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[edit] Proceedings of the 2007 ACM Symposium on Applied computing (SAC)

[edit] Session: Advances in spatial and image-based information systems (ASIIS)

[edit] 2007

• Reporting leadership patterns among trajectories

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern 'one object is leading others', and discuss how such leadership patterns can be computed from a group of moving entities. The proposed definition is based on behavioural patterns discussed in the behavioural ecology literature. We also present several algorithms for computing the pattern, and they are analysed both theoretically and experimentally.

• Distortion-constrained compression of vector maps

An algorithm for lossy compression of vector maps for given error tolerance was developed. The algorithm is based on optimal polygonal approximation and dynamic quantization of vector data. A near optimal distortion-constrained quantizer with step defined by the tolerance level was constructed. The proposed algorithm performed well compared to other approaches.

• An OLAP system for network-constrained moving objects

The continued advances in mobile devices, geo-location wireless sensors and positioning technologies have led to a profusion of Moving Object (MO) data. However, conventional On-Line Analytical Processing (OLAP) systems cannot be applied to MO analysis because the position dimension evolves continuously over time. In this paper, we consider the representation of network-constrained MOs in OLAP systems and make the three following contributions: (i) We introduce a logical model to support continuous dimensions and facts. (ii) We propose an efficient data structure to index moving objects. (iii) Based on this index structure, we describe an algorithm which optimizes OLAP queries for analyzing MOs.

• Structural similarity in geographical queries to improve query answering

The paper proposes a method for query approximation in Geographic Information Systems. In particular, the problem of matching a query with imprecise or missing data is analyzed and an approach for the relaxation of query constraints is proposed. Query approximation is performed by relaxing structural constraints, according to an extension of a previous proposal for evaluating concept similarity in an ontology management system [1] inspired by the maximum weighted matching problem in bipartite graphs. In our approach, we start from a weighted hierarchy of geographical objects evaluated using WordNet, a lexical database for the English language available on the Internet. If a concept contained in a query has no match in the database, the query is approximated using a structural similarity graph that connects all geographical concepts by the lowest structural distance. The aim of the proposed methodology is to relax structural query constraints, in order to obtain meaningful answers for imprecise or missing data.

• HIS-KCWater: context-aware geospatial data and service integration

The nature of today's geographically and managerially distributed geospatial information sources makes the interoperability across different sources from different organizations difficult. The integration of real-time water quality assurance data with geographic data is even more challenging. In this paper, we present a context-aware geospatial data and service integration framework that is based on the combination of a syntactic model, a semantic model and a pragmatic model using Semantic Web technologies. This model is context-aware, with the ability to analyze existing dependencies, predict causes and effects and provide context-aware services (which information services are relevant, how to perform the services, how often they are needed, etc). As a proof of concept, we demonstrate the HIS-KCWater system for supporting users in analyzing real time watershed data, predicting the water quality using hydrologic model simulators, interpreting the results, dynamically forecasting problems and generating alerts about water quality issues.