The Story of an Experiment:A Provenance-based Semantic Approach towards Research Reproducibility

End-to-end reproducibility of scientific experiments is a key to the foundation of science. Reproducibility of an experiment does not necessarily guarantee the accuracy of its results, but it guarantees that the steps of an experiment can be repeated to a certain level of significance to generate similar results. Data provenance plays a key role in telling the story of an experiment which helps one step towards reproducibility. To convey the message of a story, it is essential to provide sufficient data and its flow along with its semantics. In this paper, we present a provenance-based semantic approach to explain the story of a scientific experiment with the primary goal of reproducibility. The REPRODUCE-ME ontology extended from PROV-O and P-Plan is used to represent the whole story of an experiment describing the path it took from its design to result. We visualize and evaluate the provenance lifecycle of a scientific experiment taking into account the use case of life science experiments.

@inproceedings{DBLP:conf/swat4ls/SamuelGTWKLKBB18,
  author    = {Sheeba Samuel and
               Kathrin Groeneveld and
               Frank Taubert and
               Daniel Walther and
               Tom Kache and
               Teresa Langenst{\"{u}}ck and
               Birgitta K{\"{o}}nig{-}Ries and
               H. Martin B{\"{u}}cker and
               Christoph Biskup},
  title     = {The Story of an experiment: a provenance-based semantic approach towards
               research reproducibility},
  booktitle = {Proceedings of the 11th International Conference Semantic Web Applications
               and Tools for Life Sciences, {SWAT4LS} 2018, Antwerp, Belgium, December
               3-6, 2018.},
  year      = {2018},
  crossref  = {DBLP:conf/swat4ls/2018},
  url       = {http://ceur-ws.org/Vol-2275/paper2.pdf},
  timestamp = {Tue, 18 Dec 2018 14:48:01 +0100},
  biburl    = {https://dblp.org/rec/bib/conf/swat4ls/SamuelGTWKLKBB18},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}