Osman, T ORCID: https://orcid.org/0000-0001-8781-2658, Shires, L, Omitola, T, Shadbolt, N and Hague, J, 2013. Investigating the use of semantic technologies in spatial mapping applications. In: 27th European Conference on Modelling and Simulation, Aalesund, Norway, 27-30 May 2013. European Council for Modeling and Simulation (ECMS). ISBN 9780956494467
Preview |
Text
216233_PubSub318-semMapApps_ECMS2013_0173.pdf Download (1MB) | Preview |
Abstract
Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend.
Item Type: | Chapter in book |
---|---|
Creators: | Osman, T., Shires, L., Omitola, T., Shadbolt, N. and Hague, J. |
Publisher: | European Council for Modeling and Simulation (ECMS) |
Date: | 2013 |
ISBN: | 9780956494467 |
Identifiers: | Number Type 10.7148/2013-0301 DOI |
Divisions: | Schools > School of Science and Technology |
Record created by: | EPrints Services |
Date Added: | 09 Oct 2015 09:51 |
Last Modified: | 09 Jun 2017 13:12 |
URI: | https://irep.ntu.ac.uk/id/eprint/3749 |
Actions (login required)
Edit View |
Statistics
Views
Views per month over past year
Downloads
Downloads per month over past year