scholarly journals Data sharing practices and data availability upon request differ across scientific disciplines

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Leho Tedersoo ◽  
Rainer Küngas ◽  
Ester Oras ◽  
Kajar Köster ◽  
Helen Eenmaa ◽  
...  
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Modern Science ◽  
Research Data ◽  
Data Availability ◽  
Research Articles ◽  
Scientific Disciplines ◽  
Funding Agencies ◽  
Share Data ◽  
Bonus Points

AbstractData sharing is one of the cornerstones of modern science that enables large-scale analyses and reproducibility. We evaluated data availability in research articles across nine disciplines in Nature and Science magazines and recorded corresponding authors’ concerns, requests and reasons for declining data sharing. Although data sharing has improved in the last decade and particularly in recent years, data availability and willingness to share data still differ greatly among disciplines. We observed that statements of data availability upon (reasonable) request are inefficient and should not be allowed by journals. To improve data sharing at the time of manuscript acceptance, researchers should be better motivated to release their data with real benefits such as recognition, or bonus points in grant and job applications. We recommend that data management costs should be covered by funding agencies; publicly available research data ought to be included in the evaluation of applications; and surveillance of data sharing should be enforced by both academic publishers and funders. These cross-discipline survey data are available from the plutoF repository.

scholarly journals A survey of researchers' needs and priorities for data sharing

2021 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
James Harney ◽  
Lauren Cadwallader
Keyword(s):  
Data Sharing ◽  
Research Impact ◽  
Open Science ◽  
Research Data ◽  
Data Reuse ◽  
Data Availability ◽  
Data Repositories ◽  
Use Of Data ◽  
Share Data ◽  
Do So

PLOS has long supported Open Science. One of the ways in which we do so is via our stringent data availability policy established in 2014. Despite this policy, and more data sharing policies being introduced by other organizations, best practices for data sharing are adopted by a minority of researchers in their publications. Problems with effective research data sharing persist and these problems have been quantified by previous research as a lack of time, resources, incentives, and/or skills to share data. In this study we built on this research by investigating the importance of tasks associated with data sharing, and researchers’ satisfaction with their ability to complete these tasks. By investigating these factors we aimed to better understand opportunities for new or improved solutions for sharing data. In May-June 2020 we surveyed researchers from Europe and North America to rate tasks associated with data sharing on (i) their importance and (ii) their satisfaction with their ability to complete them. We received 728 completed and 667 partial responses. We calculated mean importance and satisfaction scores to highlight potential opportunities for new solutions to and compare different cohorts.Tasks relating to research impact, funder compliance, and credit had the highest importance scores. 52% of respondents reuse research data but the average satisfaction score for obtaining data for reuse was relatively low. Tasks associated with sharing data were rated somewhat important and respondents were reasonably well satisfied in their ability to accomplish them. Notably, this included tasks associated with best data sharing practice, such as use of data repositories. However, the most common method for sharing data was in fact via supplemental files with articles, which is not considered to be best practice.We presume that researchers are unlikely to seek new solutions to a problem or task that they are satisfied in their ability to accomplish, even if many do not attempt this task. This implies there are few opportunities for new solutions or tools to meet these researcher needs. Publishers can likely meet these needs for data sharing by working to seamlessly integrate existing solutions that reduce the effort or behaviour change involved in some tasks, and focusing on advocacy and education around the benefits of sharing data. There may however be opportunities - unmet researcher needs - in relation to better supporting data reuse, which could be met in part by strengthening data sharing policies of journals and publishers, and improving the discoverability of data associated with published articles.

scholarly journals The intertwining of reputation and sharing – The significance of standardization in preparing research data and the impact of project organization

2020 ◽  
Vol 33 ◽  
pp. 01002
Author(s):  
Saskia-Rabea Schrade
Keyword(s):  
Data Sharing ◽  
Special Form ◽  
Research Data ◽  
External Factors ◽  
Data Preparation ◽  
Project Organization ◽  
Funding Agencies ◽  
Share Data ◽  
Definition Of ◽  
The Impact

