Étiquette : research data

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Data Sharing in the Context of Health-Related Citizen Science

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

Catégories
FR

Pratiques de gestion des données de la recherche : une nécessaire acculturation des chercheurs aux enjeux de la science ouverte ? Résultats d’une enquête exploratoire dans le bassin montpelliérain (juin 2018)

Auteur/Authors : Philippe Amiel, Francesca Frontini, Pierre-Yves Lacour, Agnès Robin

L’article présente les résultats d’une enquête exploratoire, menée en juin 2018 par le programme de recherche CommonData, dans le bassin montpelliérain à propos des pratiques de gestion des données de la recherche scientifique par les chercheurs.

Les principaux objectifs étaient de voir si cette gestion est ou non le fruit d’une organisation pensée et raisonnée, de vérifier la capacité ou l’incapacité dans laquelle se trouvent les chercheurs pour qualifier juridiquement les données explorées, collectées ou produites – qualification rendue nécessaire par la mise en œuvre de la politique actuelle d’ouverture de la science – et enfin, d’observer la réalité du sentiment de propriété développé par les chercheurs à l’égard des données qu’ils produisent, posant la question plus générale de la dimension personnelle et/ou institutionnelle du travail de recherche et de ses conséquences sur l’attribution de la propriété.

URL : https://journals.openedition.org/cdst/2061

Catégories
EN

Research Data Management Services and Strategic Planning in Libraries Today: A Longitudinal Study

Authors : Elise Gowen, John J. Meier

INTRODUCTION

Research data services have been adopted by many academic libraries. This study tracked the changes in research data management services and staffing among Association of American Universities (AAU) libraries over the past 5 years and compared them to the libraries’ goals for research data management (RDM) in their strategic plan.

METHODS

This quantitative study examined libraries at the 60 U.S. AAU institutions. In order to examine longitudinal changes, portions of Briney et.al. (2015a) were used as a basis for measuring data librarian staffing and services.

These trends were compared to the contemporary strategic priorities of libraries interviewed by Meier (2016), as well as against strategic plans of 2014 and 2019 available online.

RESULTS & DISCUSSION

While there have been modest increases in libraries in the sample population offering data services, most of those gains have been among the libraries that did not consider RDM a priority in 2014. Interestingly, some of the libraries that mentioned RDM as a priority in 2014 have lost data librarian positions.

Over half of the libraries in this study now provide or support a data repository. Many library strategic plans that mentioned RDM as an explicit goal 5 years ago now no longer mention it.

CONCLUSION

Data librarian positions, data services, and data repositories have now become common features of large research university libraries. However, research data services are no longer as prominent in many library strategic plans at institutions where such services are more established, and libraries instead seem to be moving on to the work of rethinking the nature of the services or expanding them.

URL : Research Data Management Services and Strategic Planning in Libraries Today: A Longitudinal Study

DOI : https://doi.org/10.7710/2162-3309.2336

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Non classé

SPI-Hub™: a gateway to scholarly publishing information

Authors : Taneya Y. Koonce, Mallory N. Blasingame, Jerry Zhao, Annette M. Williams, Jing Su, Spencer J. DesAutels, Dario A. Giuse, John D. Clark, Zachary E. Fox, Nunzia Bettinsoli Giuse

Background

Advances in the health sciences rely on sharing research and data through publication. As information professionals are often asked to contribute their knowledge to assist clinicians and researchers in selecting journals for publication, the authors recognized an opportunity to build a decision support tool, SPI-Hub: Scholarly Publishing Information Hub™, to capture the team’s collective publishing industry knowledge, while carefully retaining the quality of service.

Case Presentation

SPI-Hub’s decision support functionality relies on a data framework that describes journal publication policies and practices through a newly designed metadata structure, the Knowledge Management Journal Record™.

Metadata fields are populated through a semi-automated process that uses custom programming to access content from multiple sources. Each record includes 25 metadata fields representing best publishing practices. Currently, the database includes more than 24,000 health sciences journal records.

To correctly capture the resources needed for both completion and future maintenance of the project, the team conducted an internal study to assess time requirements for completing records through different stages of automation.

Conclusions

The journal decision support tool, SPI-Hub, provides an opportunity to assess publication practices by compiling data from a variety of sources in a single location.

Automated and semi-automated approaches have effectively reduced the time needed for data collection.

Through a comprehensive knowledge management framework and the incorporation of multiple quality points specific to each journal, SPI-Hub provides prospective users with both recommendations for publication and holistic assessment of the trustworthiness of journals in which to publish research and acquire trusted knowledge.

URL : SPI-Hub™: a gateway to scholarly publishing information

Original location : http://jmla.pitt.edu/ojs/jmla/article/view/815

Catégories
EN

FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Authors : Koenraad De Smedt, Dimitris Koureas, Peter Wittenburg

Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability.

As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers.

In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data.

The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions.

We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

URL : FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units

Alternative location : https://www.mdpi.com/2304-6775/8/2/21

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Non classé

Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves

Authors : Thu-Mai Christian, Amanda Gooch, Todd Vision, Elizabeth Hull

Despite the increase in the number of journals issuing data policies requiring authors to make data underlying reporting findings publicly available, authors do not always do so, and when they do, the data do not always meet standards of quality that allow others to verify or extend published results.

This phenomenon suggests the need to consider the effectiveness of journal data policies to present and articulate transparency requirements, and how well they facilitate (or hinder) authors’ ability to produce and provide access to data, code, and associated materials that meet quality standards for computational reproducibility.

This article describes the results of a research study that examined the ability of journal-based data policies to: 1) effectively communicate transparency requirements to authors, and 2) enable authors to successfully meet policy requirements.

To do this, we conducted a mixed-methods study that examined individual data policies alongside editors’ and authors’ interpretation of policy requirements to answer the following research questions.

Survey responses from authors and editors along with results from a content analysis of data policies found discrepancies among editors’ assertion of data policy requirements, authors’ understanding of policy requirements, and the requirements stated in the policy language as written.

We offer explanations for these discrepancies and offer recommendations for improving authors’ understanding of policies and increasing the likelihood of policy compliance.

URL : Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves

DOI : https://doi.org/10.1371/journal.pone.0230281

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Non classé

Digital Objects – FAIR Digital Objects: Which Services Are Required?

Author : Ulrich Schwardmann

Some of the early Research Data Alliance working groups reused the notion of digital objects as digital entities described by metadata and referenced by a persistent identifier. In recent times the FAIR principles became a prominent role as framework for the sustainability of scientific data.

Both approaches had always machine actionability, the capability of computational systems to use services on data without human intervention, in their focus. The more technical approach of digital objects turned out to provide a complementary view on several aspects of the policy framework of FAIR from a technical perspective.

After a deeper analysis and integration of these concepts by a group of European data experts the discussion intensified on so called FAIR digital objects. But they need to be accompanied by services as building blocks for automated processes. We will describe the components of this framework and its potentials here, and also which services inside this framework are required.

URL : Digital Objects – FAIR Digital Objects: Which Services Are Required?

DOI : http://doi.org/10.5334/dsj-2020-015