Mobile metadata: bringing Neuroinformatics tools to the bench
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1
Ludwig-Maximilians-Universität München, Department Biology II, Germany
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2
University of Antwerp, Belgium
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3
Eberhard Karls University Tübingen, Germany
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4
University of West Bohemia, Dept. of Computer Science and Engineering, New Technologies for Information Society, Czechia
The complexity of experimental paradigms in neuroscience results in corresponding complexity of recorded data and associated metadata. This poses a challenge to data annotation and metadata capture in the lab. Often, crucial experimental information is hand-written in lab notebooks or entered manually in various text files or spreadsheets. This process is both time-consuming and error prone, and the information is not easily accessible for data processing. Moreover, the diversity of formats hampers the development of common software solutions to further manage and re-use the metadata. To address this problem, odML, a flexible data model for metadata, was proposed (Grewe et al., 2011) that supports efficient organization of metadata. While such a machine-readable format enables to automatize metadata capture to large extent, in every experiment there is information that needs to be recorded manually. For these cases, we here present a standalone mobile app that enables scientists to acquire seamlessly and efficiently their metadata in a structured format at the bench, independent of lab environment, or even outside in the field. The tool was inspired by, and is similar in concept to, the pioneering solution for clinical assessment, CARAT (Turner et al., 2011), but uses odML as a standard data model, which enables acquisition of metadata from various scientific domains, and offers features for designing templates and managing metadata structures. The strength of this approach is to hide the complexity of odML structures from the user while providing the necessary control over the data entry process. The mobile app runs on the most frequently used platforms, iOS and Android. An intuitive and simple user interface allows researchers to create metadata forms that can be either directly filled in with acquired values, or saved as templates for re-use. When designing templates the user can, for example, define whether a certain field is required, or in which order the fields are presented and should be filled. Thus, one can design fillable forms that are adapted to the specific experiment and can be re-used in later experiments. Experimental records are stored as odML files and therefore can be integrated with other experimental metadata. This mobile application thus provides an important element in a toolchain for metadata management that facilitates the recording of metadata in machine-readable form.
Acknowledgements
Supported by the German INCF Node (BMBF grant 01GQ1302) and the European Regional Development Fund (ERDF), Project "NTIS - New Technologies for Information Society", European Centre of Excellence, CZ.1.05/1.1.00/02.0090.
References
Grewe, J., Wachtler, T., & Benda, J. (2011). A Bottom-up Approach to Data Annotation in Neurophysiology. Frontiers in neuroinformatics, 5, 16.
Turner JA, Lane SR, Bockholt HJ and Calhoun VD (2011) The clinical assessment and remote administration tablet. Front. Neuroinform. 5:31.
Keywords:
experimental metadata,
Mobile application,
odml,
Electrophysiology,
user interface
Conference:
Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014.
Presentation Type:
Demo, to be considered for oral presentation
Topic:
General neuroinformatics
Citation:
Le Franc
Y,
Gonzalez
D,
Mylyanyk
I,
Grewe
J,
Jezek
P,
Mouček
R and
Wachtler
T
(2014). Mobile metadata: bringing Neuroinformatics tools to the bench.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2014.
doi: 10.3389/conf.fninf.2014.18.00053
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Received:
26 Apr 2014;
Published Online:
04 Jun 2014.
*
Correspondence:
Dr. Yann Le Franc, Ludwig-Maximilians-Universität München, Department Biology II, Planegg-Martinsried, Germany, Germany, ylefranc@gmail.com