Integrated platform and API for electrophysiological data
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 requis...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2014-04-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00032/full |
| _version_ | 1817994780647358464 |
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| author | Andrey eSobolev Adrian eStoewer Aljoscha Pascal Leonhardt Philipp L. Rautenberg Christian Johannes Kellner Christian eGarbers Thomas eWachtler |
| author_facet | Andrey eSobolev Adrian eStoewer Aljoscha Pascal Leonhardt Philipp L. Rautenberg Christian Johannes Kellner Christian eGarbers Thomas eWachtler |
| author_sort | Andrey eSobolev |
| collection | DOAJ |
| description | 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.<br/><br/>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. |
| first_indexed | 2024-04-14T01:56:44Z |
| format | Article |
| id | doaj.art-fffa4b19808f473cadf14e1e3fe3bcbb |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-04-14T01:56:44Z |
| publishDate | 2014-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-fffa4b19808f473cadf14e1e3fe3bcbb2022-12-22T02:19:00ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962014-04-01810.3389/fninf.2014.0003279777Integrated platform and API for electrophysiological dataAndrey eSobolev0Adrian eStoewer1Aljoscha Pascal Leonhardt2Philipp L. Rautenberg3Christian Johannes Kellner4Christian eGarbers5Thomas eWachtler6Ludwig-Maximilians-Universitaet MuenchenLudwig-Maximilians-Universitaet MuenchenMax Planck Institute of NeurobiologyMax Planck Digital LibraryLudwig-Maximilians-Universitaet MuenchenLudwig-Maximilians-Universitaet MuenchenLudwig-Maximilians-Universitaet MuenchenRecent 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.<br/><br/>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.http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00032/fullElectrophysiologyneuroinformaticscollaborationdata managementWeb serviceNeo |
| spellingShingle | Andrey eSobolev Adrian eStoewer Aljoscha Pascal Leonhardt Philipp L. Rautenberg Christian Johannes Kellner Christian eGarbers Thomas eWachtler Integrated platform and API for electrophysiological data Frontiers in Neuroinformatics Electrophysiology neuroinformatics collaboration data management Web service Neo |
| title | Integrated platform and API for electrophysiological data |
| title_full | Integrated platform and API for electrophysiological data |
| title_fullStr | Integrated platform and API for electrophysiological data |
| title_full_unstemmed | Integrated platform and API for electrophysiological data |
| title_short | Integrated platform and API for electrophysiological data |
| title_sort | integrated platform and api for electrophysiological data |
| topic | Electrophysiology neuroinformatics collaboration data management Web service Neo |
| url | http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00032/full |
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