scholarly journals Characteristics of available studies and dissemination of research using major clinical data sharing platforms

2021 ◽  
pp. 174077452110385
Author(s):  
Enrique Vazquez ◽  
Henri Gouraud ◽  
Florian Naudet ◽  
Cary P Gross ◽  
Harlan M Krumholz ◽  
...  
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Clinical Data ◽  
Open Data ◽  
Data Access ◽  
Data Repository ◽  
Biological Specimen ◽  
Research Findings ◽  
Access Project ◽  
Project Data

Background/Aims: Over the past decade, numerous data sharing platforms have been launched, providing access to de-identified individual patient-level data and supporting documentation. We evaluated the characteristics of prominent clinical data sharing platforms, including types of studies listed as available for request, data requests received, and rates of dissemination of research findings from data requests. Methods: We reviewed publicly available information listed on the websites of six prominent clinical data sharing platforms: Biological Specimen and Data Repository Information Coordinating Center, ClinicalStudyDataRequest.com , Project Data Sphere, Supporting Open Access to Researchers–Bristol Myers Squibb, Vivli, and the Yale Open Data Access Project. We recorded key platform characteristics, including listed studies and available supporting documentation, information on the number and status of data requests, and rates of dissemination of research findings from data requests (i.e. publications in a peer-reviewed journals, preprints, conference abstracts, or results reported on the platform’s website). Results: The number of clinical studies listed as available for request varied among five data sharing platforms: Biological Specimen and Data Repository Information Coordinating Center (n = 219), ClinicalStudyDataRequest.com (n = 2,897), Project Data Sphere (n = 154), Vivli (n = 5426), and the Yale Open Data Access Project (n = 395); Supporting Open Access to Researchers did not provide a list of Bristol Myers Squibb studies available for request. Individual patient-level data were nearly always reported as being available for request, as opposed to only Clinical Study Reports (Biological Specimen and Data Repository Information Coordinating Center = 211/219 (96.3%); ClinicalStudyDataRequest.com  = 2884/2897 (99.6%); Project Data Sphere = 154/154 (100.0%); and the Yale Open Data Access Project = 355/395 (89.9%)); Vivli did not provide downloadable study metadata. Of 1201 data requests listed on ClinicalStudyDataRequest.com , Supporting Open Access to Researchers–Bristol Myers Squibb, Vivli, and the Yale Open Data Access Project platforms, 586 requests (48.8%) were approved (i.e. data access granted). The majority were for secondary analyses and/or developing/validating methods ( ClinicalStudyDataRequest.com  = 262/313 (83.7%); Supporting Open Access to Researchers–Bristol Myers Squibb = 22/30 (73.3%); Vivli = 63/84 (75.0%); the Yale Open Data Access Project = 111/159 (69.8%)); four were for re-analyses or corroborations of previous research findings ( ClinicalStudyDataRequest.com  = 3/313 (1.0%) and the Yale Open Data Access Project = 1/159 (0.6%)). Ninety-five (16.1%) approved data requests had results disseminated via peer-reviewed publications ( ClinicalStudyDataRequest.com  = 61/313 (19.5%); Supporting Open Access to Researchers–Bristol Myers Squibb = 3/30 (10.0%); Vivli = 4/84 (4.8%); the Yale Open Data Access Project = 27/159 (17.0%)). Forty-two (6.8%) additional requests reported results through preprints, conference abstracts, or on the platform’s website ( ClinicalStudyDataRequest.com  = 12/313 (3.8%); Supporting Open Access to Researchers–Bristol Myers Squibb = 3/30 (10.0%); Vivli = 2/84 (2.4%); Yale Open Data Access Project = 25/159 (15.7%)). Conclusion: Across six prominent clinical data sharing platforms, information on studies and request metrics varied in availability and format. Most data requests focused on secondary analyses and approximately one-quarter of all approved requests publicly disseminated their results. To further promote the use of shared clinical data, platforms should increase transparency, consistently clarify the availability of the listed studies and supporting documentation, and ensure that research findings from data requests are disseminated.

