Towards Reproducible Research in a Biomedical Collaboration Platform Following the FAIR Guiding Principles
International Conference on Utility and Cloud Computing(2017)
Abstract
Replication of computational experiments is essential for verifiable research. However, it requires a comprehensive and unambiguous description of all employed digital artifacts, in particular data, code and the computational environment. Recently, the FAIR Guiding Principles have been published to support reproducible research. In this paper, a cloud-based biomedical collaboration platform has been evaluated regarding FAIR principles and has been extended to support reproducibility. The FAICE suite is presented, encompassing tools to thoroughly describe and reproduce a computational experiment within the original execution environment as well as within a dynamically configured VM.
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Key words
Reproducibility,Repeatability,Medical Data,XNAT,Docker,Cloud Computing
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