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@MISC{Villamar:1052977,
      author       = {Villamar, Jose and Kelbling, Matthias and Thober, Stephan},
      othercontributors = {More, Heather and Denker, Michael and Tetzlaff, Tom and
                          Senk, Johanna},
      title        = {{M}etadata {A}rchivist - {P}roof of {C}oncept},
      reportid     = {FZJ-2026-01327},
      year         = {2025},
      abstract     = {This archive contains an example implementation of a
                      knowledge generation workflow. Here the questions to answer
                      relate to benchmarking and validation of a given simulator
                      and model. In this workflow, 10 simulation runs of a model
                      are performed while collecting metadata. Then the generated
                      data is post processed to ensure an aggregation of
                      simulation statistics over the 10 different runs. These
                      statistics alongside system information are used to
                      structure the metadata. Both raw and post-processed, data
                      and metadata are stored in a MongoDB instance. This instance
                      can then be queried to plot the benchmarks and validation
                      results.},
      keywords     = {Snakemake workflow (Other) / Metadata processing (Other) /
                      Simulation workflow (Other)},
      cin          = {IAS-6},
      cid          = {I:(DE-Juel1)IAS-6-20130828},
      pnm          = {5231 - Neuroscientific Foundations (POF4-523) / 5232 -
                      Computational Principles (POF4-523)},
      pid          = {G:(DE-HGF)POF4-5231 / G:(DE-HGF)POF4-5232},
      typ          = {PUB:(DE-HGF)33},
      doi          = {10.5281/ZENODO.15110701},
      url          = {https://juser.fz-juelich.de/record/1052977},
}