There is a significant mismatch between traditional scientific dissemination practices and modern computational research practice that leads to reproducibility concerns. The Whole Tale platform supports computational reproducibility by enabling researchers to create and package code, data and information about the workflow and computational environment necessary to support review and reproduce results of computational analyses that are reported in published research. Whole Tale supports explicit citation of externally referenced data, capturing the artifacts and provenance information needed to facilitate understanding, transparency, and execution of the computational processes and workflows used for review and reproducibility at the time of publication.
The Whole Tale platform allows researchers to create tales. A tale is an executable research object that combines data (references), code (computational methods), computational environment, and narrative (traditional science story). Tales are captured in a standards-based format complete with metadata. The Tale stores explicit references to data and code used in computational experiments, both for reproducibility purposes and to permit the citation of the specific versions used in any subsequent research. A Tale can be submitted (e.g. published) to an external research repository and assigned a persistent identifier by the repository. The Whole Tale platform allows users to interactively create and edit Tales and to re-run a Tale to reproduce and verify results as obtained by the original Tale creator.
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- K. Chard, N. Gaffney, M. B. Jones, K. Kowalik, B. Ludascher, J. Nabrzyski, V. Stodden, I. Taylor, M. J. Turk, and C. Willis, “Implementing computational reproducibility in the whole tale environment,” in Proceedings of the 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems, ser. P-RECS 19. New York, NY, USA: Association for Computing Machinery, 2019, p. 1722.
- B. Mecum, S. Wyngaard, C. Willis, M. Turk, T. Thelen, I. Taylor, V. Stodden, D. Perez, J. Nabrzyski, B. Ludaescher, S. Kulasekaran, K. Kowalik, M. B. Jones, M. Hategan, N. Gaffney, K. Chard, and A. Brinckman, “Science, containerized: Integrating provenance and compute environments with the Whole Tale,” in AGU Fall Meeting Abstracts, vol. 2018, Dec 2018, pp. IN53A–02.
This material is based upon work supported by the National Science Foundation under Grant No. OAC-1541450.