Integrated platform and API for electrophysiological data
| Autor: | Aljoscha Leonhardt, Andrey Sobolev, Christian Kellner, Philipp L. Rautenberg, Christian Garbers, Thomas Wachtler, Adrian Stoewer |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Computer science
Data management Biomedical Engineering Neuroscience (miscellaneous) lcsh:RC321-571 Original Research Article lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Spatial data infrastructure Data element Application programming interface business.industry Web service Neo neuroinformatics Data science collaboration Computer Science Applications Data mapping Metadata Electrophysiology odml data management business Software engineering Data migration Neuroscience Data virtualization |
| Zdroj: | Frontiers in Neuroinformatics, Vol 8 (2014) Frontiers in Neuroinformatics |
| ISSN: | 1662-5196 |
| Popis: | Recent advancements in technology and methodology have led to growing amounts of increasingly complex neuroscience data recorded from various species, modalities, and levels of study. The rapid data growth has made efficient data access and flexible, machine-readable data annotation a crucial requisite for neuroscientists. Clear and consistent annotation and organization of data is not only an important ingredient for reproducibility of results and re-use of data, but also essential for collaborative research and data sharing. In particular, efficient data management and interoperability requires a unified approach that integrates data and metadata and provides a common way of accessing this information.In this paper we describe GNData, a data management platform for neurophysiological data. GNData provides a storage system based on a data representation that is suitable to organize data and metadata from any electrophysiological experiment, with a functionality exposed via a common application programming interface (API). Data representation and API structure are compatible with existing approaches for data and metadata representation in neurophysiology. The API implementation is based on the Representational State Transfer (REST) pattern, which enables data access integration in software applications and facilitates the development of tools that communicate with the service. Client libraries that interact with the API provide direct data access from computing environments like Matlab or Python, enabling integration of data management into the scientist's experimental or analysis routines. |
| Databáze: | OpenAIRE |
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