Data Science

R. A. Leite, “Events analysis in visual analytics”, TU Wien, Vienna, 2021.
Author
Advisor
Co-Advisor
Abstract

The global expansion of wind energy requires robust and meaningful geographic information about its locations. Studies have shown how enriched global data on wind infrastructure can be generated using OpenStreetMap but have neglected to represent and make it analyzable using visual tools. For an accurate visual investigation, knowing which parameters can be used to characterize wind farms and which visual encodings are suitable for global and local analysis are essential. With this aim in mind, we conducted a design study that produced a dataset called the Enriched Data of Wind Farms (EDWin) and a prototype for its interactive visualization. Through a user study, we evaluated the tool's appropriateness for exploring unproven claims about wind farms from the literature and identifying specific wind farms characteristics through simplified visual encoding. The prototype enabled users to complete the tasks, but many needed help from the interviewer due to the need for an improved dynamic grouping functionality. Furthermore, interviews with wind energy experts revealed which features are relevant for the community to describe wind farms. They can be divided into technical, temporal, terrain, and weather characteristics. From those we have covered, several insights were generated, including that the worldwide predominant land cover for the installation of wind infrastructure is agricultural land and that the predominant landform is flat terrain.

Year of Publication
2023
Paper
Number of Pages
95
reposiTUm Handle
20.500.12708/177274
Publisher
TU Wien
Place Published
Vienna
DOI
10.34726/hss.2023.102920
M. Haller, “What do wind farms look like? Visualizing global wind farms”. TU Wien, Vienna, p. 95, 2023.
Master Thesis
AC16856157