A Database System for Electrophysiological Data
A. Hameurlain et al. (Eds.): TLDKS IV, LNCS 6990, pp. 1-14, Springer-Verlag Berlin Heidelberg 2011
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Scientific progress depends increasingly on collaborative efforts that involve exchange of data and re-analysis of previously recorded data. A major obstacle to fully exploit the scientific potential of experimental data is the effort it takes to access both data and metadata for application of specific analysis methods, for exchange with collaborators, or for further analysis some time after the initial study was completed. To cope with these challenges and to make data analysis, re-analysis, and data sharing efficient, data together with metadata should be managed and accessed in a unified and reproducible way, so that the researcher can concentrate on the scientific questions rather than on problems of data management. We present a data management system for electrophysiological data based on well established relational database technology and domain-specific data models, together with mechanisms to account for the heterogeneity of electrophysiological data. This approach provides interfaces to analysis tools and programming languages that are commonly used in neurophysiology. It thus will enable researchers to seamlessly integrate data access into their daily laboratory workflow and efficiently perform management and selection of data in a systematic and largely automatized fashion for data sharing and analysis.