DEEP: a provenance-aware executable document system

  • Authors:

  • Huanjia Yang;Danius T. Michaelides;Chris Charlton;William J. Browne;Luc Moreau

  • Affiliations:

  • Electronics and Computer Science, University of Southampton, UK;Electronics and Computer Science, University of Southampton, UK;Graduate School of Education, University of Bristol, UK;School of Veterinary Science, University of Bristol, UK;Electronics and Computer Science, University of Southampton, UK

  • Venue:
  • IPAW'12 Proceedings of the 4th international conference on Provenance and Annotation of Data and Processes
  • Year:
  • 2012

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Abstract

The concept of executable documents is attracting growing interest from both academics and publishers since it is a promising technology for the the dissemination of scientific results. Provenance is a kind of metadata that provides a rich description of the derivation history of data products starting from their original sources. It has been used in many different e-Science domains and has shown great potential in enabling reproducibility of scientific results. However, while both executable documents and provenance are aimed at enhancing the dissemination of scientific results, little has been done to explore the integration of both techniques. In this paper, we introduce the design and development of Deep, an executable document environment that generates scientific results dynamically and interactively, and also records the provenance for these results in the document. In this system, provenance is exposed to users via an interface that provides them with an alternative way of navigating the executable document. In addition, we make use of the provenance to offer a document rollback facility to users and help to manage the system's dynamic resources.