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@BOOK{Schlenz:1051956,
      author       = {Schlenz, Hartmut and Bronger, Torsten and Selzer, Michael
                      and Nestler, Britta and Enahoro, Salome Ehinomen and Riem,
                      Leo},
      title        = {{R}esearch {D}ata {M}anagement - {A} {P}ractical
                      {I}ntroduction; {V} 1.0},
      address      = {zenodo.org},
      publisher    = {Zenodo},
      reportid     = {FZJ-2026-00637},
      pages        = {103 pages},
      year         = {2025},
      abstract     = {The motivation for this best practice manual for research
                      data management (RDM) resulted from many discussions and
                      interviews that we conducted with users from the engineering
                      and natural sciences communities. It became clear again and
                      again that a practice-oriented guide for real research data
                      management is missing and urgently needed. The available,
                      more theoretically oriented presentations are generally only
                      of limited help in practical application. For example, they
                      do not explain how to specifically write a data management
                      plan (DMP) and what third-party funding bodies look out for.
                      Even for the practical operation of an electronic laboratory
                      notebook (ELN), users are almost exclusively dependent on
                      the manuals of the respective system, which represents a
                      major hurdle for many users. Legal issues are also often a
                      problem, for example when it comes to granting licenses or
                      using external data. We have therefore decided to write this
                      best practice handbook for RDM in order to close these gaps
                      and provide free practical help for scientists. For example,
                      we go into detail about how to write a DMP, explain the
                      legal aspects of RDM that need to be taken into account in
                      everyday life, show examples of how to use and operate the
                      open-source electronic lab note-books JuliaBase, eLabFTW and
                      Kadi4Mat, discuss aspects of data quality and analysis and
                      which open-source software can be used for this purpose. We
                      show how data can be exchanged and tracked between different
                      ELNs and we demonstrate the publication of data. We also
                      explain how research data can be used and reused for machine
                      learning and what requirements must be met for this.
                      Finally, we explain secure ways of permanently storing data
                      and provide helpful tips and references for finding further
                      information.},
      keywords     = {Research data management (Other) / Best-Practice (Other) /
                      Manual (Other) / Handbook (Other) / ELN (Other) / Electronic
                      Lab Notebook (Other) / Juliabase (Other) / eLabFTW (Other) /
                      Kadi4Mat (Other) / SciMesh (Other)},
      cin          = {IMD-2 / ZB},
      cid          = {I:(DE-Juel1)IMD-2-20101013 / I:(DE-Juel1)ZB-20090406},
      pnm          = {899 - ohne Topic (POF4-899) / NFDI4Ing Task Area CADEN -
                      Task Area CADEN – provenance tracking of physical samples
                      and data samples (442146713-CADEN)},
      pid          = {G:(DE-HGF)POF4-899 / G:(GEPRIS)442146713-CADEN},
      typ          = {PUB:(DE-HGF)3},
      doi          = {10.5281/ZENODO.16870779},
      url          = {https://juser.fz-juelich.de/record/1051956},
}