Enterprise Neuroinformatics for Interoperable Data Management and Dissemination

Project Summary Abstract There is a tremendous need for tools that allow NIH sponsored investigators to easily share and disseminate data from brain imaging studiesAccess to large neuroimaging data sets is a critical aspect of learning about how the brain works both in health and diseaseMost typicallylarge data sets are collected by one investigatorused for a specific purposeand then archivedSometimes these data are shared with collaboratorstypically after an extended effortSuch an approach takes a very narrow view of what could be learned from these rich data setsFor examplethere are often multiple questions that could be asked but weren t conceived at the time of the study designThere are also a plethora of advanced analytic techniques and approachesdeveloped by multiple groupswhich can be applied to these data to identify hidden structure or answer new questionsHoweverthere are many barriers to data sharing of multimodal neuroimaging data and the community has tried for years to confront the various barriersIn this direct Phase II SBIR 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 studiesassessmentsand neuroimaging dataInvestigator tools allow management of privacy within prospectiveongoingstudiesThese tools allow investigators to control what is shared with collaboratorsWe believe that robust privacy controls are essential for data sharingAll data is collectedstoredand managed within a scalable infrastructureWe will deliver our neuroinformatics suite to NIH sponsored investigatorsas well as other customers and clientsThe rollout process and implementation includes installationsupporttrainingand data storageThe 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