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@ARTICLE{Rybicki:842150,
      author       = {Rybicki, Jedrzej and von St. Vieth, Benedikt},
      title        = {{A} {F}ramework for {R}eproducible {E}valuation of
                      {S}emantic {S}torage {O}ptions},
      journal      = {International Journal on Advances in
                      Software[[Elektronische Ressource]]},
      volume       = {10},
      number       = {$3\&4$},
      issn         = {1942-2628},
      address      = {[S.l.]},
      publisher    = {IARIA},
      reportid     = {FZJ-2018-00424},
      pages        = {345-354},
      year         = {2017},
      abstract     = {spite the urgent need to conduct computer-driven
                      experiments in a reproducible fashion, there is no
                      widely-accepted, established approach to this problem. The
                      rise of Open Data surely helps in understanding and
                      verifying some of the research findings, but the true
                      verification comes from a means to reproduce the original
                      tests. This paper proposes a framework for conducting such
                      reproducible experiments. It leverages Docker to facilitate
                      exchange of, not just source code used in test trails but
                      rather whole, ready-to-run experimental environments. The
                      lightweight virtualization provided by Docker makes it very
                      portable across a wide variety of hardware and software
                      platforms. We explain the framework in detail, discuss its
                      advantages as well as shortcomings, and assess how
                      future-proof it is. The usability of the proposed framework
                      was verified by conducting a reproducible evaluation of the
                      possible storage options for semantic annotations. This use
                      case emerged in the context of a particular distributed
                      infrastructure, where users requested a possibility to
                      annotate stored digital objects. There are many possible
                      technologies that can be used to store semantic annotations.
                      We evaluated performance and suitability of relational
                      databases, document stores, and graph databases, to conclude
                      that the graph database is the best candidate to efficiently
                      handle the task. Although, it has also some limitations,
                      which we will point out. By using the proposed framework in
                      the aforementioned evaluation, we enable other researchers
                      to repeat it, but also benchmark alternative technologies if
                      required. Furthermore, the framework can be reused in an
                      iterative process of performance tuning of the selected
                      storage option, to quantify and verify the influence of
                      particular configuration changes. The main output of this
                      paper is a framework which allows to easily redo the
                      evaluation of semantic storage options.},
      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)16},
      url          = {https://juser.fz-juelich.de/record/842150},
}