Open MIND · 2018 · 14 citations · 6 references
ComputingData ScienceExperimental DesignKnowledge RepresentationData ProvenanceDissemination Of Research FindingsProvenance ResearchSource AuthenticationSource Data VerificationSource ProvenanceProvenance Models
End-to-end reproducibility of scientific experiments is a key<br>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 re-<br>producibility. 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<br>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 life-cycle of a scientific experiment taking into account the use case of life<br>science experiments.
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