Mark Gahegan
ABSTRACT
We describe a semantically-based Web Map Mediation Service (WMMS) that allows researchers to define, capture and reuse semantic relationships between map categories, via a set of Web Services. A map can then be viewed according to different taxonomies or legends, whose categories have been semantically related to those native to the map. Such 'mappings' or 'mediation schema' can be constructed directly between maps, or can utilise an independent 'master schema' such as an application ontology, to which map categories are aligned.
This paper explains the workings of the Mediation Service that allows users to: (i) experiment with the design of map classification schemes, (ii) explore how the use of different schemes affects what is apparent on the map and (iii) translate maps---as far as possible---from one classification scheme to another. Semantic equivalences and similarities are supported via underlying ontologies, and it is these that facilitate the merging and re-grouping of classes. Users can create their own map re-classification schemes, which can be serialized for later use. They can also create and share new versions of existing maps that have been reclassified according to the mediations that they specify.
Examples are provided of mediations to support the combined use of three different land cover maps used in New Zealand, each with a different set of base categories. The service shows promise in extending the useful life of historical data, by allowing communities to build and share schemas that re-express older map legends.
- Ahlqvist, O. 2005. Using uncertain conceptual spaces to translate between land cover categories. International Journal of Geographical Information Science. 19, 7 (2005), 831--857.Google Scholar
Cross Ref
- Andrei, M. et al. 2008. SWING: An Integrated Environment for Geospatial Semantic Web Services. The Semantic Web: Research and Applications (2008), 767--771. Google ScholarDigital Library
- Ban, H. and Ahlqvist, O. 2009. Representing and negotiating uncertain geospatial concepts -- Where are the exurban areas? Computers, Environment and Urban Systems. 33 (2009), 233--246.Google ScholarCross Ref
- Brodaric, B. and Gahegan, M. (2010). Ontology use for semantic e-Science. Semantic Web, 2010, 149~153. Google ScholarDigital Library
- Comber, A. et al. 2005. You know what land cover is but does anyone else?...an investigation into semantic and ontological confusion. International Journal of Remote Sensing. 26, 1 (2005), 223--228.Google ScholarCross Ref
- Comber, A. J. et al. 2008. Using semantics to clarify the conceptual confusion between land cover and land use: the example of "forest." Journal of Land Use Science. 3, 2--3 (2008), 185--198.Google ScholarCross Ref
- Comber, A. et al. 2004. Integrating land-cover data with different ontologies: identifying change from inconsistency. International Journal of Geographical Information Science. 18, 7 (2004), 691--708.Google ScholarCross Ref
- Davies, J., Studer, R., and Warren, P. 2006 Semantic Web Technologies: Trends and Research in Ontology-based Systems. London: John Wiley & Sons Ltd. Google ScholarDigital Library
- Fox, P., McGuinness, D. L., Cinquini, L., West, P., Garcia, J., Benedict, J. L., Middleton, D. (2009). Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience. Computers & Geosciences, 35, 4 (2009) 724--738. Google ScholarDigital Library
- Gahegan, M. and Pike, W. (2006). A situated representation of geographical information. Transactions in GIS, 10, 5, 727--749.Google ScholarCross Ref
- Gahegan, M., Luo, J., Weaver, S., Pike, W. and Banchuen, T (2009). Connecting GEON: making sense of the myriad resources, researchers and concepts that comprise a geoscience cyberinfrastructure. Computers & Geosciences, 35, 836--854. Google ScholarDigital Library
- Kavouras, M. et al. 2005. Comparing categories among geographic ontologies. Computers & Geosciences. 31, (2005), 145--154. Google ScholarDigital Library
- Lanzenberger, M., Sampson, J. AlViz - A Tool for Visual Ontology Alignment, iv, pp.430--440, Tenth International Conference on Information Visualisation (IV'06), 2006 Google ScholarDigital Library
- Lutz, M. et al. 2009. Overcoming semantic heterogeneity in spatial data infrastructures. Computers & Geosciences. 35, (2009), 739--752. Google ScholarDigital Library
- Noy, N. F. (2004) Semantic integration: A survey of ontology-based approaches. SIGMOD Record, 33, 4 (2004), 65--70. Google ScholarDigital Library
- Nyerges, T. L. 1989. Schema integration analysis for the development of GIS databases. International Journal of Geographical Information Systems, 3, 2 (1989), 153--183.Google ScholarCross Ref
- Schwering, A. 2008 Approaches to semantic similarity measurement for geo-spatial data: A Survey. Transactions in GIS 12, 1, 5--29.Google ScholarCross Ref
- Stoimenov, L., Djordjevic-Kajan, S. An architecture for interoperable GIS use in a local community environment, Computers & Geosciences, 31, 2, 211--220. Google ScholarDigital Library
- Yetongnon, K., Suwanmanee, S., Benslimane, D. Champin, P. A., A web-centric semantic mediation approach for spatial information systems, Journal of Visual Languages & Computing, Volume 17, 1, (2006) 1--24. Google ScholarDigital Library
Index Terms
- A semantic web map mediation service: interactive redesign and sharing of map legends
Recommendations
Two-Fold Service Matchmaking --- Applying Ontology Mapping for Semantic Web Service Discovery
ASWC '09: Proceedings of the 4th Asian Conference on The Semantic WebSemantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level ...
Exploiting Metrics for Similarity-Based Semantic Web Service Discovery
ICWS '09: Proceedings of the 2009 IEEE International Conference on Web ServicesSemantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong ...
Semantic enrichment for medical ontologies
The Unified Medical Language System (UMLS) contains two separate but interconnected knowledge structures, the Semantic Network (upper level) and the Metathesaurus (lower level). In this paper, we have attempted to work out better how the use of such a ...
Comments