Towards knowledge-based integration and visualization of geospatial data using semantic web technologies*
(2018) 2018 Doctoral Consortium and Challenge at RuleML+RR, RuleML+RR-DCC 2018 In CEUR Workshop Proceedings 2204.- Abstract
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... (More)
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.
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- author
- Huang, Weiming LU
- organization
- publishing date
- 2018
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Data integration, Data visualization, Geospatial data, Ontologies, Rule-based inference, Semantic Web
- host publication
- Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018)
- series title
- CEUR Workshop Proceedings
- volume
- 2204
- conference name
- 2018 Doctoral Consortium and Challenge at RuleML+RR, RuleML+RR-DCC 2018
- conference location
- Luxembourg, Luxembourg
- conference dates
- 2018-09-20 - 2018-09-26
- external identifiers
-
- scopus:85053760210
- ISSN
- 1613-0073
- language
- English
- LU publication?
- yes
- id
- 0d8eb4eb-79eb-4c6e-9388-2454390ae50a
- alternative location
- http://ceur-ws.org/Vol-2204/paper4.pdf
- date added to LUP
- 2018-10-22 12:15:22
- date last changed
- 2022-01-31 06:24:51
@inproceedings{0d8eb4eb-79eb-4c6e-9388-2454390ae50a,
abstract = {{<p>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.</p>}},
author = {{Huang, Weiming}},
booktitle = {{Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018)}},
issn = {{1613-0073}},
keywords = {{Data integration; Data visualization; Geospatial data; Ontologies; Rule-based inference; Semantic Web}},
language = {{eng}},
series = {{CEUR Workshop Proceedings}},
title = {{Towards knowledge-based integration and visualization of geospatial data using semantic web technologies<sup>*</sup>}},
url = {{http://ceur-ws.org/Vol-2204/paper4.pdf}},
volume = {{2204}},
year = {{2018}},
}