Neuroinformatics for Prospective Data Management and Sharing

DESCRIPTION (provided by applicant): There is a tremendous need for tools that allow NIH sponsored investigators to easily share and disseminate data from brain imaging studies. Access to large neuroimaging data sets is a critical aspect of learning abouthow the brain works both in health and disease. Most typically, large data sets are collected by one investigator, used for a specific purpose, and then often archived. Sometimes these data are shared with collaborators, typically after an extended effort.Such an approach takes a very narrow view of what could be learned from these rich data sets. For example, there are often multiple questions that could be asked but weren't conceived at the time of the study design. There are also a plethora of advancedanalytic techniques and approaches, developed by multiple groups, which can be applied to these data to identify hidden structure or answer new questions. However, there are many barriers to data sharing of multimodal neuroimaging data and the community has tried for years to confront the various barriers. In this Phase I STTR we are proposing a unique approach which is to take the neuroinformatics tools that we have been developing at the Mind Research Network and create a user friendly neuroinformatics suite which will enable prospective management and sharing of studies, assessments, and neuroimaging data. The ability to handle prospective (ongoing) studies including privacy aspects is, we believe, critical to encouraging sharing as the control of whetherand who to share with will be under the individual investigator's control. Sharing is then quite simple to enable as all the data are collected, stored, and managed within a larger infrastructure. We plan to explore the feasibility of our approach, whichwill be to market the services required to implement and sustain our neuroinformatics tools. This will include installation, support, training, and data storage among other things. The successful completion of this project would represent a major transformation which could propel scientific sharing and knowledge extraction of diverse types of data into a practical and widely used model. 2 PUBLIC HEALTH RELEVANCE PUBLIC HEALTH RELEVANCE: There is a great need for tools to easily share and disseminate data from brain imaging studies. Previous and ongoing attempts are powerful, but do not handle prospective collection of all data and require a significant customization effort to implement at an existing site. We are proposing to develop a user friendly neuroinformatics suite which can handle all aspects of study data collection, management of security, and data sharing. 3