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 ◽  
Individual Researcher ◽  
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, for example 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 how measures to promote sharing and reuse of research data affect individuals who do and do not share data. 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 receive benefits, as datasets in our model can be reused to achieve a higher efficiency (i.e. more publications, higher quality papers). Surprisingly, as sharing implies a cost, even sharing individuals themselves, in a community in which sharing is common, can gain a higher efficiency than individuals who do not share, in a community in which sharing is not common. In addition to these findings, we find that measures to ensure better data retrieval and quality can compensate for sharing costs by further 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, we see the average scientific community efficiency in our model steadily drop as more individuals decide not to share. 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 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 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 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 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 Data Sharing Policies: Share Well and You Shall be Rewarded

2021 ◽  
Author(s):  
Jean Peccoud
Keyword(s):  
Data Sharing ◽  
Scientific Community ◽  
Computer Software ◽  
Research Data ◽  
Objective Data ◽  
Scientific Publishing ◽  
Publishing Process ◽  
Administrative Burden ◽  
Textual Description ◽  
The Impact

Abstract Sharing research data is an integral part of the scientific publishing process. By sharing data authors enable their readers to use their results in a way that the textual description of the results does not allow by itself. In order to achieve this objective, data should be shared in a way that makes it as easy as possible for readers to import them in computer software where they can be viewed, manipulated, and analyzed. Many authors and reviewers seem to misunderstand the purpose of the data sharing policies developed by journals. Rather than being an administrative burden that authors should comply with to get published, the objective of these policies is to help authors maximize the impact of their work by allowing other members of the scientific community to build upon it. Authors and reviewers need to understand the purpose of data sharing policies to assist editors and publishers in their efforts to ensure that every article published complies with them.

scholarly journals Research Data Management and Data Sharing among Research Scholars of Life Sciences and Social Sciences

2019 ◽  
Vol 39 (06) ◽  
pp. 290-299
Author(s):  
Naushad Ali PM ◽  
Sidra Saeed
Keyword(s):  
Social Sciences ◽  
Data Management ◽  
Data Sharing ◽  
Life Sciences ◽  
Scientific Progress ◽  
Research Data ◽  
Key Factors ◽  
Research Data Management ◽  
Share Data

This study investigates perception of research scholars towards research data management and sharing. A survey was conducted among research scholars from Faculty of Life Sciences and Social Sciences, Aligarh Muslim University (AMU). In total, 352 participants filled out the questionnaire. The study shows that research scholars ofFaculty of Social Sciences are more willing to share their research data as compared to Research Scholars of Life Sciences. Contributing to scientific progress and increasing research citations and visibility were the key factors that motivated researchers to share data. However, confidentiality and data misuse were the main concerns among those who were unwilling to share. Finally, some recommendations to improve the of data management and sharing practices are presented.

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 research data sharing game

2015 ◽  
Author(s):  
Tessa E Pronk ◽  
Paulien H Wiersma ◽  
Anne van Weerden ◽  
Feike Schieving
Keyword(s):  
Data Sharing ◽  
Scientific Community ◽  
Theoretical Framework ◽  
Research Data ◽  
Stable Strategy ◽  
Policy Measures ◽  
Conflicting Interests ◽  
Almost All

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. In this paper we analyse, within a game theoretical framework, how sharing and reuse of research data affect individuals who share or do not share their datasets. We construct a model in which there is a cost associated with sharing datasets whereas reusing such sets implies a benefit. In our calculations conflicting interests appeared for researchers. Individual researchers are always better off not sharing and omitting the sharing cost, at the same time both sharing and not sharing researchers are better off if (almost) all researchers share. Namely, the more researchers share, the more benefit can be gained by the reuse of those datasets. We simulated several policy measures to increase benefits for researchers sharing or reusing datasets. Results point out that, although policies should be able to increase the rate of sharing researchers, and increased discoverability and dataset quality could partly compensate for costs, a better measure would be to directly lower the costs for sharing, or even turn it into a (citation-) benefit. Making data available would in that case become the most profitable, and therefore stable, strategy. This means researchers would willingly make their datasets available, and arguably in the best possible way to enable reuse, making other policy measures less pressing.

scholarly journals A research data sharing game

2015 ◽  
Author(s):  
Tessa E Pronk ◽  
Paulien H Wiersma ◽  
Anne van Weerden ◽  
Feike Schieving
Keyword(s):  
Data Sharing ◽  
Scientific Community ◽  
Theoretical Framework ◽  
Research Data ◽  
Stable Strategy ◽  
Policy Measures ◽  
Conflicting Interests ◽  
Almost All

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. In this paper we analyse, within a game theoretical framework, how sharing and reuse of research data affect individuals who share or do not share their datasets. We construct a model in which there is a cost associated with sharing datasets whereas reusing such sets implies a benefit. In our calculations conflicting interests appeared for researchers. Individual researchers are always better off not sharing and omitting the sharing cost, at the same time both sharing and not sharing researchers are better off if (almost) all researchers share. Namely, the more researchers share, the more benefit can be gained by the reuse of those datasets. We simulated several policy measures to increase benefits for researchers sharing or reusing datasets. Results point out that, although policies should be able to increase the rate of sharing researchers, and increased discoverability and dataset quality could partly compensate for costs, a better measure would be to directly lower the costs for sharing, or even turn it into a (citation-) benefit. Making data available would in that case become the most profitable, and therefore stable, strategy. This means researchers would willingly make their datasets available, and arguably in the best possible way to enable reuse, making other policy measures less pressing.

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