1. 1 Matthew J. McAuliffe, Ph.D., Chief, Biomedical Imaging Research Services Section (BIRSS) CIT Ramona Hicks, Ph.D., Program Director, Repair and Plasticity NIH/NINDS Douglas Gibson, Ph.D., Deputy Neurotrauma Research Coordinator USAMRMC-CCCRP (RAD2) Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System

2. 2 Why do we bring all this data together? to replicate experiments to ask new questions to simulate to model to share to publish to teach to search to analyze to visualize

3. 3 The FITBIR framework is a collaborative biomedical informatics system to support research at NIH to accelerate scientific discovery and treatment. The mission of BRICS is accomplished by the: 1.Definition of standards to enable cross site meta-analysis and data comparisons (e.g. NINDS CDEs) 2.Deployment of useful tools for community adoption 3.Promotion for the sharing of quality research data throughout the research community 4.Central Repository and Portal to phenotypic, genomic, imaging and pedigree data. FITBIR

4. 4 BRICS Components Clinical Trial / Research Defining electronic case report forms Scheduling and collecting clinical data Exporting, analyzing and reporting on collected data. Study Management and Data Submission Defining and managing study information and access Contributing, uploading, and storing the research data Define federated data stores Querying, Reporting and Exporting Data Include locally collected research data Include research data from defined, federated sites. Defining and Validating Data Creating, managing, and searching data elements and form structures Validating research data against the defined validation rules Global Unique Identifier System Allows researchers to share data specific to study participants Correlate participants across studies without exposing personally identifiable information (PII) User Account Management Creating, approving, and managing user accounts Managing access controls, roles & permissions Single sign on MIPAV Imaging Tool Image submission tool Image analysis tools 3D Image visualization

5. 5 Generic Forms Tool (eCRF) ProFoRM (eCRF+) RESTFUL API GUID Repository Manager Data Access GUID Webstart Client Data Dictionary NINDS CDEs, Unique DE Validation Webstart Tool Upload ToolDownload MgrQuery Tool Meta Data Raw Data Export Package Query Results Data SubmissionData Access FITBIR Arch

6. 6 Generic Forms Tool (eCRF) ProFoRM (eCRF+) RESTFUL API GUID Repository Manager Data Access GUID Webstart Client Data Dictionary NINDS CDEs, Unique DE Validation Webstart Tool Upload ToolDownload MgrQuery Tool Meta Data Raw Data Export Package Query Results Data SubmissionData Access FITBIR Arch Data Analytics (Big Data)

7. 7 Submission Dataflow VALIDATE & SUBMITRESEARCHER USE COLLABORATIONQUALIFIED ACCESS CAPTURE NEUROIMAGING GENOMICS ASSESSMENT DATA

8. 8 Researcher logs into GUID client on their university PC and enters in subject PII GUID client (on university computer) uses personnaly identifiable information to derive a series of one way hashes which securely encrypt PII information One way hashes are sent off to the GUID server for reference and storage. No personally identifiable information is sent to the system GUID server returns a GUID identifier. If the one way hashes match a known subject, an existing GUID will be returned. If this is a new subject, a new GUID will be returned. Once the researcher has a GUID, s/he may submit data associated with this subject. No data may be submitted to the system without a GUID. Researchers are able to access data across studies, without revealing personally identifiable information, while correlating study data across different studies AND uniquely sorting between distinct and redundant datasets Shared Shared Data Repository GUID Once data is in the database, a researcher may query this data. The GUID allows researchers to distinguish between unique subjects and recurrent subjects across all datasets.

9. 9 Validation Tool

10. 10 ProFoRMS Build Form Page

11. 11 Image Analysis Tool http://mipav.cit.nih.gov

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15. 15 Future work 1. Define pipeline APIs for imaging, meta-data, genomics Cloud API to support multiple processing applications 2. Further development of imaging CDEs to support the description of DTI and related images stored in the database