Ontology-assisted provenance visualization for supporting enterprise search of engineering and business files. Issue 2 (April 2016)

• Record Type: Journal Article
• Authors: Khan, Saiful; Kanturska, Urszula; Waters, Tom; Eaton, James; Bañares-Alcántara, René; Chen, Min
• Is Part Of: Advanced engineering informatics. Volume 30:Issue 2(2016:Apr.)
• Page Start: 244
• Page End: 257
• Publication Date: 2016-04
• Subjects: Enterprise search -- Engineering document -- Knowledge management -- Information visualization -- Provenance visualization; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2016.04.003
• Languages: English
• ISSNs: 1474-0346

Abstract

Graphical abstract: Highlights: Large scale enterprise search activities can benefit from provenance information. An ontologies-based search engine can capture semantically-meaningful provenance information. Provenance visualization can support criteria reformulation and collaborate search activities. Visualization-assisted enterprise search can provide a cost-effective solution to large scale file search in industry. 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.