Abstract
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.
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Amari, S.-I., Beltrame, F., Bjaalie, J.G., Dalkara, T., De Schutter, E., Egan, G.F., Goddard, N.H., Gonzalez, C., Grillner, S., Herz, A., Hoffmann, K.-P., Jaaskelainen, I., Koslow, S.H., Lee, S.-Y., Matthiessen, L., Miller, P.L., Da Silva, F.M., Novak, M., Ravindranath, V., Ritz, R., Ruotsalainen, U., Sebestra, V., Subramaniam, S., Tang, Y., Toga, A.W., Usui, S., Van Pelt, J., Verschure, P., Willshaw, D., Wrobel, A.: Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience. Journal of Integrative Neuroscience 1(2), 117–128 (2002)
Cannon, R.C., Gewaltig, M.-O., Gleeson, P., Bhalla, U.S., Cornelis, H., Hines, M.L., Howell, F.W., Muller, E., Stiles, J.R., Wils, S., De Schutter, E.: Interoperability of Neuroscience Modeling Software: Current Status and Future Directions. Neuroinformatics 5(2), 127–138 (2007)
Codd, E.F.: A relational model of data for large shared data banks. 1970. M.D. Computing: Computers in Medical Practice 15(3), 162–166 (1970)
Garcia, S., Fourcaud-Trocmé, N.: OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework. Frontiers in neuroinformatics 3(May) 14 (2009)
Gardner, D., Knuth, K.H., Abato, M., Erde, S.M., White, T., DeBellis, R., Gardner, E.P.: Common data model for neuroscience data and data model exchange. J. Am. Med. Inform. Assoc. 8(1), 17–33 (2001)
Gelbart, W.M., Crosby, M., Matthews, B., Rindone, W.P., Chillemi, J., Russo Twombly, S., Emmert, D., Ashburner, M., Drysdale, R.A., Whitfield, E., Millburn, G.H., de Grey, A., Kaufman, T., Matthews, K., Gilbert, D., Strelets, V., Tolstoshev, C.: Flybase: a drosophila database. the flybase consortium. Nucleic Acids Res. 25(1), 63–66 (1997)
Gibson, F., Austin, J., Ingram, C., Fletcher, M., Jackson, T., Jessop, M., Knowles, A., Liang, B., Lord, G., Pitsilis, P., Periorellis, P., Simonotto, J., Watson, P., Smith, L.: The carmen virtual laboratory: Web-based paradigms for collaboration in neurophysiology. In: 6th International Meeting on Substrate-Integrated Microelectrodes 2008 (2008)
Grewe, J., Wachtler, T., Benda, J.: odML format and terminologies for automated handling of (meta)data. In: Front. Neurosci. Conference Abstract: Neuroinformatics 2010 (2010)
Gupta, A., Bug, W., Marenco, L., Qian, X., Condit, C., Rangarajan, A., Müller, H.M., Miller, P.L., Sanders, B., Grethe, J.S., Astakhov, V., Shepherd, G., Sternberg, P.W., Martone, M.E.: Federated access to heterogeneous information resources in the neuroscience information framework (NIF). Neuroinformatics 6(3), 205–217 (2008)
Herz, A.V.M., Meier, R., Nawrot, M.P., Schiegel, W., Zito, T.: G-Node: an integrated tool-sharing platform to support cellular and systems neurophysiology in the age of global neuroinformatics. Neural Netw. 21(8), 1070–1075 (2008)
Hines, M.L., Davison, A.P., Muller, E.: NEURON and Python. Frontiers in neuroinformatics 3(January), 1 (2009)
Ljungquist, B., Petersson, P., Schouenborg, J., Johansson, A.J., Garwicz, M.: A novel framework for storage, analysis and integration through mediation of large-scale electrophysiological data. In: 5th International IEEE/EMBS Conference on Neural Engineering (2011)
Paradis, E., Claude, J., Strimmer, K.: APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics 20(2), 289–290 (2004)
Stoesser, G., Sterk, P., Tuli, M.A., Stoehr, P.J., Cameron, G.N.: The embl nucleotide sequence database. Nucleic Acids Res. 25(1), 7–14 (1997)
Teeters, J.L., Harris, K.D., Jarrod Millman, K., Olshausen, B.A., Sommer, F.T.: Data sharing for computational neuroscience. Neuroinformatics 6(1), 47–55 (2008)
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Rautenberg, P.L., Sobolev, A., Herz, A.V.M., Wachtler, T. (2011). A Database System for Electrophysiological Data. In: Hameurlain, A., Küng, J., Wagner, R., Böhm, C., Eder, J., Plant, C. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems IV. Lecture Notes in Computer Science, vol 6990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23740-9_1
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DOI: https://doi.org/10.1007/978-3-642-23740-9_1
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