Web Data Storage for Management and Sharing of Neuroscience Data
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1
Ludwig-Maximilians-Universität München, Department Biology II, Germany
In neuroscience, technological advancements and improvements in methodology, achieved during the last decades enable scientists to produce growing amounts of increasingly complex data recorded from many species, modalities, and levels of study. Annotation and organisation of these data has become a challenging task, which is not only important for the interpretability and reproducibility of results and analyses, but also essential for collaboration and data sharing. In order to address these issues, the German INCF Node (G-Node) is developing software solutions consisting of several services and tools for experimental neuroscientists, focusing on online data access and organisation of electrophysiological data.
The core of this project is a web service representing a centralized data storage system that provides functions for upload, search, and management of data and metadata [1]. The principal design goal of this service was to improve the experimental workflow and to unify data access from different locations and platforms. In addition we develop libraries and client programs providing the full functionality while allowing the scientist to use this service either directly through a web page or from his preferred working environment. Currently this includes a toolbox for the popular numeric computing environment Matlab and a library for the programming language Python. The software supports various techniques and standards used in the field for data analysis and management, including NEO[2], Neuroshare[3], and odML[4]. When files are uploaded to the storage service, they are converted to native objects such as signals, spikes, neural events or metadata objects. All those objects can be searched, selected and manipulated separately. Furthermore, the service implements a versioning system for all stored data objects and allows fine-grained sharing of data from whole datasets down to single signals and files.
The service itself exposes its full functionality via a common application programming interface (API). The architecture of the API is based on the Representational State Transfer[5] (REST) pattern, which is a widely used design model for HTTP-based web APIs. As main transfer format the API uses the markup language JSON[6]. This use of common web technologies facilitates the development of other software solutions that interact with the service.
Acknowledgements
Supported by the Federal Ministry of Education and Research (Grant 01GQ0801).
References
[1] G-Node Repository (http://g-node.github.com)
[2] NEO I/O (http://neuralensemble.org/neo)
[3] Neuroshare (https://github.com/G-Node/python-neuroshare)
[4] odML (https://github.com/G-Node/python-odml)
[5] R. T. Fielding (2002) doi:10.1145/514183.514185
[6] RFC 4627 (http://tools.ietf.org/html/rfc4627)
Keywords:
Electrophysiology,
metadata,
Web service,
data management,
MATLAB,
python
Conference:
Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013.
Presentation Type:
Demo
Topic:
Infrastructural and portal services
Citation:
Stoewer
A,
Sobolev
A,
Leonhardt
AP,
Kellner
CJ,
Garbers
C,
Herz
AV and
Wachtler
T
(2013). Web Data Storage for Management and Sharing of Neuroscience Data.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2013.
doi: 10.3389/conf.fninf.2013.09.00074
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Received:
09 Apr 2013;
Published Online:
11 Jul 2013.
*
Correspondence:
Mr. Adrian Stoewer, Ludwig-Maximilians-Universität München, Department Biology II, Munich, Germany, adrian@stoewer.me
Mr. Andrey Sobolev, Ludwig-Maximilians-Universität München, Department Biology II, Munich, Germany, sobolev.andrey@gmail.com