Analyzing Spatiotemporal Anomalies through Interactive Visualization
Abstract
:1. Introduction
2. Related Work
3. Spatiotemporal Data Analysis and Visualization
3.1. System Overview
3.2. Anomaly Bars Visualization
3.3. Normalization of Bar Heights
Algorithm 1 Bar height normalization using min-max (L). |
Require: : list of raw data records; includes longitudes, latitudes and values |
Ensure: : list of normalized bar heights. |
(L) |
for do |
if then |
× |
else |
× |
end if |
end for |
return N |
3.4. GridScan
3.5. Anomaly Grids Visualization
3.6. Interaction and Trend Presentation
3.7. Color Encoding Model
3.8. Spatiotemporal Anomaly Analysis
4. Evaluation
4.1. Case Study: Corporate Computer Networks
4.1.1. Data Process and Analysis
4.1.2. Number of Online Machines
4.1.3. Number of Connections
4.1.4. Policy Status
4.2. Case Study: Environmental Quality
4.2.1. Data Process and Visualization
PM 2.5 (China) μg/m 24 h Average | Level Description | Bar Color |
---|---|---|
0–35 | Excellent | Dark blue |
35–75 | Good | Blue |
75–115 | Slightly polluted | Green |
115–150 | Lightly Polluted | Yellow |
150–250 | Moderately polluted | Orange |
250+ | Heavily polluted | Red |
4.2.2. Analysis
5. Conclusions and Further Work
Acknowledgements
Author Contributions
Conflicts of Interest
References
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Zhang, T.; Liao, Q.; Shi, L.; Dong, W. Analyzing Spatiotemporal Anomalies through Interactive Visualization. Informatics 2014, 1, 100-125. https://doi.org/10.3390/informatics1010100
Zhang T, Liao Q, Shi L, Dong W. Analyzing Spatiotemporal Anomalies through Interactive Visualization. Informatics. 2014; 1(1):100-125. https://doi.org/10.3390/informatics1010100
Chicago/Turabian StyleZhang, Tao, Qi Liao, Lei Shi, and Weishan Dong. 2014. "Analyzing Spatiotemporal Anomalies through Interactive Visualization" Informatics 1, no. 1: 100-125. https://doi.org/10.3390/informatics1010100
APA StyleZhang, T., Liao, Q., Shi, L., & Dong, W. (2014). Analyzing Spatiotemporal Anomalies through Interactive Visualization. Informatics, 1(1), 100-125. https://doi.org/10.3390/informatics1010100