Domain-specific data sharing in neuroscience: what do we have to learn from each other?

Abstract

Molecular biology and genomics have made notable strides in the sharing of primary data and resources. In other domains of neuroscience research, however, there has been resistance to adopting formalized strategies for data exchange, archiving, and availability. In this article, we discuss how neuroscience domains might follow the lead of molecular biology on what has been successful and what has failed in active data sharing. This considers not only the technical challenges but also the sociological concerns in making it possible. Though, not a pain-free process, with increased data availability, scientists from multiple fields can enjoy greater opportunity for novel discoveries about the brain in health and disease.

Figure 1. To share or not to share?

Neuroscience data is obtained in many forms - some are obtained using modern in vivo neuroimaging techniques to examine brain function or structure (1a), while some form are obtained from biological tissue samples to derive DNA sequences or gene expression profiles (1b). In the end, these data are represented as digital information, either as text, images, image volumes, time series, etc. Once they are digital, why not share them so that others might benefit from the information they contain? In this figure one might ask is one domain of more shareable than the other? Factors underlying the willingness of investigators to share their data include how difficult or costly the digital information was to obtain, a lack of efficient standards for data exchange, fear of being “scooped”, the overall amount of data to be shared, concerns over patient privacy, as well as the seniority of the investigator. Such factors can be difficult to quantify or overcome. But if they can be systematically surmounted with support from leading scientific organizations and government agencies then neuroscience will be enriched and new discoveries may be closer at hand. 1a) Diffusion tensor imaging (DTI; Philips 3.0 Tesla, 8-channel SENSE head coil, 32-gradient directions) white matter fiber tractography as determined via streamline projections along image voxels with maximal directional preference. Color denotes fiber orientation: Red=Left-to-Right, Green= anterior-posterior, and Blue=Inferior-to-Superior. 1b) A microarray segment from the frontal cortex chosen from the Stanford Microarray Database (SMD; http://genome-www5.stanford.edu): Experiment = 27745, SlideName = shcg212, Experiment = ”Brain(frontal)”, Category = Normal Tissue, Subcategory = Brain, Experimenter = JJUNKERM, ExptDate = 2002-04-16.

Figure 1. To share or not to share?

Neuroscience data is obtained in many forms - some are obtained using modern in vivo neuroimaging techniques to examine brain function or structure (1a), while some form are obtained from biological tissue samples to derive DNA sequences or gene expression profiles (1b). In the end, these data are represented as digital information, either as text, images, image volumes, time series, etc. Once they are digital, why not share them so that others might benefit from the information they contain? In this figure one might ask is one domain of more shareable than the other? Factors underlying the willingness of investigators to share their data include how difficult or costly the digital information was to obtain, a lack of efficient standards for data exchange, fear of being “scooped”, the overall amount of data to be shared, concerns over patient privacy, as well as the seniority of the investigator. Such factors can be difficult to quantify or overcome. But if they can be systematically surmounted with support from leading scientific organizations and government agencies then neuroscience will be enriched and new discoveries may be closer at hand. 1a) Diffusion tensor imaging (DTI; Philips 3.0 Tesla, 8-channel SENSE head coil, 32-gradient directions) white matter fiber tractography as determined via streamline projections along image voxels with maximal directional preference. Color denotes fiber orientation: Red=Left-to-Right, Green= anterior-posterior, and Blue=Inferior-to-Superior. 1b) A microarray segment from the frontal cortex chosen from the Stanford Microarray Database (SMD; http://genome-www5.stanford.edu): Experiment = 27745, SlideName = shcg212, Experiment = ”Brain(frontal)”, Category = Normal Tissue, Subcategory = Brain, Experimenter = JJUNKERM, ExptDate = 2002-04-16.