Despite efforts to increase scientists’ willingness to share research data political stakeholders and funding agencies, there is still a discrepancy between scientists’ attitude toward data sharing and their actual practice. In a first step, this paper takes a close look at scientists’ definition of research data and the influence of project organization on scientist’ willingness to share data by analyzing interviews with scientists of three different disciplines. As the analysis shows, talking about “data sharing” should always happen in the context of data preparation and its various steps. Additionally, the influence of external factors such as a special form of project organization seems to be limited.

scholarly journals Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences

1970 ◽  
Vol 15 (1) ◽  
pp. 7
Author(s):  
Rebecca Springer ◽  
Danielle Cooper
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Data Repository ◽  
Disciplinary Boundaries ◽  
Success Stories ◽  
Scholarly Communications ◽  
Information Technologists ◽  
Share Data ◽  
Technological Intervention ◽  
Informal Groups

There is a growing perception that science can progress more quickly, more innovatively, and more rigorously when researchers share data with each other. However many scientists are not engaging in data sharing and remain skeptical of its relevance to their work. As organizations and initiatives designed to promote STEM data sharing multiply – within, across, and outside academic institutions – there is a pressing need to decide strategically on the best ways to move forward. In this paper, we propose a new mechanism for conceptualizing and supporting STEM research data sharing.. Successful data sharing happens within data communities, formal or informal groups of scholars who share a certain type of data with each other, regardless of disciplinary boundaries. Drawing on the findings of four large-scale qualitative studies of research practices conducted by Ithaka S+R, as well as the scholarly literature, we identify what constitutes a data community and outline its most important features by studying three success stories, investigating the circumstances under which intensive data sharing is already happening. We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and empower emergent data communities. These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture. We conclude by offering recommendations for ways forward.

scholarly journals PsychData – Experiences from 12 Years of Research Data Archiving

2015 ◽  
Author(s):  
Peter Weiland ◽  
Ina Dehnhard
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Research Data ◽  
Data Reuse ◽  
German Research Foundation ◽  
Cross Sectional ◽  
Data Archiving ◽  
Wide Range ◽  
Domain Specific Knowledge ◽  
Meta Analyses

See video of the presentation.The benefits of making research data permanently accessible through data archives is widely recognized: costs can be reduced by reusing existing data, research results can be compared and validated with results from archived studies, fraud can be more easily detected, and meta-analyses can be conducted. Apart from that, authors may gain recognition and reputation for producing the datasets. Since 2003, the accredited research data center PsychData (part of the Leibniz Institute for Psychology Information in Trier, Germany) documents and archives research data from all areas of psychology and related fields. In the beginning, the main focus was on datasets that provide a high potential for reuse, e.g. longitudinal studies, large-scale cross sectional studies, or studies that were conducted during historically unique conditions. Presently, more and more journal publishers and project funding agencies require researchers to archive their data and make them accessible for the scientific community. Therefore, PsychData also has to serve this need.In this presentation we report on our experiences in operating a discipline-specific research data archive in a domain where data sharing is met with considerable resistance. We will focus on the challenges for data sharing and data reuse in psychology, e.g.large amount of domain-specific knowledge necessary for data curationhigh costs for documenting the data because of a wide range on non-standardized measuressmall teams and little established infrastructures compared with the "big data" disciplinesstudies in psychology not designed for reuse (in contrast to the social sciences)data protectionresistance to sharing dataAt the end of the presentation, we will provide a brief outlook on DataWiz, a new project funded by the German Research Foundation (DFG). In this project, tools will be developed to support researchers in documenting their data during the research phase.

scholarly journals Perceptions and Attitudes toward Data Sharing among Dental Researchers

2018 ◽  
Vol 4 (1) ◽  
pp. 68-75 ◽  
Author(s):  
H. Spallek ◽  
S.M. Weinberg ◽  
M. Manz ◽  
S. Nanayakkara ◽  
X. Zhou ◽  
...  
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
International Association ◽  
Improve Patient Care ◽  
Research Data ◽  
Research Subjects ◽  
Data Repositories ◽  
Use Of Data ◽  
Share Data ◽  
Past Experiences

