L’ouverture des matériaux de recherche ethnographiques en question

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

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

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

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

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

Factors that influence data sharing through data sharing platforms: A qualitative study on the views and experiences of cohort holders and platform developers

Authors : Thijs Devriendt, Pascal Borry, Mahsa Shabani

Background

Infrastructures are being developed to enhance and facilitate the sharing of cohort data internationally. However, empirical studies show that many barriers impede sharing data broadly.

Purpose

Therefore, our aim is to describe the barriers and concerns for the sharing of cohort data, and the implications for data sharing platforms.

Methods

Seventeen participants involved in developing data sharing platforms or tied to cohorts that are to be submitted to platforms were recruited for semi-structured interviews to share views and experiences regarding data sharing.

Results

Credit and recognition, the potential misuse of data, loss of control, lack of resources, socio-cultural factors and ethical and legal barriers are elements that influence decisions on data sharing. Core values underlying these reasons are equality, reciprocity, trust, transparency, gratification and beneficence.

Conclusions

Data generators might use data sharing platforms primarily for collaborative modes of working and network building. Data generators might be unwilling to contribute and share for non-collaborative work, or if no financial resources are provided for sharing data.

URL : Factors that influence data sharing through data sharing platforms: A qualitative study on the views and experiences of cohort holders and platform developers

DOI : https://doi.org/10.1371/journal.pone.0254202

Data sharing practices and data availability upon request differ across scientific disciplines

Authors : Leho tedersoo, Rainer Küngas, Ester Oras, Kajar Köster, Helen Eenmaa, Äli Leijen, Margus Pedaste, Marju Raju, Anastasiya Astapova, Heli Lukner, Karin Kogermann, Tuul Sepp

Data sharing is one of the cornerstones of modern science that enables large-scale analyses and reproducibility. We evaluated data availability in research articles across nine disciplines in Nature and Science magazines and recorded corresponding authors’ concerns, requests and reasons for declining data sharing.

Although data sharing has improved in the last decade and particularly in recent years, data availability and willingness to share data still differ greatly among disciplines. We observed that statements of data availability upon (reasonable) request are inefficient and should not be allowed by journals.

To improve data sharing at the time of manuscript acceptance, researchers should be better motivated to release their data with real benefits such as recognition, or bonus points in grant and job applications.

We recommend that data management costs should be covered by funding agencies; publicly available research data ought to be included in the evaluation of applications; and surveillance of data sharing should be enforced by both academic publishers and funders. These cross-discipline survey data are available from the plutoF repository.

URL : Data sharing practices and data availability upon request differ across scientific disciplines

DOI : https://doi.org/10.1038/s41597-021-00981-0