Clinical research studies require data collected through many different processes, including often neuroimaging, physiological, medical records, and clinical interviews and assessments. Imaging record collection and management within and between institutions are increasingly electronically managed, so that the images are available online and easily archived; data sharing techniques, which identify and capture the critical meta-data for neuroimaging analyses, are still in development. Software for managing electronic health records is being developed and is available from several sources. On the other hand, clinical interviews, assays, and case report forms (CRFs) that accompany psychiatric and neurological research and clinical trials, on the other hand, are often recorded in paper format for convenience and flexibility. Several efforts now exist that provide tools for use in electronic data capture and protocol management and representation. However, careful thought must be given to ensuring appropriate, efficient, optimal, and replicable processing of the data as well as patient confidentiality. The needed meta-data for correct analyses and re-analyses of neuroimaging data in combination with behavioral and clinical measures does not yet have standardized representations. In this volume, we ask leaders in the field of the neurosciences to provide articles which detail methods for efficient electronic data capture, interoperability with large-scale databases, meta-data representation for data archiving and re-use, and to discuss their application toward exploring the richness of brain imaging data as well as the literature of published research results.
Clinical research studies require data collected through many different processes, including often neuroimaging, physiological, medical records, and clinical interviews and assessments. Imaging record collection and management within and between institutions are increasingly electronically managed, so that the images are available online and easily archived; data sharing techniques, which identify and capture the critical meta-data for neuroimaging analyses, are still in development. Software for managing electronic health records is being developed and is available from several sources. On the other hand, clinical interviews, assays, and case report forms (CRFs) that accompany psychiatric and neurological research and clinical trials, on the other hand, are often recorded in paper format for convenience and flexibility. Several efforts now exist that provide tools for use in electronic data capture and protocol management and representation. However, careful thought must be given to ensuring appropriate, efficient, optimal, and replicable processing of the data as well as patient confidentiality. The needed meta-data for correct analyses and re-analyses of neuroimaging data in combination with behavioral and clinical measures does not yet have standardized representations. In this volume, we ask leaders in the field of the neurosciences to provide articles which detail methods for efficient electronic data capture, interoperability with large-scale databases, meta-data representation for data archiving and re-use, and to discuss their application toward exploring the richness of brain imaging data as well as the literature of published research results.
