Journal Article

FZJ-2019-04875

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png odMLtables: A User-Friendly Approach for Managing Metadata of Neurophysiological Experiments

Sprenger, J. (Corresponding author)FZJ*RWTH* ; Zehl, L.FZJ*RWTH* ; Pick, J.FZJ* ; Sonntag, M. ; Grewe, J. ; Wachtler, T.Extern* ; Grün, S.FZJ*RWTH* ; Denker, M.FZJ*RWTH*

2019
Frontiers Research Foundation Lausanne

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Please use a persistent id in citations: http://hdl.handle.net/2128/23055  doi:10.3389/fninf.2019.00062

Abstract: An essential aspect of scientific reproducibility is a coherent and complete acquisition of metadata along with the actual data of an experiment. The high degree of complexity and heterogeneity of neuroscience experiments requires a rigorous management of the associated metadata. The odML framework represents a solution to organize and store complex metadata digitally in a hierarchical format that is both human and machine readable. However, this hierarchical representation of metadata is difficult to handle when metadata entries need to be collected and edited manually during the daily routines of a laboratory. With odMLtables, we present an open-source software solution that enables users to collect, manipulate, visualize, and store metadata in tabular representations (in xls or csv format) by providing functionality to convert these tabular collections to the hierarchically structured metadata format odML, and to either extract or merge subsets of a complex metadata collection. With this, odMLtables bridges the gap between handling metadata in an intuitive way that integrates well with daily lab routines and commonly used software products on the one hand, and the implementation of a complete, well-defined metadata collection for the experiment in a standardized format on the other hand. We demonstrate usage scenarios of the odMLtables tools in common lab routines in the context of metadata acquisition and management, and show how the tool can assist in exploring published datasets that provide metadata in the odML format.

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Contributing Institute(s):

1. Computational and Systems Neuroscience (INM-6)
2. Theoretical Neuroscience (IAS-6)
3. Jara-Institut Brain structure-function relationships (INM-10)
4. Strukturelle und funktionelle Organisation des Gehirns (INM-1)

Research Program(s):

1. 571 - Connectivity and Activity (POF3-571) (POF3-571)
2. DFG project 322093511 - Kognitive Leistung als Ergebnis koordinierter neuronaler Aktivität in unreifen präfrontal-hippokampalen Netzwerken (322093511) (322093511)
3. DFG project 238707842 - Kausative Mechanismen mesoskopischer Aktivitätsmuster in der auditorischen Kategorien-Diskrimination (238707842) (238707842)
4. SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) (HGF-SMHB-2013-2017)
5. HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270) (720270)
6. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)
7. HDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612) (HDS-LEE-20190612)

Appears in the scientific report 2019

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Database coverage:
; ; ; ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; DOAJ Seal ; IF < 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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