Paper Mâché: Creating dynamic reproducible science

Grant R. Brammer, Ralph W. Crosby, Suzanne J. Matthews, Tiffani L. Williams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

For centuries, the research paper have been the main vehicle for scientific progress. From the paper, readers in the scientific community are expected to extract all the relevant information necessary to reproduce and validate the results presented by the paper's authors. However, the increased use of computer software in science makes reproducing scientific results increasingly difficult. The research paper in its current state is no longer sufficient to fully reproduce, validate, or review a paper's experimental results and conclusions. This impedes scientific progress. To remedy these concerns, we introduce Paper Mâché, a new system for creating dynamic, executable research papers. The key novelty of Paper Mâché is its use of virtual machines, which lets readers and reviewers easily view and interact with a paper, and reproduce key experimental results. For authors, the Paper Mâché workbench provides an easy-touse interface to build an executable paper. By transforming the static research paper into a dynamic and interactive entity, Paper Mâché brings the presentation of scientific results into the 21st century. We believe that Paper Mâché will become indispensable to the scientific process, and increase the visibility of key findings among members and non-members of the scientific community.
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Pages658-667
Number of pages10
DOIs
StatePublished - May 14 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-28
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: This publication is based in part on work supported by Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). This work was also supported by the National Foundation under grants DEB-0629849, IIS-0713618, and IIS-1018785.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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