research data – Page 42 – InfoDoc MicroVeille

Ethics approval in applications for open-access clinical trial data: An analysis of researcher statements to clinicalstudydatarequest.com

Posté le 13 septembre 2017 par Hans Dillaerts

Authors : Derek So, Bartha M. Knoppers

Although there are a number of online platforms for patient-level clinical trial data sharing from industry sponsors, they are not very harmonized regarding the role of local ethics approval in the research proposal review process.

The first and largest of these platforms is ClinicalStudyDataRequest.com (CSDR), which includes over three thousand trials from thirteen sponsors including GlaxoSmithKline, Novartis, Roche, Sanofi, and Bayer. CSDR asks applicants to state whether they have received ethics approval for their research proposal, but in most cases does not require that they submit evidence of approval.

However, the website does require that applicants without ethical approval state the reason it was not required. In order to examine the perspectives of researchers on this topic, we coded every response to that question received by CSDR between June 2014 and February 2017.

Of 111 applicants who stated they were exempt from ethics approval, 63% mentioned de-identification, 57% mentioned the use of existing data, 33% referred to local or jurisdictional regulations, and 20% referred to the approvals obtained by the original study.

We conclude by examining the experience of CSDR within the broader context of the access mechanisms and policies currently being used by other data sharing platforms, and discuss how our findings might be used to help clinical trial data providers design clear and informative access documents.

URL : Ethics approval in applications for open-access clinical trial data: An analysis of researcher statements to clinicalstudydatarequest.com

DOI : https://doi.org/10.1371/journal.pone.0184491

Using Peer Review to Support Development of Community Resources for Research Data Management

Posté le 10 septembre 2017 par Hans Dillaerts

Authors : Heather Soyka, Amber Budden, Viv Hutchison, David Bloom, Jonah Duckles, Amy Hodge, Matthew S. Mayernik, Timothée Poisot, Shannon Rauch, Gail Steinhart, Leah Wasser, Amanda L. Whitmire, Stephanie Wright

Objective

To ensure that resources designed to teach skills and best practices for scientific research data sharing and management are useful, the maintainers of those materials need to evaluate and update them to ensure their accuracy, currency, and quality.

This paper advances the use and process of outside peer review for community resources in addressing ongoing accuracy, quality, and currency issues. It further describes the next step of moving the updated materials to an online collaborative community platform for future iterative review in order to build upon mechanisms for open science, ongoing iteration, participation, and transparent community engagement.

Setting

Research data management resources were developed in support of the DataONE (Data Observation Network for Earth) project, which has deployed a sustainable, long-term network to ensure the preservation and access to multi-scale, multi-discipline, and multi-national environmental and biological science data (Michener et al. 2012).

Created by members of the Community Engagement and Education (CEE) Working Group in 2011-2012, the freely available Educational Modules included three complementary components (slides, handouts, and exercises) that were designed to be adaptable for use in classrooms as well as for research data management training.

Methods

Because the modules were initially created and launched in 2011-2012, the current members of the (renamed) Community Engagement and Outreach (CEO) Working Group were concerned that the materials could be and / or quickly become outdated and should be reviewed for accuracy, currency, and quality.

In November 2015, the Working Group developed an evaluation rubric for use by outside reviewers. Review criteria were developed based on surveys and usage scenarios from previous DataONE projects.

Peer reviewers were selected from the DataONE community network for their expertise in the areas covered by one of the 11 educational modules. Reviewers were contacted in March 2016, and were asked to volunteer to complete their evaluations online within one month of the request, by using a customized Google form.

Results

For the 11 modules, 22 completed reviews were received by April 2016 from outside experts. Comments on all three components of each module (slides, handouts, and exercises) were compiled and evaluated by the postdoctoral fellow attached to the CEO Working Group.

These reviews contributed to the full evaluation and revision by members of the Working Group of all educational modules in September 2016. This review process, as well as the potential lack of funding for ongoing maintenance by Working Group members or paid staff, provoked the group to transform the modules to a more stable, non-proprietary format, and move them to an online open repository hosting platform, GitHub.

These decisions were made to foster sustainability, community engagement, version control, and transparency.

Conclusion

Outside peer review of the modules by experts in the field was beneficial for highlighting areas of weakness or overlap in the education modules. The modules were initially created in 2011-2012 by an earlier iteration of the Working Group, and updates were needed due to the constant evolving practices in the field.

Because the review process was lengthy (approximately one year) comparative to the rate of innovations in data management practices, the Working Group discussed other options that would allow community members to make updates available more quickly.

The intent of migrating the modules to an online collaborative platform (GitHub) is to allow for iterative updates and ongoing outside review, and to provide further transparency about accuracy, currency, and quality in the spirit of open science and collaboration.

Documentation about this project may be useful for others trying to develop and maintain educational resources for engagement and outreach, particularly in communities and spaces where information changes quickly, and open platforms are already in common use.

URL : Using Peer Review to Support Development of Community Resources for Research Data Management

DOI : https://doi.org/10.7191/jeslib.2017.1114

Standardising and harmonising research data policy in scholarly publishing

Posté le 8 septembre 2017 par Hans Dillaerts

Authors : Iain Hrynaszkiewicz, Aliaksandr Birukou, Mathias Astell, Sowmya Swaminathan, Amye Kenall, Varsha Khodiyar

To address the complexities researchers face during publication, and the potential community-wide benefits of wider adoption of clear data policies, the publisher Springer Nature has developed a standardised, common framework for the research data policies of all its journals. An expert working group was convened to audit and identify common features of research data policies of the journals published by Springer Nature, where policies were present.

