ONTOLOGIES IN RISK MANAGEMENT
M. Konecny, T. Reznik
The problem of syntactic heterogeneity among geographic datasets emerged as a result of native data formats and the development of monolithic and proprietary systems. Although SDIs provide the basis for syntactic interoperability the usability of information that is created in one context has often limited use in other contexts. One important reason for this is semantic heterogeneity. This problem could be solved using ontologies and their implementation in the context of cartographic visualization.
The first step is to identify and analyze existing problems caused by semantic heterogeneity in several risk management use cases. Based on results of this analysis, the project focuses on developing methods for overcoming these problems during service discovery, composition and execution. The viability of the developed approaches will be illustrated by prototypically implemented web services for intelligent search and semantic translation and by applying them to the use cases. This paper describes the basis of the context cartographic visualization and also ontologies with focus on geographic ontologies. There is a need for explicit specification of ontology that supports understanding, sharing and exchange between different users and databases. The basic requirement is the possibility of ontology formulation in other languages.
A key aim in geographic ontology is the development of a search engine that displays some intelligence in the interpretation of geographical terminology. The assumption is that people may wish to find information about something that relates to somewhere. It is also proposed that ontology should be used to assist in a process of metadata extraction whereby the geographical context of resources is determined for the purpose of search engine indexing as well as providing the potential to annotate a resource to improve its future geographical visibility.
One aspect of generalization concerns the semantic level of detail. In general it can be assumed that people are interested in information at different levels of semantic detail. In order to be really useful and beneficial, the ontology should therefore be able to encode geographic data at multiple levels of semantic generalization.
This research has been supported by funding from Project No. MSM0021622418 called Dynamic geovisualization in risk management.