Cancer Research Data-Sharing Networks

Open research data is data that is free to access, reuse, and redistribute. This study focuses on the perceptions, opinions and experiences of staff and researchers of research institutes on topics related to open research data. Furthermore, the differences across gender, role in the research organization and research field were investigated. An international questionnaire survey, translated into Finnish and Swedish, was used as the data collection instrument. An online survey was distributed through an open science related network to Finnish research organizations. In the end, 469 responded to all 24 questions of the survey. Findings indicate that many are still unaware or uncertain about issues related to data sharing and long-term data storage. Women as well as staff and researchers of medical and health sciences were most concerned about the possible problems associated with data sharing. Those in the beginning of their scientific careers, hesitated about sharing their data.

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Práticas e percepções dos pesquisadores brasileiros sobre serviços de acesso aberto a dados de pesquisa | Practices and perceptions of Brazilian researchers on open access to research data

Liinc em Revista ◽

10.18617/liinc.v15i2.4771 ◽

2019 ◽

Vol 15 (2) ◽

Author(s):

Sonia Elisa Caregnato ◽

Samile Andrea de Souza Vanz ◽

Caterina Groposo Pavão ◽

Paula Caroline Jardim Schifino Passos ◽

Eduardo Borges ◽

...

Keyword(s):

Open Access ◽

Data Sharing ◽

Research Data ◽

Exploratory Analysis ◽

Data Reuse ◽

Institutional Repositories ◽

Open Research

RESUMO O artigo apresenta análise exploratória das práticas e das percepções a respeito do acesso aberto a dados de pesquisa embasada em dados coletados por meio de survey, realizada com pesquisadores brasileiros. As 4.676 respostas obtidas demonstram que, apesar do grande interesse pelo tema, evidenciado pela prevalência de variáveis relacionadas ao compartilhamento e ao uso de dados e aos repositórios institucionais, não há clareza por parte dos sujeitos sobre os principais tópicos relacionados. Conclui-se que, apesar da maioria dos pesquisadores afirmar que compartilha dados de pesquisa, a disponibilização desses dados de forma aberta e irrestrita ainda não é amplamente aceita.Palavras-chave: Dados Abertos de Pesquisa; Compartilhamento de Dados; Reuso de Dados.ABSTRACT This article presents an exploratory analysis of the practices and perceptions regarding open access to research data based on information collected by a survey with Brazilian researchers. The 4,676 responses show that, despite the great interest in the topic, evidenced by the prevalence of variables related to data sharing and use and to institutional repositories, there is no clarity on the part of the subjects on the main related topics. We conclude that, although the majority of the researchers share research data, the availability of this data in an open and unrestricted way is not yet widely accepted.Keywords: Open Research Data; Data Sharing; Data Reuse.

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PsychData – Experiences from 12 Years of Research Data Archiving

Septentrio Conference Series ◽

10.7557/5.3666 ◽

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.

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Making Research Data Accessible

10.31235/osf.io/9kgj4 ◽

2021 ◽

Author(s):

Diana Kapiszewski ◽

Sebastian Karcher

Keyword(s):

Data Sharing ◽

Research Method ◽

Secondary Analysis ◽

Research Data ◽

Data Generation ◽

Shared Data

This chapter argues that the benefits of data sharing will accrue more quickly, and will be more significant and more enduring, if researchers make their data “meaningfully accessible.” Data are meaningfully accessible when they can be interpreted and analyzed by scholars far beyond those who generated them. Making data meaningfully accessible requires that scholars take the appropriate steps to prepare their data for sharing, and avail themselves of the increasingly sophisticated infrastructure for publishing and preserving research data. The better other researchers can understand shared data and the more researchers who can access them, the more those data will be re-used for secondary analysis, producing knowledge. Likewise, the richer an understanding an instructor and her students can gain of the shared data being used to teach and learn a particular research method, the more useful those data are for that pedagogical purpose. And the more a scholar who is evaluating the work of another can learn about the evidence that underpins its claims and conclusions, the better their ability to identify problems and biases in data generation and analysis, and the better informed and thus stronger an endorsement of the work they can offer.

