TY - GEN
T1 - Guided analysis of hurricane trends using statistical processes integrated with interactive parallel coordinates
AU - Steed, Chad A.
AU - Swan, J. Edward
AU - Jankun-Kelly, T. J.
AU - Fitzpatrick, Patrick J.
PY - 2009
Y1 - 2009
N2 - This paper demonstrates the promise of augmenting interactive multivariate representations with information from statistical processes in the domain of weather data analysis. Statistical regression, correlation analysis, and descriptive statistical calculations are integrated via graphical indicators into an enhanced parallel coordinates system, called the Multidimensional Data eXplorer (MDX). These statistical indicators, which highlight significant associations in the data, are complemented with interactive visual analysis capabilities. The resulting system allows a smooth, interactive, and highly visual workflow. The system's utility is demonstrated with an extensive hurricane climate study that was conducted by a hurricane expert. In the study, the expert used a new data set of environmental weather data, composed of 28 independent variables, to predict annual hurricane activity. MDX shows the Atlantic Meridional Mode increases the explained variance of hurricane seasonal activity by 7-15% and removes less significant variables used in earlier studies. The findings and feedback from the expert (1) validate the utility of the data set for hurricane prediction, and (2) indicate that the integration of statistical processes with interactive parallel coordinates, as implemented in MDX, addresses both deficiencies in traditional weather data analysis and exhibits some of the expected benefits of visual data analysis.
AB - This paper demonstrates the promise of augmenting interactive multivariate representations with information from statistical processes in the domain of weather data analysis. Statistical regression, correlation analysis, and descriptive statistical calculations are integrated via graphical indicators into an enhanced parallel coordinates system, called the Multidimensional Data eXplorer (MDX). These statistical indicators, which highlight significant associations in the data, are complemented with interactive visual analysis capabilities. The resulting system allows a smooth, interactive, and highly visual workflow. The system's utility is demonstrated with an extensive hurricane climate study that was conducted by a hurricane expert. In the study, the expert used a new data set of environmental weather data, composed of 28 independent variables, to predict annual hurricane activity. MDX shows the Atlantic Meridional Mode increases the explained variance of hurricane seasonal activity by 7-15% and removes less significant variables used in earlier studies. The findings and feedback from the expert (1) validate the utility of the data set for hurricane prediction, and (2) indicate that the integration of statistical processes with interactive parallel coordinates, as implemented in MDX, addresses both deficiencies in traditional weather data analysis and exhibits some of the expected benefits of visual data analysis.
KW - Climate study
KW - Correlation
KW - Interaction
KW - Multivariate data
KW - Regression
KW - Statistical analysis
KW - Visual analytics
UR - http://www.scopus.com/inward/record.url?scp=72849116335&partnerID=8YFLogxK
U2 - 10.1109/VAST.2009.5332586
DO - 10.1109/VAST.2009.5332586
M3 - Conference contribution
AN - SCOPUS:72849116335
SN - 9781424452835
T3 - VAST 09 - IEEE Symposium on Visual Analytics Science and Technology, Proceedings
SP - 19
EP - 26
BT - VAST 09 - IEEE Symposium on Visual Analytics Science and Technology, Proceedings
T2 - VAST 09 - IEEE Symposium on Visual Analytics Science and Technology
Y2 - 12 October 2009 through 13 October 2009
ER -