scholarly journals Building an Open Data Repository for a Specialized Research Community: Process, Challenges and Lessons

2012 ◽  
Vol 7 (1) ◽  
pp. 151-162 ◽  
Author(s):  
Limor Peer ◽  
Ann Green
Keyword(s):  
Open Access ◽  
Open Data ◽  
Data Repository ◽  
Yale University ◽  
Digital Repository ◽  
Statistical Software ◽  
Digital Commons ◽  
Digital Collection ◽  
Redundant Storage ◽  
Research Findings

In 2009, the Institution for Social and Policy Studies (ISPS) at Yale University began building an open access digital collection of social science experimental data, metadata, and associated files produced by ISPS researchers. The digital repository was created to support the replication of research findings and to enable further data analysis and instruction. Content is submitted to a rigorous process of quality assessment and normalization, including transformation of statistical code into R, an open source statistical software. Other requirements included: (a) that the repository be integrated with the current database of publications and projects publicly available on the ISPS website; (b) that it offered open access to datasets, documentation, and statistical software program files; (c) that it utilized persistent linking services and redundant storage provided within the Yale Digital Commons infrastructure; and (d) that it operated in accordance with the prevailing standards of the digital preservation community. In partnership with Yale’s Office of Digital Assets and Infrastructure (ODAI), the ISPS Data Archive was launched in the fall of 2010. We describe the process of creating the repository, discuss prospects for similar projects in the future, and explain how this specialized repository fits into the larger digital landscape at Yale.

The Yale Open Data Access (YODA) Project — A Mechanism for Data Sharing

2016 ◽  
Vol 375 (5) ◽  
pp. 403-405 ◽  
Author(s):  
Harlan M. Krumholz ◽  
Joanne Waldstreicher
Keyword(s):  
Data Sharing ◽  
Open Data ◽  
Data Access

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 Born-Open Data for E-Prime

2020 ◽  
Author(s):  
Denis Cousineau
Keyword(s):  
Open Access ◽  
Open Data ◽  
Open Science ◽  
Research Community ◽  
Data Repository ◽  
Data Frame ◽  
Science Practices ◽  
Data Practices ◽  
Data Files ◽  
Access Data

Born-Open Data experiments are encouraged for better open science practices. To be adopted, Born-Open data practices must be easy to implement. Herein, I introduce a package for E-Prime such that the data files are automatically saved on a GitHub repository. The BornOpenData package for E-Prime works seamlessly and performs the upload as soon as the experiment is finished so that there is no additional steps to perform beyond placing a package call within E-Prime. Because E-Prime files are not standard tab-separated files, I also provide an R function that retrieves the data directly from GitHub into a data frame ready to be analyzed. At this time, there are no standards as to what should constitute an adequate open-access data repository so I propose a few suggestions that any future Born-Open data system could follow for easier use by the research community.

scholarly journals POS0636 INFLUENCE OF DEMOGRAPHIC AND DISEASE RELATED FACTORS ON EFFICACY OF INFLIXIMAB OR GOLIMUMAB IN RHEUMATOID ARTHRITIS. A META-ANALYSIS ON RANDOMIZED PLACEBO- CONTROLLED TRIALS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 556.1-556
Author(s):  
M. A. Sparfel ◽  
S. Derolez ◽  
J. Law-Wan ◽  
N. Azzopardi ◽  
P. Goupille ◽  
...  
Keyword(s):  
Physical Activity ◽  
Disease Activity ◽  
Clinical Response ◽  
Open Data ◽  
Data Access ◽  
Yale University ◽  
Research Support ◽  
Related Factors ◽  
Access Project ◽  
The Impact

