to discuss ethical issues arising across different NFDI consortia and to bring together experts from different backgrounds to collaborate on addressing these issues. With this presentation, the WGE would like to propose a Webinar Series on Data Ethics. The Webinar Series will have two main objectives: Demystifying Ethics and its relevance for RDIs In order to integrate ethics into the everyday language that data practitioners are comfortable using, we first must aim to demystify what "ethics" means and how it is a relevant concern in RDM. The first webinars of the series will therefore be dedicated to a brief introduction to ethics and the many ways in which data practices raise ethical questions. Helping data practitioners learn relevant skills in ethical reflection and analysis In order to integrate ethics into data practice, it is not enough for ethics workstreams accompanying technical projects to provide ethics guidelines [7]. Instead, data practitioners need to be able to identify, understand, phrase, analyse, and evaluate ethical problems independently. The Webinar Series aims to help them acquire these abilities by taking a case study-based interactive learning approach. Drawing on existing training and university-level teaching resources [4], [8], [9], the webinars will engage participants in active discussions about specific examples to explore both ways to phrase the ethical problems connected to them as well as possible approaches to address them. The Webinar Series will be hosted and delivered by the WGE and is envisioned to be an ongoing project. New webinars on focus topics can be added, depending on reception and feedback from the NFDI community. All materials, such as slides and recordings, will be made available as an open educational resource.

Keywords

Ethics By Design, Data Ethics, Embedded Ethics, Research Data Infrastructures

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green