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@INPROCEEDINGS{Giesler:827958,
      author       = {Giesler, André and Czekala, Myriam and Hagemeier, Björn
                      and Grunzke, Richard},
      title        = {{U}ni{P}rov: {A} flexible {P}rovenance {T}racking {S}ystem
                      for {UNICORE}},
      volume       = {10164},
      address      = {Cham},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2017-01986},
      isbn         = {978-3-319-53861-7},
      series       = {Lecture Notes in Computer Science},
      pages        = {233-242},
      year         = {2017},
      comment      = {High-Performance Scientific Computing / Di Napoli, Edoardo
                      (Editor) ; Cham : Springer International Publishing, 2017,
                      Chapter 20 ; ISSN: 0302-9743=1611-3349 ; ISBN:
                      978-3-319-53861-7=978-3-319-53862-4 ;
                      doi:10.1007/978-3-319-53862-4},
      booktitle     = {High-Performance Scientific Computing
                       / Di Napoli, Edoardo (Editor) ; Cham :
                       Springer International Publishing,
                       2017, Chapter 20 ; ISSN:
                       0302-9743=1611-3349 ; ISBN:
                       978-3-319-53861-7=978-3-319-53862-4 ;
                       doi:10.1007/978-3-319-53862-4},
      abstract     = {In this paper we present a flexible provenance managment
                      system called UniProv. UniProv is an ongoing development
                      project providing provenance tracking in scientific
                      workflows and data management particularly in the field of
                      neuroscience, thus allowing users to validateand reproduce
                      tasks and results of their experiments. The primary goal is
                      to equip the commonly used Grid middleware UNICORE and its
                      incorporated workflow engine with the provenance capturing
                      mechanism of UniProv. We also explain an approach for using
                      predefined patterns to ensure compatibility with the W3C
                      PROV Data Model and to map the provenance information
                      properly to a neo4j graph database.},
      month         = {Oct},
      date          = {2016-10-04},
      organization  = {JARA-HPC Symposium, Aachen, Germany, 4
                       Oct 2016 - 5 Oct 2016, Aachen
                       (Germany), 4 Oct 2016 - 5 Oct 2016},
      cin          = {JSC},
      ddc          = {004},
      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},
      doi          = {10.1007/978-3-319-53862-4_20},
      url          = {https://juser.fz-juelich.de/record/827958},
}