Archives des mots-clés : data sharing

Establishing an early indicator for data sharing and reuse

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Authors : Agata Piękniewska, Laurel L. Haak, Darla Henderson, Katherine McNeill, Anita Bandrowski, Yvette Seger

Funders, publishers, scholarly societies, universities, and other stakeholders need to be able to track the impact of programs and policies designed to advance data sharing and reuse. With the launch of the NIH data management and sharing policy in 2023, establishing a pre-policy baseline of sharing and reuse activity is critical for the biological and biomedical community.

Toward this goal, we tested the utility of mentions of research resources, databases, and repositories (RDRs) as a proxy measurement of data sharing and reuse. We captured and processed text from Methods sections of open access biological and biomedical research articles published in 2020 and 2021 and made available in PubMed Central.

We used natural language processing to identify text strings to measure RDR mentions. In this article, we demonstrate our methodology, provide normalized baseline data sharing and reuse activity in this community, and highlight actions authors and publishers can take to encourage data sharing and reuse practices.

URL : Establishing an early indicator for data sharing and reuse

DOI : https://doi.org/10.1002/leap.1586

Making Mathematical Research Data FAIR: A Technology Overview

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Authors : Tim Conrad, Eloi Ferrer, Daniel Mietchen, Larissa Pusch, Johannes Stegmuller, Moritz Schubotz

The sharing and citation of research data is becoming increasingly recognized as an essential building block in scientific research across various fields and disciplines. Sharing research data allows other researchers to reproduce results, replicate findings, and build on them. Ultimately, this will foster faster cycles in knowledge generation.

Some disciplines, such as astronomy or bioinformatics, already have a long history of sharing data; many others do not. The current landscape of so-called research data repositories is diverse. This review aims to perform a technology review on existing data repositories/portals with a focus on mathematical research data.

URL : Making Mathematical Research Data FAIR: A Technology Overview

Original location: https://arxiv.org/abs/2309.11829

La crédibilité des matériaux ethnographiques face au mouvement d’ouverture des données de la recherche

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Auteur.ices/Authors : Alix Levain, Florence Revelin, Anne-Gaëlle Beurier, Marianne Noël

Les politiques d’ouverture des données de la recherche s’appuient sur des arguments de transparence, d’innovation et de démocratisation des savoirs. Cet article vise à rendre intelligibles leurs implications pour les communautés travaillant à partir de données ethnographiques, confrontées à une transformation des critères de reconnaissance de la crédibilité des savoirs qu’elles produisent.

Alors que les chercheur·e·s qui pratiquent l’ethnographie sont engagé·e·s dans des formes situées de partage des matériaux avec les pair·e·s, les autres disciplines et les « communautés sources », le renforcement du contrôle externe sur les conditions dans lesquelles ce partage s’effectue déstabilise les économies de la crédibilité qui structurent ces pratiques.

Davantage qu’une réticence au processus d’ouverture, le retrait des ethnographes du mouvement apparaît au terme de notre analyse comme résultant à la fois de l’existence d’écologies alternatives des matériaux empiriques et d’une éthique des marges incorporée dans des normes professionnelles souvent implicites.

DOI : https://doi.org/10.4000/rac.30291

Biomedical supervisors’ role modeling of open science practices

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Authors : Tamarinde L Haven, Susan Abunijela, Nicole Hildebrand

Supervision is one important way to socialize Ph.D. candidates into open and responsible research. We hypothesized that one should be more likely to identify open science practices (here publishing open access and sharing data) in empirical publications that were part of a Ph.D. thesis when the Ph.D. candidates’ supervisors engaged in these practices compared to those whose supervisors did not or less often did.

Departing from thesis repositories at four Dutch University Medical centers, we included 211 pairs of supervisors and Ph.D. candidates, resulting in a sample of 2062 publications. We determined open access status using UnpaywallR and Open Data using Oddpub, where we also manually screened publications with potential open data statements. Eighty-three percent of our sample was published openly, and 9% had open data statements.

