Étiquette : data sharing

Building a Trustworthy Data Repository: CoreTrustSeal Certification as a Lens for Service Improvements

Auteur de l’article Par Hans Dillaerts
Date de l’article 12 janvier 2024

Authors : Cara Key, Clara Llebot, Michael Boock

Objective

The university library aims to provide university researchers with a trustworthy institutional repository for sharing data. The library sought CoreTrustSeal certification in order to measure the quality of data services in the institutional repository, and to promote researchers’ confidence when depositing their work.

Methods

The authors served on a small team of library staff who collaborated to compose the certification application. They describe the self-assessment process, as they iterated through cycles of compiling information and responding to reviewer feedback.

Results

The application team gained understanding of data repository best practices, shared knowledge about the institutional repository, and identified areas of service improvements necessary to meet certification requirements. Based on the application and feedback, the team took measures to enhance preservation strategies, governance, and public-facing policies and documentation for the repository.

Conclusions

The university library gained a better understanding of top-notch data services and measurably improved these services by pursuing and obtaining CoreTrustSeal certification.

URL : Building a Trustworthy Data Repository: CoreTrustSeal Certification as a Lens for Service Improvements

DOI : https://doi.org/10.7191/jeslib.761

Étiquettes Cara Key, certification, Clara Llebot, CoreTrustSeal, data repositories, data sharing, institutional repositories, Michael Boock, research data

Establishing an early indicator for data sharing and reuse

Auteur de l’article Par Hans Dillaerts
Date de l’article 18 novembre 2023

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

Étiquettes Agata Piękniewska, Anita Bandrowski, biomedical research, Darla Henderson, data reuse, data sharing, Katherine McNeill, Laurel L. Haak, research data, scientific communication, Yvette Seger

Making Mathematical Research Data FAIR: A Technology Overview

Auteur de l’article Par Hans Dillaerts
Date de l’article 23 septembre 2023

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

Étiquettes Daniel Mietchen, data sharing, Eloi Ferrer, FAIR Data, Johannes Stegmuller, Larissa Pusch, Mathematics, Moritz Schubotz, research data, Tim Conrad

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

Auteur de l’article Par Hans Dillaerts
Date de l’article 5 juin 2023

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

Étiquettes Alix Levain, Anne-Gaëlle Beurier, data sharing, Ethnography, Florence Revelin, HSS, humanities and social sciences, Marianne Noel, research data, Research Ethics

Biomedical supervisors’ role modeling of open science practices

Auteur de l’article Par Hans Dillaerts
Date de l’article 31 mai 2023

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

Étiquettes biomedical research, data sharing, Nicole Hildebrand, open access, open research, research data, scientific communication, scientific practices, Susan Abunijela, Tamarinde L. Haven

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

Auteur de l’article Par Hans Dillaerts
Date de l’article 17 mai 2023

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

Étiquettes data sharing, Eva Barlösius, open data, Peer-to-Peer, research data