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@INPROCEEDINGS{Giesler:859352,
      author       = {Giesler, André and Czekala, Myriam and Hagemeier, Björn},
      title        = {{U}ni{P}rov - {P}rovenance {M}anagement for {UNICORE}
                      {W}orkflows in {HPC} {E}nvironments},
      volume       = {11017},
      address      = {Cham},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2019-00220},
      isbn         = {978-3-319-98378-3 (print)},
      series       = {Lecture Notes in Computer Science},
      pages        = {188 - 191},
      year         = {2018},
      comment      = {Provenance and Annotation of Data and Processes /
                      Belhajjame, Khalid (Editor) [0000-0001-6938-0820] ; Cham :
                      Springer International Publishing, 2018, Chapter 16 ; ISSN:
                      0302-9743=1611-3349 ; ISBN:
                      978-3-319-98378-3=978-3-319-98379-0 ;
                      doi:10.1007/978-3-319-98379-0},
      booktitle     = {Provenance and Annotation of Data and
                       Processes / Belhajjame, Khalid (Editor)
                       [0000-0001-6938-0820] ; Cham : Springer
                       International Publishing, 2018, Chapter
                       16 ; ISSN: 0302-9743=1611-3349 ; ISBN:
                       978-3-319-98378-3=978-3-319-98379-0 ;
                       doi:10.1007/978-3-319-98379-0},
      abstract     = {The goal of comprehensive provenance tracking in the
                      scientific environment should be the inclusion of the entire
                      life cycle of data management. Thus, the data collection
                      process begins with the registration of lab-generated or
                      sensor-generated data, continues to organize and manage data
                      in the storage repositories, processing analysis and
                      simulation data on clusters and HPC systems, and finally
                      referencing and verifying computational results in
                      scientific publications. In the associated provenance
                      tracking life cycle, UniProv initially concentrates on the
                      processing and simulation of data in scientific workflows
                      used in particular on supercomputers in the HPC environment.
                      In this context, UniProv aims to create the core of a
                      provenance management framework that can be extended in
                      order to integrate different sources of the scientific
                      provenance cycle. Here UniProv should facilitate the
                      creation, the standardized formalization, the storage and
                      the retrieval of Provenance Information.},
      month         = {Jul},
      date          = {2018-07-09},
      organization  = {7th International Provenance and
                       Annotation Workshop, London (UK), 9 Jul
                       2018 - 13 Jul 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:000477747000016},
      doi          = {10.1007/978-3-319-98379-0_16},
      url          = {https://juser.fz-juelich.de/record/859352},
}