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@INPROCEEDINGS{Ulianych:873932,
      author       = {Ulianych, Danylo and Gutzen, Robin and Sprenger, Julia and
                      Pastorelli, Elena and De Bonis, Giulia and Paolucci, Pier
                      Stanislao and Grün, Sonja and Denker, Michael},
      title        = {{D}esigning reproducible analysis workflows for
                      experimental and simulated activity using {E}lephant},
      reportid     = {FZJ-2020-01105},
      year         = {2020},
      abstract     = {Neuroscientists have a diversified and constantly growing
                      repertoire of methods to analyze neuronal activity data.
                      Moreover, the growing availability of open data sets
                      containing neuronal activity data puts modelers in a
                      position to perform a more in-depth validation of their
                      models (e.g., [1]) based on the statistical descriptions of
                      the activity observed in experiments. However, the increased
                      possibilities also come at the cost of higher complexity of
                      such analysis and validation processes. Here, we showcase
                      the state of HBP-enabled, tool-based workflow solutions that
                      implement rigorous and well-defined data handling and
                      analysis, as well as model validation schemes, for activity
                      data such as spike trains or local field potentials. We
                      demonstrate methods for data and metadata representation,
                      and its analysis using multiple emerging open-source
                      software tools (e.g., [2-4]). Analysis is performed using
                      the Electrophysiology Analysis Toolkit (Elephant,
                      http://neuralensemble.org/elephant/) as a community-centered
                      analysis framework for parallel, multi-scale activity data
                      developed within the HBP, while validation is carried out
                      using the HBP validation framework, and in particular the
                      NetworkUnit library [5-7]. The interplay between the tools
                      is showcased by integrating them into a robust workflow
                      solution. Concrete examples on how to utilize these tools
                      for scientific discovery in conjunction with the
                      Collaboratory and Knowledgegraph HBP infrastructure
                      components, as well as with the snakemake workflow tool, are
                      given in the context of the use cases of SP3
                      [8,9].References1. van Albada, S.J. et al. (2018). Front
                      Neuroinf 12, 291.2. Garcia, S. et al. (2014). Front Neuroinf
                      8, 10.3. Zehl, L. et al. (2016). Front Neuroinf 10, 26.4.
                      Grewe, J. et al. (2011). Front Neuroinf 5, 16.5. Gutzen, R.
                      et al. (2018) Front Neuroinf 12, 90.6. Omar, C. et al.
                      (2014). ICSE Companion 2014, 524–527.7. Sarma, G. P. et
                      al. (2016). F1000 Research, 5:1946.8. Pastorelli, E. et al.
                      (2019) Front. Syst. Neurosci 13, 339. De Bonis, G. et al.
                      (2019) Front. Syst. Neurosci. doi: 10.3389/fnsys.2019.00070
                      (in press)},
      month         = {Feb},
      date          = {2020-02-03},
      organization  = {Human Brain Project Summit, Athens
                       (Greece), 3 Feb 2020 - 6 Feb 2020},
      subtyp        = {Invited},
      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          = {571 - Connectivity and Activity (POF3-571) / 574 - Theory,
                      modelling and simulation (POF3-574) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907)},
      pid          = {G:(DE-HGF)POF3-571 / G:(DE-HGF)POF3-574 /
                      G:(EU-Grant)785907},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/873932},
}