scholarly journals Open Science and Data Sharing in Clinical Research

2012 ◽  
Vol 5 (2) ◽  
pp. 141-142 ◽  
Author(s):  
Harlan M. Krumholz
Keyword(s):  
Clinical Research ◽  
Data Sharing ◽  
Open Science

Introduction to the special section on Increasing Replicability, Transparency, and Openness in Clinical Psychology

2019 ◽  
Author(s):  
Jennifer L Tackett ◽  
Josh Miller
Keyword(s):  
Empirical Evidence ◽  
Data Sharing ◽  
Clinical Psychology ◽  
Special Section ◽  
Psychological Research ◽  
Open Science ◽  
Clinical Psychologists ◽  
Existing Problems

As psychological research comes under increasing fire for the crisis of replicability, attention has turned to methods and practices that facilitate (or hinder) a more replicable and veridical body of empirical evidence. These trends have focused on “open science” initiatives, including an emphasis on replication, transparency, and data sharing. Despite this broader movement in psychology, clinical psychologists and psychiatrists have been largely absent from the broader conversation on documenting the extent of existing problems as well as generating solutions to problematic methods and practices in our area (Tackett et al., 2017). The goal of the current special section was to bring together psychopathology researchers to explore these and related areas as they pertain to the types of research conducted in clinical psychology and allied disciplines.

scholarly journals Tutkimusaineiston avoin jakaminen – tutkimusorganisaatioiden jäsenten käsityksiä, kokemuksia ja mielipiteitä

2018 ◽  
Vol 37 (4) ◽  
Author(s):  
Heidi Enwald
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Online Survey ◽  
Open Science ◽  
Research Data ◽  
Research Field ◽  
Open Research ◽  
Research Organizations ◽  
Data Collection Instrument ◽  
In The Beginning

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.

scholarly journals Announcing the Journal of the Medical Library Association’s data sharing policy

2019 ◽  
Vol 107 (4) ◽  
Author(s):  
Katherine G. Akers ◽  
Kevin B. Read ◽  
Liz Amos ◽  
Lisa M. Federer ◽  
Ayaba Logan ◽  
...  
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Open Science ◽  
Data Reuse ◽  
Medical Library ◽  
Firm Data ◽  
Published Research

As librarians are generally advocates of open access and data sharing, it is a bit surprising that peer-reviewed journals in the field of librarianship have been slow to adopt data sharing policies. Starting October 1, 2019, the Journal of the Medical Library Association (JMLA) is taking a step forward and implementing a firm data sharing policy to increase the rigor and reproducibility of published research, enable data reuse, and promote open science. This editorial explains the data sharing policy, describes how compliance with the policy will fit into the journal’s workflow, and provides further guidance for preparing for data sharing.

scholarly journals Development of Common Data Elements for Use in Chiari Malformation Type I Clinical Research: An NIH/NINDS Project

Neurosurgery ◽  
2019 ◽  
Vol 85 (6) ◽  
pp. 854-860 ◽  
Author(s):  
Mark G Luciano ◽  
Ulrich Batzdorf ◽  
Roger W Kula ◽  
Brandon G Rocque ◽  
Cormac O Maher ◽  
...  
Keyword(s):  
Clinical Research ◽  
Data Sharing ◽  
Chiari I Malformation ◽  
Type I ◽  
Design Data ◽  
Chiari Malformation Type I ◽  
Common Data Elements ◽  
Clinical Research Trial ◽  
Symptom Patterns ◽  
Data Elements

ABSTRACT The management of Chiari I malformation (CMI) is controversial because treatment methods vary and treatment decisions rest on incomplete understanding of its complex symptom patterns, etiologies, and natural history. Validity of studies that attempt to compare treatment of CMI has been limited because of variable terminology and methods used to describe study subjects. The goal of this project was to standardize terminology and methods by developing a comprehensive set of Common Data Elements (CDEs), data definitions, case report forms (CRFs), and outcome measure recommendations for use in CMI clinical research, as part of the CDE project at the National Institute of Neurological Disorders and Stroke (NINDS) of the US National Institutes of Health. A working group, comprising over 30 experts, developed and identified CDEs, template CRFs, data dictionaries, and guidelines to aid investigators starting and conducting CMI clinical research studies. The recommendations were compiled, internally reviewed, and posted online for external public comment. In October 2016, version 1.0 of the CMI CDE recommendations became available on the NINDS CDE website. The recommendations span these domains: Core Demographics/Epidemiology; Presentation/Symptoms; Co-Morbidities/Genetics; Imaging; Treatment; and Outcome. Widespread use of CDEs could facilitate CMI clinical research trial design, data sharing, retrospective analyses, and consistent data sharing between CMI investigators around the world. Updating of CDEs will be necessary to keep them relevant and applicable to evolving research goals for understanding CMI and its treatment.

scholarly journals Open-access policy and data-sharing practice in UK academia

2019 ◽  
Vol 46 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Yimei Zhu
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Secondary Data ◽  
Open Science ◽  
Research Data ◽  
Academic Disciplines ◽  
Free Access ◽  
Online Publishing ◽  
Institutional Repositories ◽  
Access To Data

Data sharing can be defined as the release of research data that can be used by others. With the recent open-science movement, there has been a call for free access to data, tools and methods in academia. In recent years, subject-based and institutional repositories and data centres have emerged along with online publishing. Many scientific records, including published articles and data, have been made available via new platforms. In the United Kingdom, most major research funders had a data policy and require researchers to include a ‘data-sharing plan’ when applying for funding. However, there are a number of barriers to the full-scale adoption of data sharing. Those barriers are not only technical, but also psychological and social. A survey was conducted with over 1800 UK-based academics to explore the extent of support of data sharing and the characteristics and factors associated with data-sharing practice. It found that while most academics recognised the importance of sharing research data, most of them had never shared or reused research data. There were differences in the extent of data sharing between different gender, academic disciplines, age and seniority. It also found that the awareness of Research Council UK’s (RCUK) Open-Access (OA) policy, experience of Gold and Green OA publishing, attitudes towards the importance of data sharing and experience of using secondary data were associated with the practice of data sharing. A small group of researchers used social media such as Twitter, blogs and Facebook to promote the research data they had shared online. Our findings contribute to the knowledge and understanding of open science and offer recommendations to academic institutions, journals and funding agencies.

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