scholarly journals Open data repositories: Current risks and opportunities

2020 ◽  
Vol 81 (2) ◽  
pp. 62
Author(s):  
Abigail Goben ◽  
Robert J. Sandusky
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Open Data ◽  
Management Consulting ◽  
Academic Institutions ◽  
Data Repositories ◽  
Professional Societies ◽  
Funding Agencies ◽  
Academic Researchers

As data sharing has become a more familiar obligation for academic researchers, there has been a correlating increase in the roles that librarians play supporting open data repositories and providing data management consulting and services. These repositories are sponsored by governments, funding agencies, academic institutions, professional societies, and scholarly publishers.

scholarly journals Potential opportunities and risks of sharing agricultural research data in Tanzania

2021 ◽  
Vol 45 (3-4) ◽  
Author(s):  
Anajoyce Samuel Katabalwa ◽  
Jo Bates ◽  
Pamela Abbott
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Agricultural Research ◽  
Research Output ◽  
Open Data ◽  
Research Literature ◽  
Research Data ◽  
Data Repositories ◽  
The Government ◽  
Support Research

Purpose: The purpose of this paper was to examine the potential opportunities and risks of sharing agricultural research data in Tanzania identified in the existing research literature. Design/methodology/approach: The study involved a review of the literature on research data sharing practices. Findings: The findings indicate that, research data sharing have significant positive benefits among researchers such as increase high research impact; enhancing international community collaboration among researchers with same interests; improving scientific transparency and accuracy of data (Rappert and Bezuidenhout, 2016); increasing research output whereby a single dataset can be used to generate more than one article by different authors; and many more. The risks hampering data sharing practices includes researchers’ fears that data will be scooped, poached or misused (Onyancha, 2016); unreliable electric power; lack of fund to support research data sharing activities; absence of institutional governmental support for data management; perceived lack of evidence benefits (Leonelli, Rappert and Bezuidenhout, 2018); and others. However, in Tanzania research data sharing is relatively new, thus, no any governmental agency mandating or encouraging research data sharing; therefore, there is no research data management; no research open data repositories and no research data sharing policy at any agricultural institution in Tanzania. The study recommends that agricultural researchers should be sensitized to share their data, research data policy and data repositories should also be established to support data sharing practices in Tanzania. Originality and usefulness: From the available literature, this has been the first time that an effort has been made to examine the potential opportunities and risks of sharing agricultural research data in Tanzania. The study could be used by agricultural institutions and other institutions to assess the researchers’ needs in supporting research data sharing. Also, it can be used by the government and institutions to see the need of establishing open data repositories and open data policies to support research data sharing.

scholarly journals NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany

2020 ◽  
Vol 6 ◽  
Author(s):  
Christoph Steinbeck ◽  
Oliver Koepler ◽  
Felix Bach ◽  
Sonja Herres-Pawlis ◽  
Nicole Jung ◽  
...  
Keyword(s):  
Data Management ◽  
Data Science ◽  
Open Data ◽  
Research Data ◽  
Data Standards ◽  
Data Repositories ◽  
Data Infrastructure ◽  
Research Data Management ◽  
Wide Range ◽  
Chemistry Community

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

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 Publishing descriptions of non-public clinical datasets: guidance for researchers, repositories, editors and funding organisations

2015 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
Varsha Khodiyar ◽  
Andrew L Hufton ◽  
Susanna-Assunta Sansone
Keyword(s):  
Clinical Research ◽  
Data Sharing ◽  
Peer Review Process ◽  
Open Data ◽  
Data Access ◽  
Research Data ◽  
Future Research ◽  
Patient Privacy ◽  
Journal Articles ◽  
Data Repositories

AbstractSharing of experimental clinical research data usually happens between individuals or research groups rather than via public repositories, in part due to the need to protect research participant privacy. This approach to data sharing makes it difficult to connect journal articles with their underlying datasets and is often insufficient for ensuring access to data in the long term. Voluntary data sharing services such as the Yale Open Data Access (YODA) and Clinical Study Data Request (CSDR) projects have increased accessibility to clinical datasets for secondary uses while protecting patient privacy and the legitimacy of secondary analyses but these resources are generally disconnected from journal articles – where researchers typically search for reliable information to inform future research. New scholarly journal and article types dedicated to increasing accessibility of research data have emerged in recent years and, in general, journals are developing stronger links with data repositories. There is a need for increased collaboration between journals, data repositories, researchers, funders, and voluntary data sharing services to increase the visibility and reliability of clinical research. We propose changes to the format and peer-review process for journal articles to more robustly link them to data that are only available on request. We also propose additional features for data repositories to better accommodate non-public clinical datasets, including Data Use Agreements (DUAs).

scholarly journals 11,000 researchers gave their views on data sharing, here's what we learned

2019 ◽  
Author(s):  
Mithu Lucraft ◽  
Samuel Winthrop
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Market Research ◽  
Open Data ◽  
White Paper ◽  
Research Community ◽  
Data Publishing ◽  
Training And Education ◽  
Collaborative Action ◽  
Share Data

Good data sharing can make research more productive, more likely to be cited, and unlock innovation for the good of society. In 2019, a Springer Nature white paper (Lucraft et al. 2019), based on surveys with more than 11,000 researchers internationally, set out key challenges in data management and data sharing. We found: Data sharing is increasing: more than 64% of researchers in a 2018 survey said they made their data openly available. The majority of researchers see data sharing as important: across three surveys, when asked about the importance of making data discoverable, researchers gave an average rating of 7.5 out of 10. Data sharing and planning is currently suboptimal: The majority of the research community are not yet managing or sharing data in ways that make it findable, accessible or reusable. Increasingly, funders and other expert groups (European Commission 2018) are emphasising the need for data that is FAIR (findable, accessible, interoperable and re-useable). To shift the needle on data sharing and to reap the benefits from more widely-available open data, collaborative action is required. In this presentation, we will discuss the five measures we believe are needed to make data sharing the norm: Clear policy: from funders, institutions, journals/publishers, and research communities themselves. Better credit: to make data sharing worth a researcher’s time. Explicit funding: for data management and data sharing, as well as data publishing. Practical help: for organising data, finding appropriate repositories, and provision of faster, easier routes to share data. Training and education: to answer common questions from researchers on data sharing and to help build skills and knowledge. We will draw on evidence and case studies from across Europe and beyond, as well as further feedback from our market research.

scholarly journals Opening Pandora’s Box: Peeking inside psychology’s data sharing practices, and seven recommendations for change.

