Archives des mots-clés : data sharing

Bringing All the Stakeholders to the Table: A Collaborative Approach to Data Sharing

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Authors : Megan N. O’Donnell, Curtis Brundy

Objective

This paper examines a unique data set disclosure process at a medium sized, land grant, research university and the campus collaboration that led to its creation.

Methods

The authors utilized a single case study methodology, reviewing relevant documents and workflows. As first-hand participants in the collaboration and disclosure process development, their own accounts and experiences also were utilized.

Results

A collaborative approach to enhancing research data sharing is essential, considering the wide array of stakeholders involved across the life cycle of research data. A transparent, inclusive data set disclosure process is a viable route to ensuring research data can be appropriately shared.

Conclusions

Successful sharing of research data impacts a range of university units and individuals. The establishment of productive working relationships and trust between these stakeholders is critical to expanding the sharing of research data and to establishing shared workflows.

URL : Bringing All the Stakeholders to the Table: A Collaborative Approach to Data Sharing

DOI : https://doi.org/10.7191/jeslib.2022.1224

Dissimuler ou disséminer ? Une étude sur le sort réservé aux résultats négatifs

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Auteures/Authors : Marie-Emilia Herbet, Jérémie Leonard, Maria Santangelo, Lucie Albaret

Une enquête composée de 34 questions a été adressée à des chercheurs en chimie, physique, sciences de l’ingénieur et de l’environnement, en vue d’identifier leur rapport aux résultats de recherche infructueux ainsi que les freins et les leviers de leur diffusion.

L’étude se fonde sur 310 réponses complètes émanant de participants affiliés à des établissements de recherche et d’enseignement français. Menée dans le cadre du projet Datacc, porté par les bibliothèques universitaires de Lyon et Grenoble Alpes, engagées dans l’accompagnement des chercheurs à l’ouverture des données de recherche, notre étude permet de combler le déficit de données sur le sujet au regard des disciplines concernées.

Elle relève que 81% des chercheurs interrogés ont déjà produit des résultats négatifs pertinents et 75% se disent prêts à publier ce type de données. Pourtant, seuls 12,5% des répondants ont déjà eu l’occasion de le faire dans une revue scientifique. Ce contraste béant entre l’intention et la pratique soulève des interrogations sur les obstacles en présence et les solutions potentielles à apporter.

URL : Dissimuler ou disséminer ? Une étude sur le sort réservé aux résultats négatifs

Original location : https://hal.archives-ouvertes.fr/hal-03371040

L’ouverture des matériaux de recherche ethnographiques en question

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Auteur-e-s/Authors : Florence Revelin, Alix Levain, Morgane Mignon, Marianne Noel, Betty Queffelec, Pascal Raux, Hervé Squividant

Le mouvement d’ouverture des données scientifiques constitue, pour les sciences humaines et sociales (SHS), un défi à la fois épistémologique, juridique, éthique et technique. Il se manifeste par des normes et injonctions multiples vis-à-vis des communautés de recherche, qui peinent à s’y conformer et à se saisir des instruments mis à leur disposition.

Le projet PARDOQ vise à rendre intelligibles les implications complexes de ce mouvement pour les communautés travaillant à partir de données qualitatives (ethnographiques), à travers l’analyse de l’expérience de chercheuses et chercheurs confronté.e.s à la tension entre partage et protection des données ethnographiques, en prenant appui d’une part sur une étude de cas (le programme de recherche interdisciplinaire Parchemins) et d’autre part sur une enquête auprès de chercheurs.euses pratiquant l’ethnographie et de membres de réseaux scientifiques, techniques et juridiques d’appui et à la recherche.

URL : L’ouverture des matériaux de recherche ethnographiques en question

Original location : https://hal.archives-ouvertes.fr/hal-03238067

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

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Authors : Christian Ohmann, David Moher, Maximilian Siebert, Edith Motschall, Florian Naudet

Objectives

To explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data.

Eligibility criteria

All studies investigating data-sharing practices for individual participant data (IPD) from clinical trials.

Sources of evidence

We searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication.

In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders.

Charting methods

Two reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain.

Results

93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal.

A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics.

Conclusions

There is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices.

URL : Status, use and impact of sharing individual participant data from clinical trials: a scoping review

Original location : https://bmjopen.bmj.com/content/11/8/e049228

Open research data repositories: Practices, norms, and metadata for sharing images

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Authors : Karin Hansson, Anna Dahlgren

Open research data repositories are promoted as one of the cornerstones in the open research paradigm, promoting collaboration, interoperability, and large-scale sharing and reuse. There is, however, a lack of research investigating what these sharing platforms actually share and a more critical interface analysis of the norms and practices embedded in this datafication of academic practice is needed.

