Opening Research Data: What Does It Mean for Social Sciences?

Abstract

Recent international trends demonstrate multilevel efforts to ‘open’ science across its whole ecosystem and lifecycle – from capturing research data through to publishing results. In social sciences, the publication process is already largely ‘open access’ or transitioning toward it. However, opening research data raises specific issues and concerns for the field. Here, we set out to understand what open research data mean for social sciences, and if, why, and how data should be made open. We argue that while the ecosystem of actors, infrastructures, standards, and principles is starting to take structure in France and abroad, there are several barriers to the process of opening data in social sciences: (1) a misperception of the motivations for opening data (i.e., focusing on risks of exercising control over researchers and their academic freedom and overlooking motivations like data patrimonialization, pooling and potential synergies, trust-building, and broader engagement), (2) a system based on competition and the dominant process of ‘starification’ in research, (3) a lack of resources and capabilities that might further exacerbate inequalities among genders, communities, institutions, and countries, and (4) the potential risks inherent to opening data and the specific constraints posed by social science data. Against this backdrop, we investigate several ways forward to operationalize not only FAIR (Findable, Accessible, Interoperable and Reusable) but also CARE (Collective benefit, Authority to control, Responsibility, Ethics) principles for open data in social sciences, before going on to present M@n@gement’s new open data policy.

Políticas editoriais de compartilhamento de dados em periódicos brasileiros de ciências sociais aplicadas na coleção SciELO

“…Apesar de suas origens nas chamadas "ciências duras", as práticas de compartilhamento de dados também avançam nas Ciências Sociais, ainda que mais lentamente (Christensen et al, 2020;Dunleavy, 2022;Swanson et al, 2020). Há, no entanto, desafios e resistências, ligados, por exemplo, à dinâmica da pesquisa qualitativa e às características dos dados qualitativos, aos padrões de comunicação dessas áreas, à carência de recursos (Beigel, 2023;Berkowitz;Delacour, 2022;Laakso, 2022). A despeito dos benefícios, as políticas de compartilhamento de dados não podem ser uma solução de tamanho único e devem refletir os padrões da pesquisa social (Prosser et al, 2022).…”