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@ARTICLE{Sprenger:865390,
      author       = {Sprenger, Julia and Zehl, Lyuba and Pick, Jana and Sonntag,
                      Michael and Grewe, Jan and Wachtler, Thomas and Grün, Sonja
                      and Denker, Michael},
      title        = {od{ML}tables: {A} {U}ser-{F}riendly {A}pproach for
                      {M}anaging {M}etadata of {N}europhysiological {E}xperiments},
      journal      = {Frontiers in neuroinformatics},
      volume       = {13},
      issn         = {1662-5196},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2019-04875},
      pages        = {62},
      year         = {2019},
      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.},
      cin          = {INM-6 / IAS-6 / INM-10 / INM-1},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113 / I:(DE-Juel1)INM-1-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571) / DFG project
                      322093511 - Kognitive Leistung als Ergebnis koordinierter
                      neuronaler Aktivität in unreifen präfrontal-hippokampalen
                      Netzwerken (322093511) / DFG project 238707842 - Kausative
                      Mechanismen mesoskopischer Aktivitätsmuster in der
                      auditorischen Kategorien-Diskrimination (238707842) / SMHB -
                      Supercomputing and Modelling for the Human Brain
                      (HGF-SMHB-2013-2017) / HBP SGA1 - Human Brain Project
                      Specific Grant Agreement 1 (720270) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907) / HDS LEE -
                      Helmholtz School for Data Science in Life, Earth and Energy
                      (HDS LEE) (HDS-LEE-20190612)},
      pid          = {G:(DE-HGF)POF3-571 / G:(GEPRIS)322093511 /
                      G:(GEPRIS)238707842 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      G:(EU-Grant)720270 / G:(EU-Grant)785907 /
                      G:(DE-Juel1)HDS-LEE-20190612},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31611781},
      UT           = {WOS:000488101100001},
      doi          = {10.3389/fninf.2019.00062},
      url          = {https://juser.fz-juelich.de/record/865390},
}