% 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”.

@CONFERENCE{Denker:889218,
      author       = {Denker, Michael and Davison, Andrew and Ulianych, Danylo
                      and Sprenger, Julia and Köhler, Cristiano and Gutzen, Robin
                      and Kleinjohann, Alexander and Stella, Alessandra and
                      Jurkus, Regimantas and Essink, Simon and Bouss, Peter and
                      Grün, Sonja},
      title        = {2nd {E}lephant {U}ser {W}orkshop: {A}ccelerate {S}tructured
                      and {R}eproducible {D}ata {A}nalysis in {E}lectrophysiology},
      reportid     = {FZJ-2021-00123},
      year         = {2020},
      abstract     = {This event delves into challenges in the reproducibility of
                      neuroscience workflows dealing with classical
                      electrophysiological activity data, such as spiking data or
                      local field potentials, from experiment or simulation.The
                      training will cover the complete cycle from generating
                      structured and consistent data and metadata, accessing the
                      data, pre-processing, setting up analysis workflows, up to
                      the tracking of the provenance of the analysis results. In
                      this context, the e-infrastructure services of EBRAINS offer
                      a mature data, software and compute services ecosystem with
                      community-driven tools developed in the framework of the
                      Human Brain Project. In the first part of the workshop,
                      participants will be trained in the use of tools covering
                      the following topics: reading and manipulating
                      electrophysiology data in Python using Neo [1] analysis of
                      such data using Elephant [2] best practices for integrating
                      metadata into your workflow to aid the analysis process best
                      practices for structuring analysis results tracking data
                      analysis pipelines using the HBP Knowledge Graph [3]
                      collaboration and sharing documents using the HBP
                      Collaboratory [4] In the second part of the workshop,
                      participants will work together with a tutor in small
                      groups, on their own data and on particular personal
                      interests in the scope of the workshop. To this end,
                      participants are asked to provide a small abstract
                      describing the data set they would like to bring and work on
                      (contents of the dataset, data format, data size...) and the
                      topic they are interested in. The latter may, for example,
                      be related to: annotating the dataset with metadata for
                      collaboration and sharing, working with the dataset in the
                      Neo framework, or performing a certain kind of analysis with
                      the data set. The goal of each group is to get started
                      addressing the topic, identify solutions together with the
                      tutors, and implement a first prototype of the required
                      functionality.},
      month         = {Nov},
      date          = {2020-11-17},
      organization  = {EBRAINS Infrastructure Training,
                       Online (Online), 17 Nov 2020 - 19 Nov
                       2020},
      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          = {574 - Theory, modelling and simulation (POF3-574) / 571 -
                      Connectivity and Activity (POF3-571) / HBP SGA3 - Human
                      Brain Project Specific Grant Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF3-574 / G:(DE-HGF)POF3-571 /
                      G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)5},
      url          = {https://juser.fz-juelich.de/record/889218},
}