Introduction: Increasing attention is being given to the roles of data management and data sharing in the advancement of research. This study was undertaken to explore opinions and past experiences of established dental researchers as related to data sharing and data management. Methods: Researchers were recruited from the International Association for Dental Research scientific groups to complete a survey consisting of Likert-type, multiple-choice, and open-ended questions. Results: All 42 respondents indicated that data sharing should be promoted and facilitated, but many indicated reservations or concerns about the proper use of data and the protection of research subjects. Many had used data from data repositories and received requests for data originating from their studies. Opinions varied regarding restrictions such as requirements to share data and the time limits of investigator rights to keep data. Respondents also varied in their methods of data management and storage, with younger respondents and those with higher direct costs of their research tending to use dedicated experts to manage their data. Discussion: The expressed respondent support for research data sharing, with the noted concerns, complements the idea of developing managed data clearinghouses capable of promoting, managing, and overseeing the data-sharing process. Knowledge Transfer Statement: Researchers can use the results of this study to evaluate and improve management and sharing of research data. By encouraging and facilitating the data-sharing process, research can advance more efficiently, and research findings can be implemented into practice more rapidly to improve patient care and the overall oral health of populations.

scholarly journals A Standard for the Scholarly Citation of Archaeological Data as an Incentive to Data Sharing

2018 ◽  
Vol 6 (2) ◽  
pp. 125-143 ◽  
Author(s):  
Ben Marwick ◽  
Suzanne E. Pilaar Birch
Keyword(s):  
Data Sharing ◽  
Small Proportion ◽  
Ad Hoc ◽  
Research Data ◽  
The State ◽  
Data Availability ◽  
Pilot Studies ◽  
Editorial Policies ◽  
Archaeological Data ◽  
E Mail

ABSTRACTHow do archaeologists share their research data, if at all? We review what data are, according to current influential definitions, and previous work on the benefits, costs, and norms of data sharing in the sciences broadly. To understand data sharing in archaeology, we present the results of three pilot studies: requests for data by e-mail, review of data availability in published articles, and analysis of archaeological datasets deposited in repositories. We find that archaeologists are often willing to share but that discipline-wide sharing is patchy and ad hoc. Legislation and mandates are effective at increasing data sharing, but editorial policies at journals lack adequate enforcement. Although most of the data available at repositories are licensed to enable flexible reuse, only a small proportion of the data are stored in structured formats for easy reuse. We present some suggestions for improving the state of date sharing in archaeology; among these is a standard for citing datasets to ensure that researchers making their data publicly available receive appropriate credit.

scholarly journals A Research data Sharing Game

2014 ◽  
Author(s):  
Tessa E Pronk ◽  
Paulien H Wiersma ◽  
Anne van Weerden
Keyword(s):  
Game Theory ◽  
Decision Theory ◽  
Data Sharing ◽  
Scientific Community ◽  
Data Retrieval ◽  
Research Data ◽  
Top Down ◽  
Average Efficiency ◽  
Natural Tendency ◽  
Share Data

While reusing research data has evident benefits for the scientific community as a whole, decisions to archive and share these data are primarily made by individual researchers. For individuals, it is less obvious that the benefits of sharing data outweigh the associated costs, i.e. time and money. In this sense the problem of data sharing resembles a typical game in interactive decision theory, more commonly known as game theory. Within this framework we analyse in this paper how different measures to promote sharing and reuse of research data affect sharing and not sharing individuals. We find that the scientific community can benefit from top-down policies to enhance sharing data even when the act of sharing itself implies a cost. Namely, if (almost) everyone shares, many individuals can gain a higher efficiency as datasets can be reused. Additionally, measures to ensure better data retrieval and quality can compensate for sharing costs by enabling reuse. Nevertheless, an individual researcher who decides not to share omits the costs of sharing. Assuming that the natural tendency will be to use a strategy that will lead to maximisation of individual efficiency it is seen that, as more individuals decide not to share, there is a point at which average efficiency for both sharing and non-sharing researchers becomes lower than was originally the case and scientific community efficiency steadily drops. With this in mind, we conclude that the key to motivate the researcher to share data lies in reducing the costs associated with sharing, or even better, turning it into a benefit.

