Archives des mots-clés : open science

The societal impact of Open Science: a scoping review

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Authors : Nicki Lisa Cole, Eva Kormann, Thomas Klebel, Simon Apartis, Tony Ross-Hellauer

Open Science (OS) aims, in part, to drive greater societal impact of academic research. Government, funder and institutional policies state that it should further democratize research and increase learning and awareness, evidence-based policy-making, the relevance of research to society’s problems, and public trust in research. Yet, measuring the societal impact of OS has proven challenging and synthesized evidence of it is lacking.

This study fills this gap by systematically scoping the existing evidence of societal impact driven by OS and its various aspects, including Citizen Science (CS), Open Access (OA), Open/FAIR Data (OFD), Open Code/Software and others. Using the PRISMA Extension for Scoping Reviews and searches conducted in Web of Science, Scopus and relevant grey literature, we identified 196 studies that contain evidence of societal impact. The majority concern CS, with some focused on OA, and only a few addressing other aspects.

Key areas of impact found are education and awareness, climate and environment, and social engagement. We found no literature documenting evidence of the societal impact of OFD and limited evidence of societal impact in terms of policy, health, and trust in academic research. Our findings demonstrate a critical need for additional evidence and suggest practical and policy implications.

URL : https://doi.org/10.1098/rsos.240286

To share or not to share? Image data sharing in the social sciences and humanities

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Authors : Elina Late, Mette Skov, Sanna Kumpulainen

Introduction

The paper aims to investigate image data sharing within social science and humanities. While data sharing is encouraged as a part of the open science movement, little is known about the approaches and factors influencing the sharing of image data.

This information is evident as the use of image data in these fields of research is increasing, and data sharing is context dependent.

Method

The study analyses qualitative semi-structured interviews with 14 scholars who incorporate digital images as a core component of their research data.

Analysis

Content analysis is conducted to gather information about scholars’ image data sharing and motivating and impeding factors related to it.

Results

The findings show that image data sharing is not an established research practice, and when it happens it is mostly done via informal means by sharing data through personal contacts. Supporting the scientific community, the open science agenda and fulfilling research funders’ requirements motivate scholars to share their data. Impeding factors relate to the qualities of data, ownership of data, data stewardship, and research integrity.

Conclusion

Advancing image data sharing requires the development of research infrastructures and providing support and guidelines. Better understanding of the scholars’ image data practices is also needed.

URL : To share or not to share? Image data sharing in the social sciences and humanities

DOI : https://doi.org/10.47989/ir292834

Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities

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Authors : Mohammad Hosseini, Serge P.J.M. Horbach, Kristi L. Holmes, Tony Ross-Hellauer

Technology influences Open Science (OS) practices, because conducting science in transparent, accessible, and participatory ways requires tools/platforms for collaborative research and sharing results. Due to this direct relationship, characteristics of employed technologies directly impact OS objectives. Generative Artificial Intelligence (GenAI) models are increasingly used by researchers for tasks such as text refining, code generation/editing, reviewing literature, data curation/analysis.

GenAI promises substantial efficiency gains but is currently fraught with limitations that could negatively impact core OS values such as fairness, transparency and integrity, and harm various social actors. In this paper, we explore possible positive and negative impacts of GenAI on OS.

We use the taxonomy within the UNESCO Recommendation on Open Science to systematically explore the intersection of GenAI and OS. We conclude that using GenAI could advance key OS objectives by further broadening meaningful access to knowledge, enabling efficient use of infrastructure, improving engagement of societal actors, and enhancing dialogue among knowledge systems.

However, due to GenAI limitations, it could also compromise the integrity, equity, reproducibility, and reliability of research, while also having potential implications for the political economy of research and its infrastructure. Hence, sufficient checks, validation and critical assessments are essential when incorporating GenAI into research workflows.

URL : Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities

DOI : https://doi.org/10.31235/osf.io/zns7g

L’édition scientifique en France : de la censure à l’ouverture : révolutions politiques, commerciales, technologiques… et autres problèmes éthiques

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Autrice/Author : Lise Verlaet

A travers une analyse systémique de l’édition scientifique en France – et plus particulièrement via une étude des contextes historiques, socio-économiques et politique – cet article soulève les problématiques éthiques qui ont jalonné la construction de l’écosystème scientifique et l’exploitation des produits de la recherche, et livre une réflexion sur les défis éthiques liés à la mise en place depuis 2018 de la politique de la Science Ouverte mais aussi des conséquences directes que cela va avoir sur les pratiques des chercheurs.

URL : L’édition scientifique en France : de la censure à l’ouverture : révolutions politiques, commerciales, technologiques… et autres problèmes éthiques

DOI : https://doi.org/10.25965/interfaces-numeriques.5262

An analysis of the effects of sharing research data, code, and preprints on citations

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Authors : Giovanni Colavizza, Lauren Cadwallader, Marcel LaFlamme, Grégory Dozot, Stéphane Lecorney, Daniel Rappo, Iain Hrynaszkiewicz

Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of results via preprints and openly sharing outputs such as data and code to make research more reproducible and extensible. Existing evidence shows that adopting Open Science practices has effects in several domains.

In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations.

We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average.

However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers.

Arxiv : https://arxiv.org/abs/2404.16171

A survey of how biology researchers assess credibility when serving on grant and hiring committees

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Authors : Iain Hrynaszkiewicz, Beruria Novich, James Harney, Veronique Kiermer

Researchers who serve on grant review and hiring committees have to make decisions about the intrinsic value of research in short periods of time, and research impact metrics such Journal Impact Factor (JIF) exert undue influence on these decisions. Initiatives such as the Coalition for Advancing Research Assessment (CoARA) and the Declaration on Research Assessment (DORA) emphasize responsible use of quantitative metrics and avoidance of journal-based impact metrics for research assessment. Further, our previous qualitative research suggested that assessing credibility, or trustworthiness, of research is important to researchers not only when they seek to inform their own research but also in the context of research assessment committees.

To confirm our findings from previous interviews in quantitative terms, we surveyed 485 biology researchers who have served on committees for grant review or hiring and promotion decisions, to understand how they assess the credibility of research outputs in these contexts. We found that concepts like credibility, trustworthiness, quality and impact lack consistent definitions and interpretations by researchers, which had already been observed in our interviews.

We also found that assessment of credibility is very important to most (81%) of researchers serving in these committees but fewer than half of respondents are satisfied with their ability to assess credibility. A substantial proportion of respondents (57% of respondents) report using journal reputation and JIF to assess credibility – proxies that research assessment reformers consider inappropriate to assess credibility because they don’t rely on intrinsic characteristics of the research.

This gap between importance of an assessment and satisfaction in the ability to conduct it was reflected in multiple aspects of credibility we tested and it was greatest for researchers seeking to assess the integrity of research (such as identifying signs of fabrication, falsification, or plagiarism), and the suitability and completeness of research methods. Non-traditional research outputs associated with Open Science practices – research data, code, protocol and preprints sharing – are particularly hard for researchers to assess, despite the potential of Open Science practices to signal trustworthiness.

Our results suggest opportunities to develop better guidance and better signals to support the evaluation of research credibility and trustworthiness – and ultimately support research assessment reform, away from the use of inappropriate proxies for impact and towards assessing the intrinsic characteristics and values researchers see as important.

DOI : https://doi.org/10.31222/osf.io/ht836