2019 ◽  
Author(s):  
John Towse ◽  
David Alexander Ellis ◽  
Andrea Towse
Keyword(s):  
Social Science ◽  
Data Sharing ◽  
Open Data ◽  
Research Papers ◽  
Research Project ◽  
Psychological Science ◽  
Funding Agencies ◽  
The Impact

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.

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

2020 ◽  
Author(s):  
John N. Towse ◽  
David A Ellis ◽  
Andrea S Towse
Keyword(s):  
Social Science ◽  
Data Sharing ◽  
Open Data ◽  
Research Papers ◽  
Research Project ◽  
Psychological Science ◽  
Funding Agencies ◽  
The Impact

Abstract 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.

Reconciling stakeholder interests in the era of open data

2018 ◽  
Vol 82 (3) ◽  
pp. 253-259
Author(s):  
Alessandro S. De Nadai
Keyword(s):  
Mental Health ◽  
Data Analysis ◽  
Data Sharing ◽  
Health Research ◽  
Open Data ◽  
Secondary Data ◽  
Mental Health Research ◽  
Secondary Data Analysis ◽  
Stakeholder Interests ◽  
Funding Agencies

While there is great enthusiasm about new data sharing initiatives in mental health research, some concerns have recently been expressed that reflect tension between those who generate data and those who engage in secondary data analysis. While many aspects of data sharing have been considered, some of this tension has not been fully addressed. If this tension continues to go unresolved, enthusiasm for data sharing initiatives may be hindered. The author suggests solutions to these issues after carefully considering respective stakeholder interests (including those of patients, researchers, and funding agencies).

scholarly journals Researchers at Arab Universities Hold Positive Views on Research Data Management and Data Sharing

2020 ◽  
Vol 15 (2) ◽  
pp. 168-170
Author(s):  
Jennifer Kaari
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Data Privacy ◽  
Management Practices ◽  
Open Data ◽  
Scientific Progress ◽  
Management Plan ◽  
Research Data ◽  
Data Repository ◽  
Research Data Management

A Review of: Elsayed, A. M., & Saleh, E. I. (2018). Research data management and sharing among researchers in Arab universities: An exploratory study. IFLA Journal, 44(4), 281–299. https://doi.org/10.1177/0340035218785196 Abstract Objective – To investigate researchers’ practices and attitudes regarding research data management and data sharing. Design – Email survey. Setting – Universities in Egypt, Jordan, and Saudi Arabia. Subjects – Surveys were sent to 4,086 academic faculty researchers. Methods – The survey was emailed to faculty at three Arab universities, targeting faculty in the life sciences and engineering. The survey was created using Google Docs and remained open for five months. Participants were asked basic demographic questions, questions regarding their research data and metadata practices, and questions regarding their data sharing practices. Main Results – The authors received 337 responses, for a response rate of 8%. The results showed that 48.4% of respondents had a data management plan and that 97% were responsible for preserving their own data. Most respondents stored their research data on their personal storage devices. The authors found that 64.4% of respondents reported sharing their research data. Respondents most frequently shared their data by publishing in a data research journal, sharing through academic social networks such as ResearchGate, and providing data upon request to peers. Only 5.1% of respondents shared data through an open data repository.  Of those who did not share data, data privacy and confidentiality were the most common reasons cited. Of the respondents who did share their data, contributing to scientific progress and increased citation and visibility were the primary reasons for doing so. A total of 59.6% of respondents stated that they needed more training in research data management from their universities. Conclusion – The authors conclude that researchers at Arab universities are still primarily responsible for their own data and that data management planning is still a new concept to most researchers. For the most part, the researchers had a positive attitude toward data sharing, although depositing data in open repositories is still not a widespread practice. The authors conclude that in order to encourage strong data management practices and open data sharing among Arab university researchers, more training and institutional support is needed.

scholarly journals Open Data in Scientific Communication

2018 ◽  
Vol 60 (3) ◽  
pp. 192-198
Author(s):  
Dorota Grygoruk
Keyword(s):  
Information Technology ◽  
Open Access ◽  
Data Management ◽  
Data Sharing ◽  
Open Data ◽  
Scientific Communication ◽  
Scientific Data ◽  
Scientific Publications ◽  
Management Policies ◽  
Access Model

Abstract The development of information technology makes it possible to collect and analyse more and more data resources. The results of research, regardless of the discipline, constitute one of main sources of data. Currently, the research results are increasingly being published in the Open Access model. The Open Access concept has been accepted and recommended worldwide by many institutions financing and implementing research. Initially, the idea of openness concerned only the results of research and scientific publications; at present, more attention is paid to the problem of sharing scientific data, including raw data. Proceedings towards open data are intricate, as data specificity requires the development of an appropriate legal, technical and organizational model, followed by the implementation of data management policies at both the institutional and national levels. The aim of this publication was to present the development of the open data concept in the context of open access idea and problems related to defining data in the process of data sharing and data management.

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