POLICY BRIEF: Data Ethics and Structural Inequities in Science

This is a draft Policy Brief on Data Ethics and Structural Inequities in Science produced by the CODATA Data Ethics Working Group. 

We welcome feedback or discussion of the draft briefing via this form: https://forms.gle/SmkhP9Xzu… or directly to the authors: Suchith Anand , Louise Bezuidenhout, , Andrew Cox , Johannes John-Langba, , Sabina Leonelli,

 

Summary and recommendations

The gap that we identify in The UNESCO Recommendation on Open Science is in acknowledging the systematic structural conditions creating inequitable participation in science, and the impact that this has on how a push towards open science might play out in practice.

Science as a global system is riven by inequities. This has five interconnected dimensions:

1. Identity-based inequities shaping participation in science at an individual level
2. International inequities in the strength, visibility and recognition of research systems
3. Inequities in the research infrastructure and access to funding
4. Inequitable access to an increasingly commercialised publishing system
5. Data colonialism

These issues are well known, for example many points about international patterns in inequity are reiterated in previous policy statements, including the recent Africa Charter for Transformative Research Collaborations.

As well as being unjust these inequities compromise diversity and participation in science and so its strength and richness.
We appreciate that for many open science is seen as a way to address some of these issues, but we argue that there are significant power asymmetries involved and open science as a solution is not necessarily sufficient or even effective.
Given these conditions, the impact of open science and the sharing of data in particular, may play out in ways that are also inequitable. The principle of “intelligent openness”, where the definition of open science is based on context, needs much more development and backing with robust international governance mechanisms and examples of good practice.
Across the different dimensions of inequity, there is a need for:

1. Greater explicit acknowledgement of the issues
2. More research into the nature and distribution of the barriers to participation in
   science
3. Support to local definitions of the meaning of openness
4. Benchmarks for improvement to be established and progress monitored
5. All stakeholders to educate themselves about the issues
6. More participatory approaches to policy development