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DataStaR: Using the Semantic Web approach for Data Curation

International Journal of Digital Curation ◽

10.2218/ijdc.v6i2.197 ◽

2011 ◽

Vol 6 (2) ◽

pp. 209-221 ◽

Cited By ~ 6

Author(s):

Huda Khan ◽

Brian Caruso ◽

Jon Corson-Rikert ◽

Dianne Dietrich ◽

Brian Lowe ◽

...

Keyword(s):

Social Sciences ◽

Semantic Web ◽

Data Sharing ◽

Research Data ◽

Data Curation ◽

Data Staging ◽

Domain Specific ◽

Digital Infrastructure

In disciplines as varied as medicine, social sciences, and economics, data and their analyses are essential parts of researchers’ contributions to their respective fields. While sharing research data for review and analysis presents new opportunities for furthering research, capturing these data in digital forms and providing the digital infrastructure for sharing data and metadata pose several challenges. This paper reviews the motivations behind and design of the Data Staging Repository (DataStaR) platform that targets specific portions of the research data curation lifecycle: data and metadata capture and sharing prior to publication, and publication to permanent archival repositories. The goal of DataStaR is to support both the sharing and publishing of data while at the same time enabling metadata creation without imposing additional overheads for researchers and librarians. Furthermore, DataStaR is intended to provide cross-disciplinary support by being able to integrate different domain-specific metadata schemas according to researchers’ needs. DataStaR’s strategy of a usable interface coupled with metadata flexibility allows for a more scaleable solution for data sharing, publication, and metadata reuse.

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Practicing what we preach: developing a data sharing policy for the Journal of the Medical Library Association

Journal of the Medical Library Association JMLA ◽

10.5195/jmla.2018.431 ◽

2018 ◽

Vol 106 (2) ◽

Author(s):

Kevin B. Read ◽

Liz Amos ◽

Lisa M. Federer ◽

Ayaba Logan ◽

T. Scott Plutchak ◽

...

Keyword(s):

Data Sharing ◽

Working Group ◽

Health Sciences ◽

Research Data ◽

Research Results ◽

Medical Library ◽

Information Professionals ◽

Published Research

Providing access to the data underlying research results in published literature allows others to reproduce those results or analyze the data in new ways. Health sciences librarians and information professionals have long been advocates of data sharing. It is time for us to practice what we preach and share the data associated with our published research. This editorial describes the activity of a working group charged with developing a research data sharing policy for the Journal of the Medical Library Association.

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Surveying the landscape of CIHR-funded research data sharing practices: An analysis of the published literature

10.31219/osf.io/h7byr ◽

2021 ◽

Author(s):

Kevin B Read ◽

Heather Ganshorn ◽

Sarah Rutley ◽

David R. Scott

Keyword(s):

Best Practices ◽

Data Sharing ◽

Descriptive Analysis ◽

Research Data ◽

Data Discovery ◽

Pubmed Central ◽

Funded Research ◽

Shared Data ◽

Research Data Management ◽

Is Value

Background:As Canada increases requirements for research data management (RDM) and sharing, there is value in identifying how research data are shared, and what has been done to make them findable and reusable. This study aims to understand Canada’s data sharing landscape by reviewing how Canadian Institutes of Health Research (CIHR) funded data are shared, and comparing researchers’ data sharing practices to RDM and sharing best practices. Methods:We performed a descriptive analysis of CIHR-funded publications from PubMed and PubMed Central that were published between 1946 and Dec 31, 2019 and that indicated the research data underlying the results of the publication were shared. Each publication was analyzed to identify how and where data were shared, who shared data, and what documentation was included to support data reuse.Results:Of 4,144 CIHR-funded publications, 45.2% (n=1,876) included accessible data, 21.9% (n=909) stated data were available by request, 7.3% (n=304) stated data sharing was not applicable/possible, and we found no evidence of data sharing in 37.6% (n=1,558) of publications. Frequent data sharing methods included via a repository (n=1,549, 37.3%), within supplementary files (n=1,048, 25.2%), and by request (n=919, 22.1%). 13.1% (n=554) of publications included documentation that would facilitate data reuse.Interpretation:Our findings reveal that CIHR-funded publications largely lack the metadata, access instructions, and documentation to facilitate data discovery and reuse. Without measures to address these concerns, and enhanced support for researchers seeking to implement RDM and sharing best practices, most CIHR-funded research data will remain hidden, inaccessible, and unusable.

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