From taxonomies to ontologies: formalizing generalization knowledge for on-demand mapping

Automation of the cartographic design process is central to the delivery of bespoke maps via the web. In this paper, ontological modeling is used to explicitly represent and articulate the knowledge used in this decision-making process. A use case focuses on the visualization of road traffic accident data as a way of illustrating how ontologies provide a framework by which salient and contextual information can be integrated in a meaningful manner. Such systems are in anticipation of web-based services in which the user knows what they need, but do not have the cartographic ability to get what they want.     

Ontology-based integration of topographic data sets

The integration of topographic data sets is defined as the process of establishing relationships between corresponding object instances in different, autonomously produced, topographic data sets of the same geographic space. The problem of integrating topographic data sets is in finding these relationships, considering the differences in content and abstraction. A conceptual framework is developed. Components of this framework are ontologies and sets of surveying rules. New in this approach is the introduction of a reference model. A reference model belongs uniquely to the combination of topographic data sets to be integrated. The framework is tested on two topographic data sets with area instances (polygons) which have crisp and complete boundaries and are not displaced for cartographic reasons. The overall conclusion is that the ontology-based framework is feasible, if (1) there is (at least partial) knowledge of the surveying rules, and (2) the data sets can be synchronized in time. The application of this framework is most suitable for object classes with instances that are easy to identify and have a limited spatial extent (e.g., buildings).     

Framework for probabilistic geospatial ontologies

Partial knowledge about geospatial categories is important for practical use of ontologies in the geospatial domain. Degree of overlaps between geospatial categories, especially those based on geospatial actions concepts and geospatial enitity concepts, need to be specified in ontologies. Conventional geospatial ontologies do not enable specification of such information, and this presents difficulties in ontology reasoning for practical purposes. We present a framework to encode probabilistic information in geospatial ontologies based on the BayesOWL approach. The approach enables rich inferences such as most similar concepts within and across ontologies. This paper presents two case studies of using road‐network ontologies to demonstrate the framework for probabilistic geospatial ontologies. Besides inferences within the probabilistic ontologies, we discuss inferences about most similar concepts across ontologies based on the assumption that geospatial action concepts are invariable. The results of such machine‐based mappings of most similar concepts are verified with mappings of concepts extracted from human subjects testing. The practical uses of probabilistic geospatial ontologies for concept matching and measuring naming heterogeneities between two ontologies are discussed. Based on our experiments, we propose such a framework for probabilistic geospatial ontologies as an advancement of the proposal to develop semantic reference systems.     

Modelling the temporal element in land information systems

Abstract

This paper considers the use of a modern programming language (Modula-2) to develop a data model for a lot-based land information system. The emphasis is on the importance of maintaining the history of the lots, and a data model is developed which incorporates the history of each lot.     

WebGIS数据组织发展研究

本文论述互联网GIS数据组织的发展状况。首先介绍了在WebGIS环境下空间数据的特点及其管理上存在的困难，并分析了目前实现WebGIS数据组织的几种技术及其优缺点，最后说明ontologies和RDF在WebGIS数据组织中的具体应用。