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Spatial and temporal thinking is important not just because everything happens at some places and at some time, but because knowing where and when things are happening is key to understanding how and why they happened or will happen. Spatial data science is concerned with the representation, modeling, and simulation of spatial processes, as well as with the publication, retrieval, reuse, integration, and analysis of such space- and place-centric data.
Winter School on „Spatial Simulation Modelling“ in Salzburg (Austria), from 13. to 22. Feb. 2019
Complex problems need adequate approaches. In this winter school, you will learn how to desig[…]
The GeoSim ’18 workshop focuses on all aspects of simulation as a general paradigm to model and predict spatial systems and generate spatial data. New simulation methodologies and frameworks, not necessarily coming from the SIGSPATIAL community, are encouraged to participate. Also, this workshop is of interest to everyone who works with spatial data.