% 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”.

@ARTICLE{Tsybenko:1048357,
      author       = {Tsybenko, Hanna and Menon, Sarath and Chen, Fei and Guzman,
                      Abril Azocar and Grünwald, Katharina and Brinckmann,
                      Steffen and Hickel, Tilmann and Dahmen, Tim and Hofmann,
                      Volker and Sandfeld, Stefan and Schwaiger, Ruth},
      title        = {{D}igital {T}ransformation in {M}aterials {S}cience: {A}
                      {U}ser {J}ourney of {N}anoindentation, {I}mage {A}nalysis
                      and {S}imulations},
      journal      = {Data science journal},
      volume       = {24},
      issn         = {1683-1470},
      address      = {Paris},
      publisher    = {CODATA},
      reportid     = {FZJ-2025-04577},
      pages        = {33},
      year         = {2025},
      abstract     = {A robust digital infrastructure, built upon overarching
                      frameworks and software tools, is essential for the ongoing
                      digital transformation in materials science and engineering.
                      This user journey demonstrates the seamless integration of
                      distinct technical solutions for data handling and analysis,
                      enabling (a) the pursuit of a specific scientific question
                      and (b) adherence to FAIR principles. The scientific study
                      selected for this user journey focuses on comparing
                      different measures of the elastic modulus of a typical
                      engineering material. The user journey involves three
                      research groups replicating real-world collaborative
                      research scenarios. Specifically, it integrates existing
                      digital solutions for experimental data management
                      (PASTA-ELN), simulation workflow execution (pyiron), and
                      image processing workflow execution (Chaldene). Within the
                      auxiliary data management workflow, generated data and
                      metadata are systematically stored in repositories, with
                      metadata aligned to the MatWerk Ontology. Key insights from
                      this user journey include lessons learned from scientists’
                      perspectives and recommendations for improvement, such as
                      machine-readable experimental protocols, standardized
                      workflow representation, and automated metadata extraction.},
      cin          = {IAS-9},
      ddc          = {500},
      cid          = {I:(DE-Juel1)IAS-9-20201008},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.5334/dsj-2025-033},
      url          = {https://juser.fz-juelich.de/record/1048357},
}