Data sharing in neuroimaging research

Abstract

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging.

Figshare: a universal repository for academic resource sharing?

“…Moreover, some studies need data on a scale that requires sharing. For example, identifying diseases from brain scans requires access to large numbers of healthy and diseased examples obtained from organised data sharing (Poline et al 2012) using common standards (e.g., Demir et al, 2010). More generally, sharing any kind of academic resource can aid efficiency by ensuring that scholars do not have to needlessly repeat prior work.…”

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

“…Thus, openness and transparency relate directly to reproducibility of all three kinds. Reflecting this sensibility, a diverse array of behavioral scientists have begun arguing that that achieving the scientific ideals of a free and open exchange of information requires the widespread adoption of open and transparent communication practices [15][16][27][28][29][30] . How well has the field of cognitive neuroscience measured up to these ideals?…”

PLM as a strategy for the management of heterogeneous information in bio-medical imaging field

“…In particular, no project takes into account stage 1. Few data management systems (XNAT and IDA), integrate workflows between stages 2 and 3, based on the stages of electronic data capture (Poline et al, 2012). All other database solutions store the data rather than manage the concepts.…”