% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@INPROCEEDINGS{Khler:894266,
      author       = {Köhler, Cristiano},
      title        = {{FAIR}ification of electrophysiology data analysis:
                      provenance capture in the {E}lephant toolbox},
      reportid     = {FZJ-2021-03141},
      year         = {2021},
      note         = {Contribution to the Human Brain Project Booth at the INCF
                      Neuroinformatics Assembly 2021},
      abstract     = {The analysis of electrophysiology data typically comprises
                      multiple steps. These often consist of several scripts
                      executed in a specific temporal order, which take different
                      parameter sets and use distinct data files. As the
                      researcher adjusts the individual analysis steps to
                      accommodate new hypotheses or additional data, the resulting
                      workflows may become increasingly complex, and undergo
                      frequent changes. Although it is possible to use workflow
                      management systems to organize the execution of the scripts
                      and capture provenance information at the level of the
                      script (i.e., which script file was executed, and in which
                      environment?) and data file (i.e., which input and output
                      files were supplied to that script), the resulting
                      provenance track does not automatically provide details
                      about the actual analysis carried out inside each script.
                      Therefore, the final analysis results can only be understood
                      by source code inspection or reliance in any accompanying
                      documentation. We focus on two open-source tools for the
                      analysis of electrophysiology data developed in EBRAINS. The
                      Neo $(RRID:SCR_000634)$ framework provides an object model
                      to standardize neural activity data acquired from distinct
                      sources. Elephant $(RRID:SCR_003833)$ is a Python toolbox
                      that provides several functions for the analysis of
                      electrophysiology data. We set to improve these tools by
                      implementing a data model that captures detailed provenance
                      information and by representing the analysis results in a
                      systematic and formalized manner. Ultimately, these
                      developments aim to improve reproducibility,
                      interoperability, findability, and re-use of analysis
                      results.},
      organization  = {INCF Neuroinformatics Assembly 2021,
                       online (online)},
      subtyp        = {Other},
      cin          = {INM-6 / INM-10 / IAS-6},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)INM-10-20170113 /
                      I:(DE-Juel1)IAS-6-20130828},
      pnm          = {5235 - Digitization of Neuroscience and User-Community
                      Building (POF4-523) / 5231 - Neuroscientific Foundations
                      (POF4-523) / 571 - Connectivity and Activity (POF3-571) /
                      574 - Theory, modelling and simulation (POF3-574) / HDS LEE
                      - Helmholtz School for Data Science in Life, Earth and
                      Energy (HDS LEE) (HDS-LEE-20190612) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907) / HBP SGA3 -
                      Human Brain Project Specific Grant Agreement 3 (945539) /
                      HAF - Helmholtz Analytics Framework (ZT-I-0003)},
      pid          = {G:(DE-HGF)POF4-5235 / G:(DE-HGF)POF4-5231 /
                      G:(DE-HGF)POF3-571 / G:(DE-HGF)POF3-574 /
                      G:(DE-Juel1)HDS-LEE-20190612 / G:(EU-Grant)785907 /
                      G:(EU-Grant)945539 / G:(DE-HGF)ZT-I-0003},
      typ          = {PUB:(DE-HGF)31},
      url          = {https://juser.fz-juelich.de/record/894266},
}