Workflows and provenance: Toward information science solutions for the natural sciences

MR Gryk, B Ludäscher - Library trends, 2017 - muse.jhu.edu
MR Gryk, B Ludäscher
Library trends, 2017muse.jhu.edu
The era of big data and ubiquitous computation has brought with it concerns about ensuring
reproducibility in this new research environment. It is easy to assume that computational
methods self-document by their very nature of being exact, deterministic processes.
However, similar to laboratory experiments, ensuring reproducibility in the computational
realm requires the documentation of both the protocols used (workflows), as well as a
detailed description of the computational environment: algorithms, implementations …
Abstract
The era of big data and ubiquitous computation has brought with it concerns about ensuring reproducibility in this new research environment. It is easy to assume that computational methods self-document by their very nature of being exact, deterministic processes. However, similar to laboratory experiments, ensuring reproducibility in the computational realm requires the documentation of both the protocols used (workflows), as well as a detailed description of the computational environment: algorithms, implementations, software environments, and the data ingested and execution logs of the computation. These two aspects of computational reproducibility (workflows and execution details) are discussed within the context of biomolecular Nuclear Magnetic Resonance spectroscopy (bioNMR), as well as the PRIMAD model for computational reproducibility.
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