Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5841
Title: Proximal business intelligence on the semantic web
Authors: Bell, D
Nguyen, T
Keywords: Pervasive informatics;Semantic web;Business intelligence
Issue Date: 2010
Publisher: Springer
Citation: Sustainable e-Business Management: Lecture Notes in Business Information Processing, 58(3): 145-159, Jul 2010
Abstract: Ubiquitous information systems (UBIS) extend current Information System thinking to explicitly differentiate technology between devices and software components with relation to people and process. Adapting business data and management information to support specific user actions in context is an ongoing topic of research. Approaches typically focus on providing mechanisms to improve specific information access and transcoding but not on how the information can be accessed in a mobile, dynamic and ad-hoc manner. Although web ontology has been used to facilitate the loading of data warehouses, less research has been carried out on ontology based mobile reporting. This paper explores how business data can be modeled and accessed using the web ontology language and then re-used to provide the invisibility of pervasive access; uncovering more effective architectural models for adaptive information system strategies of this type. This exploratory work is guided in part by a vision of business intelligence that is highly distributed, mobile and fluid, adapting to sensory understanding of the underlying environment in which it operates. A proof-of concept mobile and ambient data access architecture is developed in order to further test the viability of such an approach. The paper concludes with an ontology engineering framework for systems of this type – named UBIS-ONTO.
Description: This is the post-print version of this article. The official version can be accessed from the link below - Copyright @ 2010 Springer.
URI: http://www.springerlink.com/content/r2001626x88v31wh/
http://bura.brunel.ac.uk/handle/2438/5841
DOI: http://dx.doi.org/10.1007/978-3-642-15141-5_12
ISBN: 978-3-642-15140-8
Appears in Collections:Dept of Computer Science Research Papers

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