The group then consulted with approximately 30 editors, covering all research disciplines, within the organisation. The group also consulted with academic editors and librarians and funders, which informed development of the framework and the creation of supporting resources.

Four types of data policy were defined in recognition that some journals and research communities are more ready than others to adopt strong data policies. As of January 2017 more than 700 journals have adopted a standard policy and this number is growing weekly. To potentially enable standardisation and harmonisation of data policy across funders, institutions, repositories, societies and other publishers the policy framework was made available under a Creative Commons license.

However, the framework requires wider debate with these stakeholders and an Interest Group within the Research Data Alliance (RDA) has been formed to initiate this process.

This paper was presented at the 12th International Digital Curation Conference, Edinburgh, UK on 22 February 2017 and will be submitted to International Journal of Digital Curation.

URL : Standardising and harmonising research data policy in scholarly publishing

DOI : https://doi.org/10.1101/122929

Recommended versus Certified Repositories: Mind the Gap

Posté le 6 septembre 2017 par Hans Dillaerts

Authors : Sean Edward Husen, Zoë G. de Wilde, Anita de Waard, Helena Cousijn

Researchers are increasingly required to make research data publicly available in data repositories. Although several organisations propose criteria to recommend and evaluate the quality of data repositories, there is no consensus of what constitutes a good data repository.

In this paper, we investigate, first, which data repositories are recommended by various stakeholders (publishers, funders, and community organizations) and second, which repositories are certified by a number of organisations.

We then compare these two lists of repositories, and the criteria for recommendation and certification. We find that criteria used by organisations recommending and certifying repositories are similar, although the certification criteria are generally more detailed.

We distil the lists of criteria into seven main categories: “Mission”, “Community/Recognition”, “Legal and Contractual Compliance”, “Access/Accessibility”, “Technical Structure/Interface”, “Retrievability” and “Preservation”.

Although the criteria are similar, the lists of repositories that are recommended by the various agencies are very different. Out of all of the recommended repositories, less than 6% obtained certification.

As certification is becoming more important, steps should be taken to decrease this gap between recommended and certified repositories, and ensure that certification standards become applicable, and applied, to the repositories which researchers are currently using.

DOI: https://doi.org/10.5334/dsj-2017-042

Quels choix juridiques pour la médiation culturelle et scientifique dans l’environnement numérique ?

Posté le 2 septembre 2017 par Hans Dillaerts

Auteur/Author : Lionel Maurel

La dimension juridique n’est pas forcément celle à laquelle on songe en premier lorsque l’on envisage les «enjeux numériques pour la médiation scientifique et culturelle du passé».

Pourtant, tout autant que la technique, le droit est devenu aujourd’hui un facteur essentiel d’interopérabilité dans l’environnement numérique. Tout projet culturel ou scientifique produisant des données et/ou des contenus doit s’interroger sur les conditions juridiques de mise à disposition de ces objets, sous peine que ces questions ne se posent ensuite a posteriori, en provoquant alors souvent difficultés et blocages pour ne pas avoir été suffisamment anticipées.

Cette dimension juridique est néanmoins de plus en plus importante pour les institutions culturelles (archives, bibliothèques, musées, etc.), ainsi que pour les équipes de chercheurs à mesure que la démarche du Linked Open Data (LOD) se développe et place les porteurs de projets devant des choix souvent complexes à effectuer.

L’ouverture des données implique en effet d’être en mesure de choisir entre plusieurs licences parmi le panel d’outils contractuels existants pour les appliquer à différents objets, sachant que leurs effets varient sensiblement et ne sont pas neutres pour les réutilisateurs en aval.

La visibilité des projets, leur capacité à nouer des relations avec d’autres initiatives et les formes même de médiation qui pourront être mis en oeuvre auprès de différents publics découlent en partie des décisions qui auront été prises à propos des conditions d’utilisation des données et contenus.

Le présent article vise à décrire les principes de base à partir desquels ces choix peuvent être effectués dans de bonnes conditions. En particulier, cet article s’attachera à montrer que faire le choix de l’ouverture par le biais de licences adaptées constitue un atout pour le développement de la médiation autour des données de la recherche.

URL : https://hal.archives-ouvertes.fr/hal-01577998/

What do data curators care about? Data quality, user trust, and the data reuse plan

Posté le 22 août 2017 par Hans Dillaerts

Author : Frank Andreas Sposito

Data curation is often defined as the practice of maintaining, preserving, and enhancing research data for long-term value and reusability. The role of data reuse in the data curation lifecycle is critical: increased reuse is the core justification for the often sizable expenditures necessary to build data management infrastructures and user services.

Yet recent studies have shown that data are being shared and reused through open data repositories at much lower levels than expected. These studies underscore a fundamental and often overlooked challenge in research data management that invites deeper examination of the roles and responsibilities of data curators.

This presentation will identify key barriers to data reuse, data quality and user trust, and propose a framework for implementing reuser-centric strategies to increase data reuse.

Using the concept of a “data reuse plan” it will highlight repository-based approaches to improve data quality and user trust, and address critical areas for innovation for data curators working in the absence of repository support.

URL : What do data curators care about? Data quality, user trust, and the data reuse plan

Alternative location : http://library.ifla.org/id/eprint/1797