Archives des mots-clés : data sharing

Research Data Sharing in Spain: Exploring Determinants, Practices, and Perceptions

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Authors : Rafael Aleixandre-Benavent, Antonio Vidal-Infer, Adolfo Alonso-Arroyo, Fernanda Peset, Antonia Ferrer Sapena

This work provides an overview of a Spanish survey on research data, which was carried out within the framework of the project Datasea at the beginning of 2015. It is covered by the objectives of sustainable development (goal 9) to support the research.

The purpose of the study was to identify the habits and current experiences of Spanish researchers in the health sciences in relation to the management and sharing of raw research data. Method: An electronic questionnaire composed of 40 questions divided into three blocks was designed.

The three Section s contained questions on the following aspects: (A) personal information; (B) creation and reuse of data; and (C) preservation of data. The questionnaire was sent by email to a list of universities in Spain to be distributed among their researchers and professors. A total of 1063 researchers completed the questionnaire.

More than half of the respondents (54.9%) lacked a data management plan; nearly a quarter had storage systems for the research group; 81.5% used personal computers to store data; “Contact with colleagues” was the most frequent means used to locate and access other researchers’ data; and nearly 60% of researchers stated their data were available to the research group and collaborating colleagues.

The main fears about sharing were legal questions (47.9%), misuse or interpretation of data (42.7%), and loss of authorship (28.7%).

The results allow us to understand the state of data sharing among Spanish researchers and can serve as a basis to identify the needs of researchers to share data, optimize existing infrastructure, and promote data sharing among those who do not practice it yet.

URL : Research Data Sharing in Spain: Exploring Determinants, Practices, and Perceptions

DOI : https://doi.org/10.3390/data5020029

Reading the fine print: A review and analysis of business journals’ data sharing policies

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Authors : Brianne Dosch, Tyler Martindale

Business librarians offer many data services to their researchers. These services are often focused more on discovery, visualization, and analysis than general data management. But, with the replication crisis facing many business disciplines, there is a need for business librarians to offer more data sharing and general data management support to their researchers.

To find evidence of this data need, 146 business journal’s data sharing policies were reviewed and analyzed to uncover meaningful trends in business research. Results of the study indicate data sharing is not mandated by business journals.

However, data sharing is often encouraged and recommended. This journal policy content analysis provides evidence that business researchers have opportunities to share their research data, and with the right data management support, business librarians can play a significant role in improving the data sharing behaviors of business researchers.

DOI : https://doi.org/10.1080/08963568.2020.1847549

Opening Pandora’s Box: Peeking inside Psychology’s data sharing practices, and seven recommendations for change

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Authors : John N. Towse, David A Ellis, Andrea S Towse

Open data-sharing is a valuable practice that ought to enhance the impact, reach, and transparency of a research project.

While widely advocated by many researchers and mandated by some journals and funding agencies, little is known about detailed practices across psychological science. In a pre-registered study, we show that overall, few research papers directly link to available data in many, though not all, journals.

Most importantly, even where open data can be identified, the majority of these lacked completeness and reusability—conclusions that closely mirror those reported outside of Psychology.

Exploring the reasons behind these findings, we offer seven specific recommendations for engineering and incentivizing improved practices, so that the potential of open data can be better realized across psychology and social science more generally.

URL : Opening Pandora’s Box: Peeking inside Psychology’s data sharing practices, and seven recommendations for change

DOI : https://doi.org/10.3758/s13428-020-01486-1

The views, perspectives, and experiences of academic researchers with data sharing and reuse: A meta-synthesis

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Authors : Laure Perrier, Erik Blondal, Heather MacDonald

Background

Funding agencies and research journals are increasingly demanding that researchers share their data in public repositories. Despite these requirements, researchers still withhold data, refuse to share, and deposit data that lacks annotation.

We conducted a meta-synthesis to examine the views, perspectives, and experiences of academic researchers on data sharing and reuse of research data.

