Reuse of existing neuroscience data relies, in part, on our ability to understand the experimental design and study data. Historically, a description of the experiment is provided in textual documents, which are often difficult to search, lack the details necessary for data reuse, and are hampered by differences in terminologies across related fields of neuroscience. Our vision is to build on existing resources to create annotation and discovery tools that are based on a metadata standard expressive enough to provide unambiguous descriptions of the experimental methods and metadata. In this proposal, we develop the Experiment component of the Neuroimaging Data Model (NIDM-E), a metadata format leveraging techniques from the semantic web, capable of precisely describing information about the design and intent of an experiment, experimental subject characteristics, and the acquired data. The deliverables in this proposal will create an information architecture of a Data Commons to achieve Findable, Accessible, Interoperable, and Reusable metadata.
The Aims consist of three interleaved components: (1) Advance the development of the NIDM-E standard through community engagement; (2) Provide user- and developer-friendly software for NIDM-E documents; (3) Foster adoption through comprehensive training materials and outreach via community workshops.
?The Neuroimaging Data Model: FAIR descriptors of Brain Initiative Imaging Experiments? project aims to improve public health by advancing our ability to unambiguously describe data collected in Brain Initiative research and linking data across projects. By using principles and techniques from the Semantic Web, the Neuroimaging Data Model Experiment format will help scientists find, understand, and reuse data collected using public funds in service of improving scientific studies that can result in improved illness treatment and prevention.
