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@INPROCEEDINGS{Rybicki:851644,
      author       = {Rybicki, Jedrzej},
      title        = {{B}est {P}ractices in {S}tructuring {D}ata {S}cience
                      {P}rojects},
      volume       = {854},
      address      = {Cham},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2018-05194},
      isbn         = {978-3-319-99992-0 (print)},
      series       = {Advances in Intelligent Systems and Computing},
      pages        = {348 - 357},
      year         = {2019},
      comment      = {Information Systems Architecture and Technology:
                      Proceedings of 39th International Conference on Information
                      Systems Architecture and Technology – ISAT 2018 /
                      Wilimowska, Zofia (Editor) ; Cham : Springer International
                      Publishing, 2019, Chapter 31 ; ISSN: 2194-5357=2194-5365 ;
                      ISBN: 978-3-319-99992-0=978-3-319-99993-7 ;
                      doi:10.1007/978-3-319-99993-7},
      booktitle     = {Information Systems Architecture and
                       Technology: Proceedings of 39th
                       International Conference on Information
                       Systems Architecture and Technology –
                       ISAT 2018 / Wilimowska, Zofia (Editor)
                       ; Cham : Springer International
                       Publishing, 2019, Chapter 31 ; ISSN:
                       2194-5357=2194-5365 ; ISBN:
                       978-3-319-99992-0=978-3-319-99993-7 ;
                       doi:10.1007/978-3-319-99993-7},
      abstract     = {The goal of Data Science projects is to extract knowledge
                      and insights from collected data. The focus is put on the
                      novelty and usability of the obtained insights. However, the
                      impact of a project can be seriously reduced if the results
                      are not communicated well. In this paper, we describe a
                      means of managing and describing the outcomes of the Data
                      Science projects in such a way that they optimally convey
                      the insights gained. We focus on the main artifact of the
                      non-verbal communication, namely project structure. In
                      particular, we surveyed three sources of information on how
                      to structure projects: common management methodologies,
                      community best practices, and data sharing platforms. The
                      survey resulted in a list of recommendations on how to build
                      the project artifacts to make them clear, intuitive, and
                      logical. We also provide hints on tools that can be helpful
                      for managing such structures in an efficient manner. The
                      paper is intended to motivate and support an informed
                      decision on how to structure a Data Science project to
                      facilitate better communication of the outcomes.},
      month         = {Sep},
      date          = {2018-09-16},
      organization  = {39th International Conference on
                       Information Systems Architecture and
                       Technology – ISAT 2018, Nysa
                       (Poland), 16 Sep 2018 - 19 Sep 2018},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {512 - Data-Intensive Science and Federated Computing
                      (POF3-512)},
      pid          = {G:(DE-HGF)POF3-512},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:000460635000031},
      doi          = {10.1007/978-3-319-99993-7_31},
      url          = {https://juser.fz-juelich.de/record/851644},
}