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      Computing Environments for Reproducibility: Capturing the "Whole Tale"

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          Abstract

          The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and computational details (e.g., scripts and workflows) upon which the findings rely. This envisioned coupling of data and process is essential to advancing science but faces technical and institutional barriers. The Whole Tale project aims to address these barriers by connecting computational, data-intensive research efforts with the larger research process--transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create "living publications" or "tales". The Whole Tale focuses on the full spectrum of science, empowering users in the long tail of science, and power users with demands for access to big data and compute resources. We report here on the design, architecture, and implementation of the Whole Tale environment.

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          Most cited references23

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Reproducible research in computational science.

            Roger Peng (2011)
            Computational science has led to exciting new developments, but the nature of the work has exposed limitations in our ability to evaluate published findings. Reproducibility has the potential to serve as a minimum standard for judging scientific claims when full independent replication of a study is not possible.
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              Scientific workflow management and the Kepler system

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                Author and article information

                Journal
                01 May 2018
                Article
                1805.00400
                d5dea472-fb71-433d-8fec-a66a7cf77010

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                Future Generation Computer Systems, 2018
                cs.CY

                Applied computer science
                Applied computer science

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