Methods

We searched the published and unpublished literature for studies on data sharing by researchers in academic institutions. Two independent reviewers screened citations and abstracts, then full-text articles.

Data abstraction was performed independently by two investigators. The abstracted data was read and reread in order to generate codes. Key concepts were identified and thematic analysis was used for data synthesis.

Results

We reviewed 2005 records and included 45 studies along with 3 companion reports. The studies were published between 2003 and 2018 and most were conducted in North America (60%) or Europe (17%).

The four major themes that emerged were data integrity, responsible conduct of research, feasibility of sharing data, and value of sharing data. Researchers lack time, resources, and skills to effectively share their data in public repositories.

Data quality is affected by this, along with subjective decisions around what is considered to be worth sharing. Deficits in infrastructure also impede the availability of research data. Incentives for sharing data are lacking.

Conclusion

Researchers lack skills to share data in a manner that is efficient and effective. Improved infrastructure support would allow them to make data available quickly and seamlessly. The lack of incentives for sharing research data with regards to academic appointment, promotion, recognition, and rewards need to be addressed.

URL : The views, perspectives, and experiences of academic researchers with data sharing and reuse: A meta-synthesis

DOI : https://doi.org/10.1371/journal.pone.0234275.s002

ODDPub – a Text-Mining Algorithm to Detect Data Sharing in Biomedical Publications

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Authors: Nico Riedel, Miriam Kip, Evgeny Bobro

Open research data are increasingly recognized as a quality indicator and an important resource to increase transparency, robustness and collaboration in science. However, no standardized way of reporting Open Data in publications exists, making it difficult to find shared datasets and assess the prevalence of Open Data in an automated fashion.

We developed ODDPub (Open Data Detection in Publications), a text-mining algorithm that screens biomedical publications and detects cases of Open Data. Using English-language original research publications from a single biomedical research institution (n = 8689) and randomly selected from PubMed (n = 1500) we iteratively developed a set of derived keyword categories.

ODDPub can detect data sharing through field-specific repositories, general-purpose repositories or the supplement. Additionally, it can detect shared analysis code (Open Code).

To validate ODDPub, we manually screened 792 publications randomly selected from PubMed. On this validation dataset, our algorithm detected Open Data publications with a sensitivity of 0.73 and specificity of 0.97.

Open Data was detected for 11.5% (n = 91) of publications. Open Code was detected for 1.4% (n = 11) of publications with a sensitivity of 0.73 and specificity of 1.00. We compared our results to the linked datasets found in the databases PubMed and Web of Science.

Our algorithm can automatically screen large numbers of publications for Open Data. It can thus be used to assess Open Data sharing rates on the level of subject areas, journals, or institutions. It can also identify individual Open Data publications in a larger publication corpus. ODDPub is published as an R package on GitHub.

URL : ODDPub – a Text-Mining Algorithm to Detect Data Sharing in Biomedical Publications

DOI : http://doi.org/10.5334/dsj-2020-042

Data sharing policies of journals in life, health, and physical sciences indexed in Journal Citation Reports

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Authors : Jihyun Kim, Soon Kim, Hye-Min Cho, Jae Hwa Chang, Soo Young Kim

Background

Many scholarly journals have established their own data-related policies, which specify their enforcement of data sharing, the types of data to be submitted, and their procedures for making data available.

However, except for the journal impact factor and the subject area, the factors associated with the overall strength of the data sharing policies of scholarly journals remain unknown.

This study examines how factors, including impact factor, subject area, type of journal publisher, and geographical location of the publisher are related to the strength of the data sharing policy.

Methods

From each of the 178 categories of the Web of Science’s 2017 edition of Journal Citation Reports, the top journals in each quartile (Q1, Q2, Q3, and Q4) were selected in December 2018. Of the resulting 709 journals (5%), 700 in the fields of life, health, and physical sciences were selected for analysis.