This article takes image data sharing in the humanities as a case study for investigating the possibilities and constraints in 5 open research data repositories. By analyzing the visual and textual content of the interface along with the technical means for metadata, the study shows how the platforms are differentiated in terms of signifiers of research paradigms, but that beneath the rhetoric of the interface, they are designed in a similar way, which does not correspond well with the image researchers’ need for detailed metadata.

Combined with the problem of copyright limitations, these data-sharing tools are simply not sophisticated enough when it comes to sharing and reusing images. The result also corresponds with previous research showing that these tools are used not so much for sharing research data, but more for promoting researcher personas.

URL : Open research data repositories: Practices, norms, and metadata for sharing images

DOI : https://doi.org/10.1002/asi.24571

Between administration and research: Understanding data management practices in an institutional context

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Authors : Stefan Reichmann, Thomas Klebel, Ilire Hasani-Mavriqi, Tony Ross-Hellauer

Research Data Management (RDM) promises to make research outputs more transparent, findable, and reproducible. Strategies to streamline data management across disciplines are of key importance.

This paper presents results of an institutional survey (N = 258) at a medium-sized Austrian university with a STEM focus, supplemented with interviews (N = 18), to give an overview of the state-of-play of RDM practices across faculties and disciplinary contexts.

RDM services are on the rise but remain somewhat behind leading countries like the Netherlands and UK, showing only the beginnings of a culture attuned to RDM. There is considerable variation between faculties and institutes with respect to data amounts, complexity of data sets, data collection and analysis, and data archiving.

Data sharing practices within fields tend to be inconsistent. RDM is predominantly regarded as an administrative task, to the detriment of considerations of good research practice. Problems with RDM fall in two categories: Generic problems transcend specific research interests, infrastructures, and departments while discipline-specific problems need a more targeted approach.

The paper extends the state-of-the-art on RDM practices by combining in-depth qualitative material with quantified, detailed data about RDM practices and needs. The findings should be of interest to any comparable research institution with a similar agenda.

URL : Between administration and research: Understanding data management practices in an institutional context

DOI : https://doi.org/10.1002/asi.24492

Clinical trial transparency and data sharing among biopharmaceutical companies and the role of company size, location and product type: a cross-sectional descriptive analysis

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Authors : Sydney A Axson, Michelle M Mello, Deborah Lincow, Catherine Yang, Cary P Gross, Joseph S Ross, Jennifer Miller

Objectives

To examine company characteristics associated with better transparency and to apply a tool used to measure and improve clinical trial transparency among large companies and drugs, to smaller companies and biologics.

Design

Cross-sectional descriptive analysis.

Setting and participants

Novel drugs and biologics Food and Drug Administration (FDA) approved in 2016 and 2017 and their company sponsors.

Main outcome measures

Using established Good Pharma Scorecard (GPS) measures, companies and products were evaluated on their clinical trial registration, results dissemination and FDA Amendments Act (FDAAA) implementation; companies were ranked using these measures and a multicomponent data sharing measure.

Associations between company transparency scores with company size (large vs non-large), location (US vs non-US) and sponsored product type (drug vs biologic) were also examined.

Results

26% of products (16/62) had publicly available results for all clinical trials supporting their FDA approval and 67% (39/58) had public results for trials in patients by 6 months after their FDA approval; 58% (32/55) were FDAAA compliant.

Large companies were significantly more transparent than non-large companies (overall median transparency score of 95% (IQR 91–100) vs 59% (IQR 41–70), p<0.001), attributable to higher FDAAA compliance (median of 100% (IQR 88–100) vs 57% (0–100), p=0.01) and better data sharing (median of 100% (IQR 80–100) vs 20% (IQR 20–40), p<0.01). No significant differences were observed by company location or product type.

Conclusions

It was feasible to apply the GPS transparency measures and ranking tool to non-large companies and biologics. Large companies are significantly more transparent than non-large companies, driven by better data sharing procedures and implementation of FDAAA trial reporting requirements.

Greater research transparency is needed, particularly among non-large companies, to maximise the benefits of research for patient care and scientific innovation.

URL : Clinical trial transparency and data sharing among biopharmaceutical companies and the role of company size, location and product type: a cross-sectional descriptive analysis

DOI : http://dx.doi.org/10.1136/bmjopen-2021-053248