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@ARTICLE{Szczepanik:1026363,
      author       = {Szczepanik, Michał and Wagner, Adina S. and Heunis,
                      Stephan and Waite, Laura K. and Eickhoff, Simon B. and
                      Hanke, Michael},
      title        = {{T}eaching {R}esearch {D}ata {M}anagement with {D}ata{L}ad:
                      {A} {M}ulti-year, {M}ulti-domain {E}ffort},
      journal      = {Neuroinformatics},
      volume       = {22},
      issn         = {1539-2791},
      address      = {New York, NY},
      publisher    = {Springer},
      reportid     = {FZJ-2024-03394},
      pages        = {635-645},
      year         = {2024},
      abstract     = {Research data management has become an indispensable skill
                      in modern neuroscience. Researchers can benefit from
                      following good practices as well as from having proficiency
                      in using particular software solutions. But as these
                      domain-agnostic skills are commonly not included in
                      domain-specific graduate education, community efforts
                      increasingly provide early career scientists with
                      opportunities for organised training and materials for
                      self-study. Investing effort in user documentation and
                      interacting with the user base can, in turn, help developers
                      improve quality of their software. In this work, we detail
                      and evaluate our multi-modal teaching approach to research
                      data management in the DataLad ecosystem, both in general
                      and with concrete software use. Spanning an online and
                      printed handbook, a modular course suitable for in-person
                      and virtual teaching, and a flexible collection of research
                      data management tips in a knowledge base, our free and open
                      source collection of training material has made research
                      data management and software training available to various
                      different stakeholders over the past five years.},
      cin          = {INM-7},
      ddc          = {540},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38713426},
      UT           = {WOS:001215338300001},
      doi          = {10.1007/s12021-024-09665-7},
      url          = {https://juser.fz-juelich.de/record/1026363},
}