System for EEG/ERP Data and Metadata Storage and Management
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F12%3A43915345" target="_blank" >RIV/49777513:23520/12:43915345 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
System for EEG/ERP Data and Metadata Storage and Management
Original language description
The paper introduces a system for EEG/ERP (electroencephalography, event-related potentials) data and metadata storage and processing. Since researchers have difficulties with a suitable long-term storage and management of electrophysiology data the presented system helps them to increase both efficiency and effectiveness of their work by providing the means for the storage, management, search and sharing of EEG/ERP data. The requirements specification including the system context, system requirements,project scope, basic features, system users, and data formats and metadata structures is presented. The database structure is proposed; upload, download and interchange of EEG/ERP data and metadata using the web interface are described. The system architecture, used technologies and final realization are described. Data and metadata search and user accounts including system security management are presented. Additional tools and structures as converters of data formats and semantic web o
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ME%20949" target="_blank" >ME 949: Analýza negativních vlivů na pozornost řidičů</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
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Volume of the periodical
22
Issue of the periodical within the volume
3
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
14
Pages from-to
277-290
UT code for WoS article
000306821100004
EID of the result in the Scopus database
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