Improvement of task-oriented visual interpretation of VGI points (TOVIP)

Volunteered Geographic Information (VGI) is very often generated as point data (e.g. Points of Interests, location of a photo taken). As one of the main characteristics, VGI data show an enormous volume as well as semantic and temporal heterogeneity. At a certain map scale and amount of data, this will lead to point clutters, which are not only hiding important information, but also making the map unreadable. Thus, reducing geometric and thematic clutter and improving the interpretability of static, multi-scale or multi-temporal visualizations of VGI points is a task of major relevance. Instead of looking at isolated generalization operations only, the project TOVIP – „Improvement of task-oriented visual interpretation of VGI point data” focuses on optimizing generalization workflows designed for specific high-level visual interpretation tasks, especially focusing on the identification and preservation of spatial patterns. 

Normally, generalization methods like aggregation, selection or simplification, are applied in order to overcome the aforementioned clutter problems, merging the user-generated information by reducing the amount of visible point symbols. Nevertheless, under certain conditions, these generation methods disperse spatial patterns, reducing the usability in visual presentation and exploration, especially when the interpretation of high-level patterns (e.g. hot spots, extreme values) is of interest. Therefore, the TOVIP project focuses on the optimization of generalization workflows regarding these specific visual interpretation tasks.

This research project is funded by the German Research Foundation (DFG) as part of the Priority Programme 1894 (“VGIscience”).


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