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@INPROCEEDINGS{Wagner:905196,
      author       = {Wagner, Adina Svenja and Poline, Jean-Baptiste and Hanke,
                      Michael},
      title        = {{A} pragmatic approach to reusable research outputs},
      reportid     = {FZJ-2022-00479},
      year         = {2021},
      abstract     = {Science is an incremental process that produces and builds
                      on more than journal articles¹. Code, data, results, or
                      tools of previous finished or unfinished projects (research
                      outputs) fuel new undertakings.Reusing research objects
                      allows for reproduction, verification, and extending
                      existing work, evidence synthesis, and minimizing duplicate
                      efforts². The more reusable outputs are, at any stage of a
                      project, the better. The FAIR principles³ center around
                      richly curated metadata to reach maximal reusability. In
                      practice, creating fully FAIR resources is difficult in
                      systems that yet lack or fail to incentivize the necessary
                      standards and procedures. But reusability should be improved
                      nevertheless.We highlight four widely accessible strategies
                      that can elevate reusability as a byproduct of pragmatic
                      research data management, even when compliance to FAIR is
                      not yet possible. ¹ Mons, B. (2018). Data Stewardship for
                      Open Science: Implementing FAIR Principles. CRC Press. ISBN
                      9780815348184² Thanos, C. (2017). Research Data
                      Reusability: Conceptual Foundations, Barriers and Enabling
                      Technologies. doi.org/10.3390/publications5010002³
                      Wilkinson, M. D. et al., (2016). The FAIR Guiding Principles
                      for scientific data management and stewardship.
                      doi.org/10.1038/sdata.2016.18},
      month         = {Jun},
      date          = {2021-06-21},
      organization  = {Organisation for Human Brain Mapping,
                       Montreal (virtual) (USA), 21 Jun 2021 -
                       25 Jun 2021},
      subtyp        = {Other},
      cin          = {INM-7},
      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)24},
      doi          = {10.7490/F1000RESEARCH.1118575.1},
      url          = {https://juser.fz-juelich.de/record/905196},
}