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.

Keywords: Database; Informatics; Neuroinformatics; Open science; Open-access; R-fMRI; fMRI.

Figure 1

Overview of the origin of visitors (website hits) to the FCP and INDI repositories.

Figure 2

Number of visitors to the FCP and INDI repositories since their launch. A. Number of visitors (website hits) per week to the FCP and INDI repositories. Peaks in the number of website hits are relatable to specific FCP/INDI releases or events. B. Cumulative number of visitors (website hits) to the FCP and INDI repositories since their launch. While substantial numbers of new visitors continue to accrue, many users return repeatedly to the repository for more data or additional information.