Journal article

Ontology-assisted provenance visualization for supporting enterprise search of engineering and business files

Abstract:: In many large engineering enterprises, searching for files is a high-volume routine activity. Visualization-assisted search facilities can significantly reduce the cost of such activities. In this paper, we introduce the concept of Search Provenance Graph (SPG), and present a technique for mapping out the search results and externalizing the provenance of a search process. This enables users to be aware of collaborative search activities within a project, and to be able to reason about potential missing files (i.e., false negatives) more effectively. We describe multiple ontologies that enable the computation of SPGs while supporting an enterprise search engine. We demonstrate the novelty and application of this technique through an industrial case study, where a large engineering enterprise needs to make a long-term technological plan for large-scale document search, and has found the visualization-assisted approach to be more cost-effective than alternative approaches being studied.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Khan, S., Kanturska, U., Waters, T., Eaton, J., Bañares-Alcántara, R., & Chen, M. (2016). Ontology-assisted provenance visualization for supporting enterprise search of engineering and business files. Advanced Engineering Informatics, 30(2), 244–257.

MLA Style

Khan, S, et al. “Ontology-Assisted Provenance Visualization for Supporting Enterprise Search of Engineering and Business Files.” Advanced Engineering Informatics, vol. 30, no. 2, 2016, pp. 244–57.

Chicago Style

Khan, S, U Kanturska, T Waters, J Eaton, R Bañares-Alcántara, and M Chen. 2016. “Ontology-Assisted Provenance Visualization for Supporting Enterprise Search of Engineering and Business Files.” Advanced Engineering Informatics 30 (2): 244–57.
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Files:: SPG_Paper.pdf

(Preview, Accepted manuscript, pdf, 2.3MB, Terms of use)

Publisher copy:: 10.1016/j.aei.2016.04.003

Authors

+ Khan, S More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Engineering Science
Role:: Author

+ Kanturska, U More by this author

Role:: Author

+ Waters, T More by this author

Role:: Author

+ Eaton, J More by this author

Role:: Author

+ Bañares-Alcántara, R More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Engineering Science
Role:: Author

More authors...

+ Laing O’Rourke, UK More from this funder

Grant:: D.Phil. Studentship

Publisher:: Elsevier
Journal:: Advanced Engineering Informatics More from this journal
Volume:: 30
Issue:: 2
Pages:: 244-257
Publication date:: 2016-04-22
Acceptance date:: 2016-04-06
DOI:: 10.1016/j.aei.2016.04.003
ISSN:: 1474-0346

Keywords:: information visualization

provenance visualization

engineering document

enterprise search

knowledge management
Pubs id:: pubs:620325
UUID:: uuid:615aad22-4746-477b-ab19-54e58b6d315e
Local pid:: pubs:620325
Source identifiers:: 620325
Deposit date:: 2016-06-05
ARK identifier:: ark:/29072/ora_615aad224746477bab1954e58b6d315e

Terms of use

Copyright holder:: Elsevier
Copyright date:: 2016
Notes:: © 2016 Elsevier Inc. All rights reserved. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: [10.1016/j.aei.2016.04.003]

Licence:: CC Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)

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