Abstract
This paper outlines a framework to support the demand-driven analysis of spatio-temporal data. It will support decision making involving complex, multidimensional data and addresses the following challenges: (1) the demand-driven acquisition of context data, (2) the combination of context and user data, (3) the consideration of different aspects and levels of detail on the analysis and (4) the storage and integration of analysis results for further use. The framework will provide web-services based on open standards to populate and explore multidimensional spatio-temporal structures interactively. Online Analitical Pro-cesing (OLAP) concepts will serve as model for storing and querying the data. Roaming-services will be used to update contents coming from different Spatial Data Infrastructures. Semantical descriptions will allow switching analysis operations at different levels of detail. Research questions and challenges related to the underlying model and implementation aspects will be discussed.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11915072_109.
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Ernst, V.H. (2006). Affordable Web-Based Spatio-temporal Applications for Ad-Hoc Decisions. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. OTM 2006. Lecture Notes in Computer Science, vol 4278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11915072_67
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