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神经科学数据发现术语:多树语法与研究者衍生语义

Terminology for neuroscience data discovery: multi-tree syntax and investigator-derived semantics.

作者信息

Gardner Daniel, Goldberg David H, Grafstein Bernice, Robert Adrian, Gardner Esther P

机构信息

Laboratory of Neuroinformatics and Department of Physiology, Weill Medical College of Cornell University, 1300 York Avenue, New York, NY, 10065, USA.

出版信息

Neuroinformatics. 2008 Sep;6(3):161-74. doi: 10.1007/s12021-008-9029-7. Epub 2008 Oct 29.

Abstract

The Neuroscience Information Framework (NIF), developed for the NIH Blueprint for Neuroscience Research and available at http://nif.nih.gov and http://neurogateway.org , is built upon a set of coordinated terminology components enabling data and web-resource description and selection. Core NIF terminologies use a straightforward syntax designed for ease of use and for navigation by familiar web interfaces, and readily exportable to aid development of relational-model databases for neuroscience data sharing. Datasets, data analysis tools, web resources, and other entities are characterized by multiple descriptors, each addressing core concepts, including data type, acquisition technique, neuroanatomy, and cell class. Terms for each concept are organized in a tree structure, providing is-a and has-a relations. Broad general terms near each root span the category or concept and spawn more detailed entries for specificity. Related but distinct concepts (e.g., brain area and depth) are specified by separate trees, for easier navigation than would be required by graph representation. Semantics enabling NIF data discovery were selected at one or more workshops by investigators expert in particular systems (vision, olfaction, behavioral neuroscience, neurodevelopment), brain areas (cerebellum, thalamus, hippocampus), preparations (molluscs, fly), diseases (neurodegenerative disease), or techniques (microscopy, computation and modeling, neurogenetics). Workshop-derived integrated term lists are available Open Source at http://brainml.org ; a complete list of participants is at http://brainml.org/workshops.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d396/2663521/a9883589e99b/nihms94458f1.jpg

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