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@INPROCEEDINGS{Szczepanik:1019361,
      author       = {Szczepanik, Michał},
      title        = {{L}ightweight data publishing on {J}ülich {D}ata with
                      {D}ata{L}ad},
      reportid     = {FZJ-2023-05331},
      year         = {2023},
      abstract     = {Jülich DATA is the central institutional repository for
                      research data of the Research Center Jülich and supports
                      sharing, preserving, citing, exploring, and analyzing
                      research data with descriptive metadata, without hosting
                      large files. In this tutorial, participants will discover
                      how DataLad can integrate with Dataverse and have the best
                      of both worlds: Discoverability and metadata with Jülich
                      DATA, and actionable data tracking with DataLad. With
                      conceptual and hands-on elements, we will learn how to
                      publish or clone lightweight DataLad datasets to and from
                      Jülich DATA.},
      month         = {Oct},
      date          = {2023-10-17},
      organization  = {INM Retreat 2023, Jülich (Germany),
                       17 Oct 2023 - 18 Oct 2023},
      subtyp        = {Other},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      SFB 1451 INF - Datenmanagement für computergestützte
                      Modellierung (INF) (458705875)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(GEPRIS)458705875},
      typ          = {PUB:(DE-HGF)31},
      doi          = {10.5281/ZENODO.10010615},
      url          = {https://juser.fz-juelich.de/record/1019361},
}