One key issue in Peer Data Management Systems (PDMSs) is the heterogeneity of the peer schemas. To help matters, ontologies may be used as uniform conceptual representation of these schemas. In this work, we are working with geographic databases to be used in a PDMS. When dealing with geospatial data, specific problems with representation and usage occur. In this sense, we have developed an app...

One key issue in Peer Data Management Systems (PDMSs) is the heterogeneity of the peer schemas. To help matters, ontologies may be used as uniform conceptual representation of these schemas. In this work, we are working with geographic databases to be used in a PDMS. When dealing with geospatial data, specific problems with representation and usage occur. In this sense, we have developed an app...

The description of location using natural language is of interest for a number of research activities in geography, linguistics and cognitive science, including the development of methods for automated interpretation and generation of natural language to ease interaction with geographic information systems, as well as a number of related endeavours. For such research activities, examples of geo...

Geospatial data interoperability has been the target of major efforts by standardization bodies (e.g. OGC, ISO/TC 211) and the research community since the beginning of the 1990s. It is seen as a solution for sharing and integrating geospatial data, more specifically to solve the syntactic, schematic, and semantic as well as the spatial and temporal heterogeneities between various representatio...

Executive Summary Errors associated with geospatial data can propagate through natural-science (biologic, geographic, geologic, geospatial, and hydrologic) models that utilize raster processing, resulting in significant and spatially variable prediction uncertainty. This inherent prediction uncertainty affects how model results are interpreted by scientists, environmental regulators, resource m...

Geographical Information Systems (GIS) presents data-intensive environment for acquiring, processing and sharing geo-data among interested parties. In order to serve geographical information to users in such environment, Service Oriented Architecture (SOA) principles have gained great importance. In SOA-based systems, Information Services support the discovery and handling of these geospatial s...

Geospatial Processing, such as queries based on point-to-polyline shortest distance and point-in-polygon test, are fundamental to many scientific and engineering applications, including post-processing large-scale environmental and climate model outputs and analyzing traffic and travel patterns from massive GPS collections in transportation engineering and urban studies. Commodity parallel hard...

As access to spatial and real-time data improves, the need for appropriate software tools has become prevalent. To develop geospatial applications in this context requires an approach to software architecture that helps developers evolve their solutions in flexible ways. Two concepts are today considered reasonable here – web services and agents. This paper presents generic geospatial agents in...

Agent-based approaches have not yet been widely applied to highly complex, data intensive,large-scale information processing systems such as are found in the domain of imagery & geospatial computing. Such systems combine diverse and distributed types of imagery and geospatial data, and require collaboration from multiple experts and processing components. This paper gives a description of the d...

Data warehouses are being considered as substantial elements for decision support systems. They are usually structured according to the multidimensional paradigm, i.e. datacubes. Geospatial datacubes contain geospatial components that allow geospatial visualization and aggregation. However, the simultaneous use of multiple geospatial datacubes, which may be heterogeneous in design or content, d...