A provenance-based infrastructure to support the life cycle of executable papers

David Koop, Emanuele Santos, Phillip Mates, Huy T. Vo, Philippe Bonnet, Bela Bauer, Brigitte Surer, Matthias Troyer, Dean N. Williams, Joel E. Tohline, Juliana Freire, Cláudio T. Silva

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


As publishers establish a greater online presence as well as infrastructure to support the distribution of more varied information, the idea of an executable paper that enables greater interaction has developed. An executable paper provides more information for computational experiments and results than the text, tables, and figures of standard papers. Executable papers can bundle computational content that allow readers and reviewers to interact, validate, and explore experiments. By including such content, authors facilitate future discoveries by lowering the barrier to reproducing and extending results. We present an infrastructure for creating, disseminating, and maintaining executable papers. Our approach is rooted in provenance, the documentation of exactly how data, experiments, and results were generated. We seek to improve the experience for everyone involved in the life cycle of an executable paper. The automated capture of provenance information allows authors to easily integrate and update results into papers as they write, and also helps reviewers better evaluate approaches by enabling them to explore experimental results by varying parameters or data. With a provenance-based system, readers are able to examine exactly how a result was developed to better understand and extend published findings.

Original languageEnglish (US)
Title of host publicationProcedia Computer Science
Number of pages10
StatePublished - 2011
Event11th International Conference on Computational Science, ICCS 2011 - Singapore, Singapore
Duration: Jun 1 2011Jun 3 2011


Other11th International Conference on Computational Science, ICCS 2011


  • Executable paper
  • Provenance
  • Reproducibility
  • Scientific workflows

ASJC Scopus subject areas

  • General Computer Science


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