Background:TNF inhibitors have changed the course of rheumatoid arthritis (RA). Yet, detailed analysis on factors influencing clinical response to TNF inhibitors in RA is lacking.Objectives:Herein we aimed at studying the impact of demographics and disease-related factors on therapeutic response to golimumab and infliximab in RA.Methods:Randomized clinical trials (RCTs) that evaluated golimumab and infliximab versus placebo or conventional therapy were sought. We selected the following factors: age, sex, ethnicity, body mass index (BMI), smoking status, physical activity, disease duration, disease activity at baseline, presence of auto-antibodies. We studied the impact of these factors on clinical response using firstly aggregate data in a Mantel-Haenszel random effects model, and secondly individual data in a multivariate regression model.Results:Individual data from 8 RCTs, 2 on infliximab (n=1477) and 6 on golimumab (total =3041) were obtained. In the aggregate model analysis, none of the selected factors had a significant impact on clinical response. In the multivariate analysis, male sex and physical activity were significantly associated with a lower DAS28-CRP after 6 months of treatment (regression coefficients -0.264 (p<0.001) and -0.193 (p=0.004) respectively), while a high initial DAS28-CRP was significantly associated with a higher DAS28-CRP (regression coefficient 0.579 (p<0.001)). The baseline disease activity was the only significant interaction factor with the effect of the treatment.Conclusion:Male gender and practicing physical activity are associated with lower disease activity 6 months after golimumab or infliximab initiation. High baseline disease activity significantly influences negatively the effect of the treatment on disease activity score.Acknowledgements:This study, carried out under YODA Project 2018-2931, used data obtained from the Yale University Open Data Access Project, which has an agreement with JANSSEN RESEARCH & DEVELOPMENT, L.L.C. The interpretation and reporting of research using this data are solely the responsibility of the authors and does not necessarily represent the official views of the Yale University Open Data Access Project or JANSSEN RESEARCH & DEVELOPMENT, L.L.C.Disclosure of Interests:Marc-Antoine SPARFEL: None declared, Sophie Derolez: None declared, Johan Law-Wan: None declared, Nicolas Azzopardi: None declared, Philippe Goupille Speakers bureau: Abbvie, Biogaran, BMS, Hospira, Janssen, MSD, Pfizer, Sanofi-Genzyme, UCB, Consultant of: Abbvie, Biogaran, BMS, Hospira, Janssen, MSD, Pfizer, Sanofi-Genzyme, UCB, Grant/research support from: Clinical trials sponsored by Abbvie, Roche, BMS, Boehringer, Lilly, Novartis, Pfizer, UCB, Janssen and MSD. Invitation to an international congresses by MSD, Roche, BMS and Abbvie, Denis Mulleman Speakers bureau: Pfizer and Novartis, Consultant of: Pfizer and Novartis, Grant/research support from: Invitation to an international congress by Janssen-Cilag, Theodora Bejan-Angoulvant: None declared

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.

scholarly journals A Historic Moment for Open Science: The Yale University Open Data Access Project and Medtronic

2013 ◽  
Vol 158 (12) ◽  
pp. 910 ◽  
Author(s):  
Harlan M. Krumholz ◽  
Joseph S. Ross ◽  
Cary P. Gross ◽  
Ezekiel J. Emanuel ◽  
Beth Hodshon ◽  
...  
Keyword(s):  
Open Data ◽  
Data Access ◽  
Open Science ◽  
Yale University ◽  
Access Project

scholarly journals The importance of adherence to international standards for depositing open data in public repositories

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Diego A. Forero ◽  
Walter H. Curioso ◽  
George P. Patrinos
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Meta Analysis ◽  
Open Data ◽  
Open Science ◽  
International Standards ◽  
Raw Data ◽  
The World ◽  
Public Repositories ◽  
Evaluation Of Evidence

AbstractThere has been an important global interest in Open Science, which include open data and methods, in addition to open access publications. It has been proposed that public availability of raw data increases the value and the possibility of confirmation of scientific findings, in addition to the potential of reducing research waste. Availability of raw data in open repositories facilitates the adequate development of meta-analysis and the cumulative evaluation of evidence for specific topics. In this commentary, we discuss key elements about data sharing in open repositories and we invite researchers around the world to deposit their data in them.

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