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Integrative Data Management for Reproducibility of Microscopy Experiments

  • Sheeba SamuelEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10250)

Abstract

Reproducibility is a fundamental factor in every domain of science since it allows scientists to trust data and results. The scientific community is interested in the results of experiments which are reproducible, reusable and understandable. In this paper, we present our work towards reproducibility of scientific experiments taking into account the use case of microscopy. We aim to analyze the components that are vital for reproducibility and to develop an integrative data management platform for scientific experiments. In this article, we show the use of Semantic Web technologies to conserve an experiment environment and its workflow. This allows scientists to ask queries related to an experiment and compare results. We present our approach for scientists to represent, search and share their experimental data and results to the scientific community for better data interoperability and reuse. Our overall goal is to extend data management and Semantic Web technologies to enable reproducibility.

Keywords

Reproducibility Experiments Ontology Microscopy Provenance 

Notes

Acknowledgements

This research is supported by the Deutsche Forschungsgemeinschaft (DFG) in Project Z2 of the CRC/TRR 166 High-end light microscopy elucidates membrane receptor function - ReceptorLight. I thank Birgitta König-Ries and H. Martin Bücker for their guidance and feedback for the research plan. I thank Christoph Biskup and Kathrin Groeneveld from the Biomolecular Photonics Group at University Hospital Jena, Germany, for providing the requirements to develop the proposed approach and validating the system.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Heinz-Nixdorf Chair for Distributed Information SystemsFriedrich-Schiller UniversityJenaGermany

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