Auteur/Author : Agnès Robin
Les données de la recherche scientifique sont actuellement soumises à un programme de standardisation technique (FAIR) dont l’objectif est d’en permettre la diffusion aux fins de réutilisation par le public (entreprises privées ou autre).
Cette politique, qui sans se confondre avec elle, converge avec celle dite de « science ouverte », s’articule autour d’un principe normatif conflictuel, selon lequel le résultats de la recherche (et donc les données) doivent être « aussi ouverts que possibles et pas plus fermés que nécessaire », obligeant alors les chercheurs, ingénieurs et documentalistes, éventuellement chargés de la gestion des données de la recherche, à procéder à une qualification juridique délicate des données.
URL : http://intelligibilite-numerique.numerev.com/index.php/numeros/n-1-2020/9-le-principe-d-ouverture-des-donnees-de-la-recherche-scientifique
Authors : Jeremy Leipzig, Daniel Nüst, Charles Tapley Hoyt, Stian Soiland-Reyes, Karthik Ram, Jane Greenberg
Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results.
In addition to its role in research integrity, RCR has the capacity to significantly accelerate evaluation and reuse. This potential and wide-support for the FAIR principles have motivated interest in metadata standards supporting RCR.
Metadata provides context and provenance to raw data and methods and is essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described the relationship between metadata and RCR.
This article employs a functional content analysis to identify metadata standards that support RCR functions across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications.
Our article provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.
URL : The role of metadata in reproducible computational research
Original location : https://arxiv.org/abs/2006.08589
Authors : Antti M. Rousi, Mikael Laakso
The practices for if and how scholarly journals instruct research data for published research to be shared is an area where a lot of changes have been happening as science policy moves towards facilitating open science, and subject-specific repositories and practices are established.
This study provides an analysis of the research data sharing policies of highly-cited journals in the fields of neuroscience, physics, and operations research as of May 2019. For these 120 journals, 40 journals per subject category, a unified policy coding framework was developed to capture the most central elements of each policy, i.e. what, when, and where research data is instructed to be shared.
The results affirm that considerable differences between research fields remain when it comes to policy existence, strength, and specificity. The findings revealed that one of the most important factors influencing the dimensions of what, where and when of research data policies was whether the journal’s scope included specific data types related to life sciences which have established methods of sharing through community-endorsed public repositories.
The findings surface the future research potential of approaching policy analysis on the publisher-level as well as on the journal-level. The collected data and coding framework is provided as open data to facilitate future research and journal policy monitoring.
DOI : https://doi.org/10.1007/s11192-020-03467-9
Authors : Maximilian Siebert, Jeanne Fabiola Gaba, Laura Caquelin, Henri Gouraud, Alain Dupuy, David Moher, Florian Naudet
To explore the implementation of the International Committee of Medical Journal Editors (ICMJE) data-sharing policy which came into force on 1 July 2018 by ICMJE-member journals and by ICMJE-affiliated journals declaring they follow the ICMJE recommendations.
A cross-sectional survey of data-sharing policies in 2018 on journal websites and in data-sharing statements in randomised controlled trials (RCTs).
ICMJE website; PubMed/Medline.
ICMJE-member journals and 489 ICMJE-affiliated journals that published an RCT in 2018, had an accessible online website and were not considered as predatory journals according to Beall’s list. One hundred RCTs for member journals and 100 RCTs for affiliated journals with a data-sharing policy, submitted after 1 July 2018.
Main outcome measures
The primary outcome for the policies was the existence of a data-sharing policy (explicit data-sharing policy, no data-sharing policy, policy merely referring to ICMJE recommendations) as reported on the journal website, especially in the instructions for authors.
For RCTs, our primary outcome was the intention to share individual participant data set out in the data-sharing statement.
Eight (out of 14; 57%) member journals had an explicit data-sharing policy on their website (three were more stringent than the ICMJE requirements, one was less demanding and four were compliant), five (35%) additional journals stated that they followed the ICMJE requirements, and one (8%) had no policy online. In RCTs published in these journals, there were data-sharing statements in 98 out of 100, with expressed intention to share individual patient data reaching 77 out of 100 (77%; 95% CI 67% to 85%).
One hundred and forty-five (out of 489) ICMJE-affiliated journals (30%; 26% to 34%) had an explicit data-sharing policy on their website (11 were more stringent than the ICMJE requirements, 85 were less demanding and 49 were compliant) and 276 (56%; 52% to 61%) merely referred to the ICMJE requirements.
In RCTs published in affiliated journals with an explicit data-sharing policy, data-sharing statements were rare (25%), and expressed intentions to share data were found in 22% (15% to 32%).
Author : Jinfang Niu
Libraries face innovations periodically. It is important to identify consistent patterns in the diffusion and adoption of innovations so that libraries and relevant stakeholders will be informed and well-prepared for future innovations.
This paper compares findings from two previous projects, each of which was conducted to investigate the diffusion and adoption of two recent innovations, research data management service and linked data, respectively.
The two projects were conducted using similar methods: collecting and analysing literature about the adoption of these innovations in libraries in the United States. Literature was collected through Google Scholar search, citation chasing, and target search for people or libraries that are involved in their adoption.
The gathered articles were then coded and analysed based on diffusion of innovation theories.
Similarities and disparities between the diffusion and adoption of the two innovations were identified.
Findings from this study are informative for the decision-making of libraries, librarians, funders, and professional associations facing future innovations. They also contribute to diffusion of innovation theories through revealing new communication channels and alternative adoption processes, as well as redefining existing concepts.
URL : http://www.informationr.net/ir/25-2/paper855.html
Author : Lisa Federer
Widely adopted standards for data citation are foundational to efforts to track and quantify data reuse. Without the means to track data reuse and metrics to measure its impact, it is difficult to reward researchers who share high-value data with meaningful credit for their contribution.
Despite initial work on developing guidelines for data citation and metrics, standards have not yet been universally adopted. This article reports on the recommendations collected from a workshop held at the Future of Research Communications and e-Scholarship (FORCE11) 2018 meeting titled Measuring and Mapping Data Reuse: An Interactive Workshop on Metrics for Data.
A range of stakeholders were represented among the participants, including publishers, researchers, funders, repository administrators, librarians, and others.
Collectively, they generated a set of 68 recommendations for specific actions that could be taken by standards and metrics creators; publishers; repositories; funders and institutions; creators of reference management software and citation styles; and researchers, students, and librarians.
These specific, concrete, and actionable recommendations would help facilitate broader adoption of standard citation mechanisms and easier measurement of data reuse.
URL : Measuring and Mapping Data Reuse: Findings From an Interactive Workshop on Data Citation and Metrics for Data Reuse
DOI : https://doi.org/10.1162/99608f92.ccd17b00
Authors : Mary A. Majumder, Amy L. McGuire
As citizen science expands, questions arise regarding the applicability of norms and policies created in the context of conventional science. This article focuses on data sharing in the conduct of health-related citizen science, asking whether citizen scientists have obligations to share data and publish findings on par with the obligations of professional scientists.
We conclude that there are good reasons for supporting citizen scientists in sharing data and publishing findings, and we applaud recent efforts to facilitate data sharing.
At the same time, we believe it is problematic to treat data sharing and publication as ethical requirements for citizen scientists, especially where there is the potential for burden and harm without compensating benefit.
DOI : https://doi.org/10.1177/1073110520917044