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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/11907

Title: DEEP: a provenance-aware executable document system
Authors: Yang, Huanjia
Michaelides, Danius T.
Charlton, Chris
Browne, William J.
Moreau, Luc
Issue Date: 2012
Publisher: © Springer-Verlag
Citation: YANG, H. ... et al., 2012. DEEP: a provenance-aware executable document system. IN: Groth, P. and Frew, J. (eds.) Provenance and Annotation of Data and Processes. 4th International Provenance and Annotation Workshop, IPAW 2012, Santa Barbara, CA, USA, June 19-21, 2012, Revised Selected Papers, pp. 24–38.
Series/Report no.: Lecture Notes in Computer Science;7525
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.
Description: This is a book chapter from Provenance and Annotation of Data and Processes, Lecture Notes in Computer Science 7525 [© Springer-Verlag]. The definitive version is available at: http://dx.doi.org/10.1007/978-3-642-34222-6_3
Version: Accepted for publication
DOI: 10.1007/978-3-642-34222-6_3
URI: https://dspace.lboro.ac.uk/2134/11907
Publisher Link: http://dx.doi.org/10.1007/978-3-642-34222-6_3
ISBN: 3642342213
Appears in Collections:Book Chapters (Computer Science)

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