cpmViz: A Web-Based Visualization Tool for Uncertain Spatiotemporal Data
(2019) 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) p.140-141- Abstract
- The goal of the VAST challenge 2019 Mini Challenge 2 was to visualize radioactive contaminations measured by mobile and static sensors and their changes over time, allowing city officials to determine the severity of the leakage at the city's nuclear power plant. We propose cpmViz, a web-based tool that allows for interactive data exploration of the sensor readings in both of the spatial and temporal dimensions. The tool consists out of three views that are connected via linking and scrolling. We visualize static sensor uncertainty by introducing Voronoi cells to illustrate how much space is covered by an individual measurement unit. For mobile sensors, we showcase their activity periods and introduce the concept of sensor streaks as... (More)
- The goal of the VAST challenge 2019 Mini Challenge 2 was to visualize radioactive contaminations measured by mobile and static sensors and their changes over time, allowing city officials to determine the severity of the leakage at the city's nuclear power plant. We propose cpmViz, a web-based tool that allows for interactive data exploration of the sensor readings in both of the spatial and temporal dimensions. The tool consists out of three views that are connected via linking and scrolling. We visualize static sensor uncertainty by introducing Voronoi cells to illustrate how much space is covered by an individual measurement unit. For mobile sensors, we showcase their activity periods and introduce the concept of sensor streaks as periods of uninterrupted recordings as a temporal uncertainty measure. As for spatial uncertainty, we color individual districts based on the amount of data that was recorded inside the user's selected time window. Using our system, we were able to easily spot major events like the city's initial earthquake in the sensor readings. Certain southern districts are clearly visible as areas of concern that we consider in need of more static sensors. Furthermore, we were also able to identify static as well as moving contaminations. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/30af820b-42a9-453f-8430-e58a40be962f
- author
- Nagel, Fabian ; Castiglia, Giuliano ; Ademaj, Gemza LU ; Buhmuller, Juri ; Schlegel, Udo and Keim, Daniel
- publishing date
- 2019-09-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2019 IEEE Conference on Visual Analytics Science and Technology (VAST)
- pages
- 140 - 141
- conference name
- 2019 IEEE Conference on Visual Analytics Science and Technology (VAST)
- conference dates
- 2019-10-20 - 2025-12-25
- external identifiers
-
- scopus:85081058251
- ISBN
- 978-1-7281-2284-7
- DOI
- 10.1109/VAST47406.2019.8986941
- language
- English
- LU publication?
- no
- id
- 30af820b-42a9-453f-8430-e58a40be962f
- date added to LUP
- 2025-12-15 11:18:08
- date last changed
- 2025-12-16 04:00:49
@inproceedings{30af820b-42a9-453f-8430-e58a40be962f,
abstract = {{The goal of the VAST challenge 2019 Mini Challenge 2 was to visualize radioactive contaminations measured by mobile and static sensors and their changes over time, allowing city officials to determine the severity of the leakage at the city's nuclear power plant. We propose cpmViz, a web-based tool that allows for interactive data exploration of the sensor readings in both of the spatial and temporal dimensions. The tool consists out of three views that are connected via linking and scrolling. We visualize static sensor uncertainty by introducing Voronoi cells to illustrate how much space is covered by an individual measurement unit. For mobile sensors, we showcase their activity periods and introduce the concept of sensor streaks as periods of uninterrupted recordings as a temporal uncertainty measure. As for spatial uncertainty, we color individual districts based on the amount of data that was recorded inside the user's selected time window. Using our system, we were able to easily spot major events like the city's initial earthquake in the sensor readings. Certain southern districts are clearly visible as areas of concern that we consider in need of more static sensors. Furthermore, we were also able to identify static as well as moving contaminations.}},
author = {{Nagel, Fabian and Castiglia, Giuliano and Ademaj, Gemza and Buhmuller, Juri and Schlegel, Udo and Keim, Daniel}},
booktitle = {{2019 IEEE Conference on Visual Analytics Science and Technology (VAST)}},
isbn = {{978-1-7281-2284-7}},
language = {{eng}},
month = {{09}},
pages = {{140--141}},
title = {{cpmViz: A Web-Based Visualization Tool for Uncertain Spatiotemporal Data}},
url = {{http://dx.doi.org/10.1109/VAST47406.2019.8986941}},
doi = {{10.1109/VAST47406.2019.8986941}},
year = {{2019}},
}