EN

The role of a data librarian in academic and research libraries

Posted on by Hans Dillaerts

Authors : Isaac K. Ohaji, Brenda Chawner, Pak Yoong

Introduction

This paper presents a data librarian role blueprint (the blueprint) in order to facilitate an understanding of the academic and research librarian’s role in research data management and e-research.

Method

The study employed a qualitative ase research approach to investigate the dimensions of the role of a data librarian in New Zealand research organizations, using semi-structured interviews as the main data collection instrument.

Analysis

A data analysis spiral was used to analyse the interview data, with the addition of a job analysis framework to organize the role performance components of a data librarian.

Results

The influencing factors, performance components and training needs for a data librarian role form the basis of the blueprint.

Conclusions

The findings which are reflected in the blueprint provide a conceptual understanding of the data librarian role which may be used to inform and enhance practice, or to develop relevant education and training programmes.

URL : http://informationr.net/ir/24-4/paper844.html

EN

Research data sharing during the Zika virus public health emergency

Posted on by Hans Dillaerts

Authors : Vanessa de Arruda Jorge, Sarita Albagli

Introduction

In a public health emergency, sharing of research data is acknowledged as essential to manage treatment and control of the disease. The objective of this study was to examine how researchers reacted during the Zika virus emergency in Brazil.

Method

A literature review examined both unpublished reports and the published literature. Interviews were conducted with eleven researchers (from a sample of sixteen) in the Renezika network. Questions concerned sources of data used for research on the Zika virus, where this data was obtained, and what requirements by funding agencies influenced how data generated was shared – and how open the degree of sharing was.

Analysis

A content analysis matrix was developed based on the results of the interviews. The data were organised acording to categories, subcategories, records units and frequency of records units.

Results

Researchers stressed the importance of access to issue samples as well as pure research data. Collaboration – and publication – increased but also depended on trust in existing networks. Researchers were aware that many agencies and publishers required the deposit of research data in repositories – and several options existed for Zika research.

Conclusions

The findings show that research data were shared, but not necessarily as open data. Trust was necessary between researchers, and researchers in developing countries needed to be assured about their rights and ownership of data, and publications using that data.

URL : http://informationr.net/ir/25-1/paper846.html

EN

Risk Assessment for Scientific Data

Posted on by Hans Dillaerts

Authors : Matthew S. Mayernik, Kelsey Breseman, Robert R. Downs, Ruth Duerr, Alexis Garretson, Chung-Yi (Sophie) Hou

Ongoing stewardship is required to keep data collections and archives in existence. Scientific data collections may face a range of risk factors that could hinder, constrain, or limit current or future data use.

Identifying such risk factors to data use is a key step in preventing or minimizing data loss. This paper presents an analysis of data risk factors that scientific data collections may face, and a data risk assessment matrix to support data risk assessments to help ameliorate those risks.

The goals of this work are to inform and enable effective data risk assessment by: a) individuals and organizations who manage data collections, and b) individuals and organizations who want to help to reduce the risks associated with data preservation and stewardship.

The data risk assessment framework presented in this paper provides a platform from which risk assessments can begin, and a reference point for discussions of data stewardship resource allocations and priorities.

URL : Risk Assessment for Scientific Data

DOI : http://doi.org/10.5334/dsj-2020-010

FR

Publications numériques scientifiques universitaires internationales : Disruption, quels acteurs,quels projets ?

Posted on by Hans Dillaerts

Auteur/Author : Appoline Romanens

Les enseignants-chercheurs d’aujourd’hui se heurtent à des APC, ont besoin de logiciels de PAO, avec un DMP pour apparaître dans la base de données du DOAJ, ou espérer rentrer dans celle duWoS.

Tous ces termes nous semblent éloignés du jargon du Journal des Sçavans, première manifestation de la compilation des pensées de la recherche scientifique.

Pourtant ils sont le signe d’une évolution du médium qui porte l’article académique scientifique aujourd’hui, le web de données, dans lequel toute publication scientifique se doit d’être réticulée pour survivre au publish or perish.

Afin de comprendre ce nouveau jargon de la recherche scientifique, qui témoigne de profonds changements dans le rapport qu’entretient l’enseignant-chercheur, l’éditeur puis le lecteur par rapport au texte, ce mémoire explore la notion de disruption dans le processus de création, relecture et édition puis publication et diffusion d’un article.

Outre un développement basé sur les théories de l’économie du document et de l’article scientifique, ce mémoire apporte deux études de cas qui rendent compte du phénomène de disruption dans les publications scientifiques, et propose à partir de ce corpus une ouverture sur ses enjeux actuels et futurs.