scholarly journals A descriptive analysis of the data availability statements accompanying medRxiv preprints and a comparison with their published counterparts

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250887
Author(s):  
Luke A. McGuinness ◽  
Athena L. Sheppard
Keyword(s):  
Data Sharing ◽  
Descriptive Analysis ◽  
Open Data ◽  
System Change ◽  
Research Data ◽  
Data Availability ◽  
Published Data ◽  
Editorial Policies ◽  
Journal Editors ◽  
Closed Data

Objective To determine whether medRxiv data availability statements describe open or closed data—that is, whether the data used in the study is openly available without restriction—and to examine if this changes on publication based on journal data-sharing policy. Additionally, to examine whether data availability statements are sufficient to capture code availability declarations. Design Observational study, following a pre-registered protocol, of preprints posted on the medRxiv repository between 25th June 2019 and 1st May 2020 and their published counterparts. Main outcome measures Distribution of preprinted data availability statements across nine categories, determined by a prespecified classification system. Change in the percentage of data availability statements describing open data between the preprinted and published versions of the same record, stratified by journal sharing policy. Number of code availability declarations reported in the full-text preprint which were not captured in the corresponding data availability statement. Results 3938 medRxiv preprints with an applicable data availability statement were included in our sample, of which 911 (23.1%) were categorized as describing open data. 379 (9.6%) preprints were subsequently published, and of these published articles, only 155 contained an applicable data availability statement. Similar to the preprint stage, a minority (59 (38.1%)) of these published data availability statements described open data. Of the 151 records eligible for the comparison between preprinted and published stages, 57 (37.7%) were published in journals which mandated open data sharing. Data availability statements more frequently described open data on publication when the journal mandated data sharing (open at preprint: 33.3%, open at publication: 61.4%) compared to when the journal did not mandate data sharing (open at preprint: 20.2%, open at publication: 22.3%). Conclusion Requiring that authors submit a data availability statement is a good first step, but is insufficient to ensure data availability. Strict editorial policies that mandate data sharing (where appropriate) as a condition of publication appear to be effective in making research data available. We would strongly encourage all journal editors to examine whether their data availability policies are sufficiently stringent and consistently enforced.

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

Data ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 29 ◽  
Author(s):  
Rafael Aleixandre-Benavent ◽  
Antonio Vidal-Infer ◽  
Adolfo Alonso-Arroyo ◽  
Fernanda Peset ◽  
Antonia Ferrer Sapena
Keyword(s):  
Data Sharing ◽  
Research Group ◽  
Storage Systems ◽  
Personal Information ◽  
Management Plan ◽  
Research Data ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
Legal Questions ◽  
Share Data

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.

scholarly journals A Unique Research Data Infrastructure for Educational Research and Beyond: The National Educational Panel Study

2016 ◽  
Vol 236 (4) ◽  
Author(s):  
Daniel Fuß ◽  
Jutta von Maurice ◽  
Hans-Günther Roßbach
Keyword(s):  
Educational Research ◽  
Large Scale ◽  
Panel Study ◽  
Data Access ◽  
Research Data ◽  
Data Availability ◽  
Background Information ◽  
Data Infrastructure ◽  
Collection Data ◽  
Set Up

AbstractThe article provides an insight into the conceptual and methodological framework as well as the research data infrastructure of the German National Educational Panel Study (NEPS). The NEPS study has been set up to build a profound empirical basis for the description and analysis of educational processes and competence development across the life span. Its large-scale database consists of longitudinal information from more than 60,000 target respondents – distributed over six different starting cohorts ranging from newborns to adults – and from relevant context persons such as parents or teachers. The complex multicohort sequence design schedules annual or even semiannual survey waves including a broad spectrum of competence assessments. All data are thoroughly prepared, documented, and disseminated free of charge in the form of regularly expanded Scientific Use Files. In addition to some background information about NEPS in general, this paper primarily focuses on issues of data collection, data structure, data availability, and the requirements for different types of data access. The number of more than 1,000 data users involved in over 700 research projects so far serves to highlight the potential of NEPS as a unique research data infrastructure for educational research and beyond.

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