Dataset Information

Making data sharing work: the FCP/INDI experience.

ABSTRACT: Over a decade ago, the fMRI Data Center (fMRIDC) pioneered open-access data sharing in the task-based functional neuroimaging community. Well ahead of its time, the fMRIDC effort encountered logistical, sociocultural and funding barriers that impeded the field-wise instantiation of open-access data sharing. In 2009, ambitions for open-access data sharing were revived in the resting state functional MRI community in the form of two grassroots initiatives: the 1000 Functional Connectomes Project (FCP) and its successor, the International Neuroimaging Datasharing Initiative (INDI). Beyond providing open access to thousands of clinical and non-clinical imaging datasets, the FCP and INDI have demonstrated the feasibility of large-scale data aggregation for hypothesis generation and testing. Yet, the success of the FCP and INDI should not be confused with widespread embracement of open-access data sharing. Reminiscent of the challenges faced by fMRIDC, key controversies persist and include participant privacy, the role of informatics, and the logistical and cultural challenges of establishing an open science ethos. We discuss the FCP and INDI in the context of these challenges, highlighting the promise of current initiatives and suggesting solutions for possible pitfalls.

SUBMITTER: Mennes M

PROVIDER: S-EPMC3959872 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Making data sharing work: the FCP/INDI experience.

Mennes Maarten M Biswal Bharat B BB Castellanos F Xavier FX Milham Michael P MP

NeuroImage 20121030

Over a decade ago, the fMRI Data Center (fMRIDC) pioneered open-access data sharing in the task-based functional neuroimaging community. Well ahead of its time, the fMRIDC effort encountered logistical, sociocultural and funding barriers that impeded the field-wise instantiation of open-access data sharing. In 2009, ambitions for open-access data sharing were revived in the resting state functional MRI community in the form of two grassroots initiatives: the 1000 Functional Connectomes Project ( ...[more]

PMID: 23123682

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Project description:Introduction:Innovative data platforms (e.g. biobanks, repositories) continually emerge to facilitate data sharing. Extant and emerging data platforms must navigate myriad tensions for successful data sharing and re-use. Two Alberta data platforms navigated such processes and factors regarding administrative, research and nonprofit data: the Child & Youth Data Laboratory (CYDL) and Secondary Analysis to Generate Evidence (SAGE). Objectives:To clarify the social and policy factors that influenced CYDL and SAGE establishment and implementation, and the relationships, if any, between these factors and data type. Methods:This paper involves a qualitative secondary analysis of two developmental evaluations on CYDL and SAGE establishment. Six-years post-implementation, the CYDL evaluation entailed document review; website user analysis; interviews (n=30); online stakeholder survey (n=260); and an environmental scan. One-year post implementation, the SAGE evaluation included 15 interviews and document review. We used thematic analysis and comparisons with the literature to identify key factors. Results:Three (not mutually exclusive) categories of social and policy factors influenced the navigation towards CYDL and SAGE realization: trusting relationships; sustainability amidst readiness; and privacy within social context. For these platforms to be able to manage, link or share data, trust had to be fostered and maintained across multiple, dynamic and intersecting relationships between primary data producers, data subjects, secondary users and institutions. Platform sustainability required capacity building and innovation. Privacy and information sharing evolved culturally and correspondingly for these data platforms, which required constant flexibility and awareness. Conclusions:This analysis calls for more empirical research on the value of data re-use or the detriment in not re-using data. While the culture of information sharing is progressing towards greater openness and capacity for data sharing and re-use, successful data platforms must advocate, facilitate and mobilize analysis and innovation using data re-use while being cognizant of social and policy influences.

Project description:ObjectivesMeta-analysis based on individual patient data (IPD) from randomised trials is superior to using published summary data since it facilitates subgroup and multiple variable analyses. Guidelines and funders expect that researchers share IPD for bona fide analyses, but in practice, this is done variably. Here, we report the experience of obtaining IPD for two collaborative analysis studies.SettingTwo linked studies required IPD from published randomised trials. The leading researchers for eligible trials were approached and asked to share IPD including trial characteristics, patient demographics, baseline clinical data and outcome measures.ParticipantsParticipants in eligible randomised controlled trials included patients with or at risk of cognitive decline/vascular events.Primary and secondary outcome measuresNumbers (%) of trials where the leading researcher responded favourably/negatively or did not respond. If negative, reasons behind the response were collected. If positive, methods used to share IPD were recorded.ResultsAcross the two studies, 391 completed trials were identified. Email addresses for researchers were found for 313 (80%) of the trials. One hundred and forty-eight (47%) researchers did not respond despite being sent multiple emails. Following contact, positive initial responses were received from 92 researchers, resulting in IPD being shared for 78 trials. Eighty-seven (28%) researchers declined to share data; justifications were recorded. The median time from first request to accessing data in one study was 241 (IQR 383.3) days. IPD sources included: direct from researcher, via academic trial funders repository and a website requiring remote analysis of commercial data. Where data were shared, a variety of methods were used to transfer data.ConclusionSharing of IPD from trials is desirable and a requirement of many funding bodies. However, accessing IPD faces multiple challenges including refusals to share, delays in access to data and having to perform analyses on a remote website.Trial registrationNot applicable.

Dataset Information

Making data sharing work: the FCP/INDI experience.

Publications

Making data sharing work: the FCP/INDI experience.

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