URL : Publications numériques scientifiques universitaires internationales : Disruption, quels acteurs,quels projets ?

Original location : https://www.enssib.fr/bibliotheque-numerique/notices/69398-publications-numeriques-scientifiques-universitaires-internationales-disruption-quels-acteurs-quels-projets

EN

Why we publish where we do: Faculty publishing values and their relationship to review, promotion and tenure expectations

Posted on by Hans Dillaerts

Authors : Meredith T. Niles, Lesley A. Schimanski, Erin C. McKiernan, Juan Pablo Alperin

Using an online survey of academics at 55 randomly selected institutions across the US and Canada, we explore priorities for publishing decisions and their perceived importance within review, promotion, and tenure (RPT).

We find that respondents most value journal readership, while they believe their peers most value prestige and related metrics such as impact factor when submitting their work for publication.

Respondents indicated that total number of publications, number of publications per year, and journal name recognition were the most valued factors in RPT.

Older and tenured respondents (most likely to serve on RPT committees) were less likely to value journal prestige and metrics for publishing, while untenured respondents were more likely to value these factors.

These results suggest disconnects between what academics value versus what they think their peers value, and between the importance of journal prestige and metrics for tenured versus untenured faculty in publishing and RPT perceptions.

URL : Why we publish where we do: Faculty publishing values and their relationship to review, promotion and tenure expectations

DOI : https://doi.org/10.1371/journal.pone.0228914

EN

No raw data, no science: another possible source of the reproducibility crisis

Posted on by Hans Dillaerts

Author : Tsuyoshi Miyakawa

A reproducibility crisis is a situation where many scientific studies cannot be reproduced. Inappropriate practices of science, such as HARKing, p-hacking, and selective reporting of positive results, have been suggested as causes of irreproducibility. In this editorial, I propose that a lack of raw data or data fabrication is another possible cause of irreproducibility.

As an Editor-in-Chief of Molecular Brain, I have handled 180 manuscripts since early 2017 and have made 41 editorial decisions categorized as “Revise before review,” requesting that the authors provide raw data.

Surprisingly, among those 41 manuscripts, 21 were withdrawn without providing raw data, indicating that requiring raw data drove away more than half of the manuscripts. I rejected 19 out of the remaining 20 manuscripts because of insufficient raw data.

Thus, more than 97% of the 41 manuscripts did not present the raw data supporting their results when requested by an editor, suggesting a possibility that the raw data did not exist from the beginning, at least in some portions of these cases.

Considering that any scientific study should be based on raw data, and that data storage space should no longer be a challenge, journals, in principle, should try to have their authors publicize raw data in a public database or journal site upon the publication of the paper to increase reproducibility of the published results and to increase public trust in science.

URL : No raw data, no science: another possible source of the reproducibility crisis

DOI : https://doi.org/10.1186/s13041-020-0552-2

EN

Reproducible and transparent research practices in published neurology research

Posted on by Hans Dillaerts

Authors : Trevor Torgerson, Austin L. Johnson, Jonathan Pollard, Daniel Tritz, Matt Vassar

Background

The objective of this study was to evaluate the nature and extent of reproducible and transparent research practices in neurology publications.

Methods

The NLM catalog was used to identify MEDLINE-indexed neurology journals. A PubMed search of these journals was conducted to retrieve publications over a 5-year period from 2014 to 2018.

A random sample of publications was extracted. Two authors conducted data extraction in a blinded, duplicate fashion using a pilot-tested Google form. This form prompted data extractors to determine whether publications provided access to items such as study materials, raw data, analysis scripts, and protocols.

In addition, we determined if the publication was included in a replication study or systematic review, was preregistered, had a conflict of interest declaration, specified funding sources, and was open access.

Results

Our search identified 223,932 publications meeting the inclusion criteria, from which 400 were randomly sampled. Only 389 articles were accessible, yielding 271 publications with empirical data for analysis.

Our results indicate that 9.4% provided access to materials, 9.2% provided access to raw data, 0.7% provided access to the analysis scripts, 0.7% linked the protocol, and 3.7% were preregistered.

A third of sampled publications lacked funding or conflict of interest statements. No publications from our sample were included in replication studies, but a fifth were cited in a systematic review or meta-analysis.

Conclusions

Currently, published neurology research does not consistently provide information needed for reproducibility. The implications of poor research reporting can both affect patient care and increase research waste. Collaborative intervention by authors, peer reviewers, journals, and funding sources is needed to mitigate this problem.

URL : Reproducible and transparent research practices in published neurology research

DOI : https://doi.org/10.1186/s41073-020-0091-5