Having a supervisor who published open access more often than the national average was associated with an odds of 1.99 to publish open access. However, this effect became nonsignificant when correcting for institutions. Having a supervisor who shared data was associated with 2.22 (CI:1.19–4.12) times the odds to share data compared to having a supervisor that did not.

This odds ratio increased to 4.6 (CI:1.86–11.35) after removing false positives. The prevalence of open data in our sample was comparable to international studies; open access rates were higher. Whilst Ph.D. candidates spearhead initiatives to promote open science, this study adds value by investigating the role of supervisors in promoting open science.

URL : Biomedical supervisors’ role modeling of open science practices

DOI : https://doi.org/10.7554/eLife.83484

“We Share All Data with Each Other”: Data-Sharing in Peer-to-Peer Relationships

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Author : Eva Barlösius

Although the topic of data-sharing has boomed in the past few years, practices of datasharing have attracted only scant attention within working groups and scientific cooperation (peer-to-peer data-sharing).

To understand these practices, the author draws on Max Weber’s concept of social relationship, conceptualizing data-sharing as social action that takes place within a social relationship. The empirical material consists of interviews with 34 researchers representing five disciplines—linguistics, biology, psychology, computer sciences, and neurosciences.

The analysis identifies three social forms of data-sharing in peer-to-peer relationships: (a) closed communal sharing, which is based on a feeling of belonging together; (b) closed associative sharing, in which the participants act on the basis of an agreement; and (c) open associative sharing, which is oriented to “institutional imperatives” (Merton) and to formal regulations.

The study shows that far more data-sharing is occurring in scientific practice than seems to be apparent from a concept of open data alone. If the main goal of open-data policy programs is to encourage researchers to increase access to their data, it could be instructive to study the three forms of data-sharing to improve the understanding of why and how scientists make their data accessible to other researchers.

URL : “We Share All Data with Each Other”: Data-Sharing in Peer- to-Peer Relationships

DOI : https://doi.org/10.1007/s11024-023-09487-y

Initial insight into three modes of data sharing: Prevalence of primary reuse, data integration and dataset release in research articles

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Authors : Yukiko Sakai, Yosuke Miyata, Keiko Yokoi, Yuqing Wang, Keiko Kurata

While data sharing has received research interest in recent times, its real status remains unclear, owing to its ambiguous concept. To understand the current status of data sharing, this study examined primary reuse, data integration, and dataset release as the actual practices of data sharing.

A total of 963 articles, chosen from those published in 2018 and registered in the Web of Science global citation database, were manually checked. Existing data were reused in the mode of data integration (13.3%) as frequently as they were for the mode of primary reuse (12.1%). Dataset release was the least common mode (9.0%).

The results show the variation in data sharing and indicate the need for standardization of data description in articles based on thorough registration and expansion in public data archives to close the loop that results in the virtuous cycle of research data.

URL : Initial insight into three modes of data sharing: Prevalence of primary reuse, data integration and dataset release in research articles

DOI : https://doi.org/10.1002/leap.1546

Do Open Access Mandates Work? A Systematized Review of the Literature on Open Access Publishing Rates

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Authors : Elena Azadbakht, Tara Radniecki, Teresa Schultz, Amy W. Shannon

To encourage the sharing of research, various entities—including public and private funders, universities, and academic journals—have enacted open access (OA) mandates or data sharing policies.

It is unclear, however, whether these OA mandates and policies increase the rate of OA publishing and data sharing within the research communities impacted by them. A team of librarians conducted a systematized review of the literature to answer this question. A comprehensive search of several scholarly databases and grey literature sources resulted in 4,689 unique citations.

However, only five articles met the inclusion criteria and were deemed as having an acceptable risk of bias. This sample showed that although the majority of the mandates described in the literature were correlated with a subsequent increase in OA publishing or data sharing, the presence of various confounders and the differing methods of collecting and analyzing the data used by the studies’ authors made it impossible to establish a causative relationship.

URL : Do Open Access Mandates Work? A Systematized Review of the Literature on Open Access Publishing Rates

DOI : https://doi.org/10.31274/jlsc.15444