Towards knowledge-based integration and visualization of geospatial data using semantic web technologies^*

Summary, in English

Geospatial data have been pervasive and indispensable for various real-world application of e.g. urban planning, traffic analysis and emergency response. To this end, the data integration and knowledge transfer are two prominent issues for augmenting the use of geospatial data and knowledge. In order to address these issue, Semantic Web technologies have been considerably adopted in geospatial domain, and there are currently still some activates investigating the benefits brought up from the adoption of Semantic Web technologies. In this context, this paper showcases and discusses the knowledge-based geospatial data integration and visualization leveraging ontologies and rules. Specifically, we use the Linked Data paradigm for modelling geospatial data, and then create knowledge base of the visualization of such data in terms of scaling, data portrayal and geometry source. This approach would benefit the transfer, interpret and reuse the visualization knowledge for geospatial data. At the meantime, we also identified some challenges of modelling geospatial knowledge and outreaching such knowledge to other domains as future study.

• Author: Weiming Huang
• Department/s: Centre for Geographical Information Systems (GIS Centre)
• Publishing year: 2018
• Language: English
• Publication/Series: CEUR Workshop Proceedings
• Volume: 2204
• Links: http://ceur-ws.org/Vol-2204/paper4.pdf
• Document type: Conference paper
• Topic: Other Earth and Related Environmental Sciences; Information Systems
• Keywords: Data integration; Data visualization; Geospatial data; Ontologies; Rule-based inference; Semantic Web
• Conference name: 2018 Doctoral Consortium and Challenge at RuleML+RR, RuleML+RR-DCC 2018
• Conference date: 2018-09-20 - 2018-09-26
• Conference place: Luxembourg, Luxembourg
• Status: Published
• ISBN/ISSN/Other: ISSN: 1613-0073