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@INPROCEEDINGS{Hagemeier:185674,
      author       = {Hagemeier, Björn and Bücker, Oliver and Giesler, André
                      and Saini, Rajveer and Schuller, Bernd},
      title        = {{A} {W}orkflow for {P}olarized {L}ight {I}maging {U}sing
                      {UNICORE} {W}orkflow {S}ervices},
      volume       = {26},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2014-07099},
      isbn         = {978-3-95806-004-3},
      series       = {IAS Series},
      pages        = {1-14},
      year         = {2014},
      comment      = {UNICORE Summit 2014},
      booktitle     = {UNICORE Summit 2014},
      abstract     = {Understanding the anatomical structure of the human brain
                      on the level of single nerve fibers is one of the most
                      challenging tasks in neuroscience nowadays. In order to
                      understand the connectivity of brain regions (affecting the
                      brain function) on the one hand and to study
                      neurodegenerative diseases on the other hand, a detailed
                      three-dimensional map of nerve fibers has to be created. One
                      technique applied to histological sections of postmortem
                      brains is Polarized Light Imaging which allows the study of
                      brain regions with a resolution at sub-millimeter scale. It
                      is based on an optical property referred to as birefringence
                      of myelin which surrounds the axons of nerve fibers.
                      Therefore about 1500 slices, each 70 micron thick, of the
                      post-mortem brain are imaged with a microscopic device using
                      polarized light.The images of brain slices are processed
                      with a chain of tools for calibration, independent component
                      analysis, enhanced analysis, stitching and segmentation.
                      These tools have been integrated in a UNICORE workflow,
                      exploiting many of the workflow system features, such as
                      control structures and human interaction. Prior to the
                      introduction of the UNICORE workflow system, the tools
                      involved were run manually by their respective developers.
                      Thus, once one step in the process was finished, the
                      developer of the next tool in the chain would retrieve the
                      data and run his tools on the output of the former. This
                      manual approach led to delays in the entire process.The
                      introduction of the UNICORE workflow system for this
                      particular use case resulted in several benefits. First of
                      all, the results are easier to reproduce now, as fewer
                      manual steps are involved. Secondly, the makespan of the
                      entire workflow could be reduced to hours rather than weeks,
                      because of the almost fully automated workflow. Lastly, only
                      the automated approach will allow for the timely analysis of
                      a large number of brain slices that are expected to be
                      available in the near future.This workflow is interesting
                      from the technical point of view, as it takes UNICORE and
                      its workflow system to the limits. Workarounds were required
                      for some peculiarities of the workflow system. For example,
                      in order to use results of one workflow job as input in the
                      next job, the workflow system usually copies this data to
                      the central workflow storage before copying it into the
                      working directory of the next job. The amount of data for a
                      single brain slice is on the order of magnitude of up to
                      1TB, with intermediate results at the same scale. Thus, the
                      total amount of data easily adds up to several TB of data
                      movement within the workflow, which can and should be
                      avoided.This paper will describe the situation as of version
                      6.6.0 of the workflow system. Results of this work have been
                      incorporated in subsequent versions starting with 7.0.0.
                      However, some of the approaches for processing large sets of
                      data used here will still apply in future versions of the
                      UNICORE system.},
      month         = {Jun},
      date          = {2014-06-24},
      organization  = {UNICORE Summit 2014, Leipzig
                       (Germany), 24 Jun 2014 - 24 Jun 2014},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {412 - Grid Technologies and Infrastructures (POF2-412) /
                      411 - Computational Science and Mathematical Methods
                      (POF2-411)},
      pid          = {G:(DE-HGF)POF2-412 / G:(DE-HGF)POF2-411},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      url          = {https://juser.fz-juelich.de/record/185674},
}