Four of the authors independently reviewed the results of the journal website searches, categorized the journals’ data sharing policies, and extracted the characteristics of individual journals.

Univariable multinomial logistic regression analyses were initially conducted to determine whether there was a relationship between each factor and the strength of the data sharing policy.

Based on the univariable analyses, a multivariable model was performed to further investigate the factors related to the presence and/or strength of the policy.

Results

Of the 700 journals, 308 (44.0%) had no data sharing policy, 125 (17.9%) had a weak policy, and 267 (38.1%) had a strong policy (expecting or mandating data sharing). The impact factor quartile was positively associated with the strength of the data sharing policies.

Physical science journals were less likely to have a strong policy relative to a weak policy than Life science journals (relative risk ratio [RRR], 0.36; 95% CI [0.17–0.78]). Life science journals had a greater probability of having a weak policy relative to no policy than health science journals (RRR, 2.73; 95% CI [1.05–7.14]).

Commercial publishers were more likely to have a weak policy relative to no policy than non-commercial publishers (RRR, 7.87; 95% CI, [3.98–15.57]). Journals by publishers in Europe, including the majority of those located in the United Kingdom and the Netherlands, were more likely to have a strong data sharing policy than a weak policy (RRR, 2.99; 95% CI [1.85–4.81]).

Conclusions

These findings may account for the increase in commercial publishers’ engagement in data sharing and indicate that European national initiatives that encourage and mandate data sharing may influence the presence of a strong policy in the associated journals.

Future research needs to explore the factors associated with varied degrees in the strength of a data sharing policy as well as more diverse characteristics of journals related to the policy strength.

URL : Data sharing policies of journals in life, health, and physical sciences indexed in Journal Citation Reports

DOI : https://doi.org/10.7717/peerj.9924

Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

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Authors : Nicolas Lombard, A. Gasmi, L. Sulpice, K. Boudjema, Damien Bergeat

Objective

To describe surgical journals’ position statements on data-sharing policies (primary objective) and to describe key features of their research transparency promotion.

Methods

Only “SURGICAL” journals with an impact factor higher than 2 (Web of Science) were eligible for the study. They were included, if there were explicit instructions for clinical trial publication in the official instructions for authors (OIA) or if they had published randomised controlled trial (RCT) between 1 January 2016 and 31 December 2018.

The primary outcome was the existence of a data-sharing policy included in the instructions for authors. Data-sharing policies were grouped into 3 categories, inclusion of data-sharing policy mandatory, optional, or not available.

Details on research transparency promotion were also collected, namely the existence of a “prospective registration of clinical trials requirement policy”, a conflict of interests (COIs) disclosure requirement, and a specific reference to reporting guidelines, such as CONSORT for RCT.

Results

Among the 87 surgical journals identified, 82 were included in the study: 67 (82%) had explicit instructions for RCT and the remaining 15 (18%) had published at least one RCT. The median impact factor was 2.98 [IQR = 2.48–3.77], and in 2016 and 2017, the journals published a median of 11.5 RCT [IQR = 5–20.75].

The OIA of four journals (5%) stated that the inclusion of a data-sharing statement was mandatory, optional in 45% (n = 37), and not included in 50% (n = 41).

No association was found between journal characteristics and the existence of data-sharing policies (mandatory or optional). A “prospective registration of clinical trials requirement” was associated with International Committee of Medical Journal Editors (ICMJE) allusion or affiliation and higher impact factors.

Journals with specific RCT instructions in their OIA and journals referenced on the ICMJE website more frequently mandated the use of CONSORT guidelines.

Conclusion

Research transparency promotion is still limited in surgical journals. Standardisation of journal requirements according to ICMJE guidelines could be a first step forward for research transparency promotion in surgery.

URL : Research transparency promotion by surgical journals publishing randomised controlled trials: a survey

DOI : https://doi.org/10.1186/s13063-020-04756-7