A0245
Title: Cubble: An R Package for organizing and wrangling multivariate spatio-temporal data
Authors: Huize Zhang - University of Texas at Austin (United States) [presenting]
Di Cook - Monash University (Australia)
Ursula Laa - BOKU University (Austria)
Nicolas Langrene - BNU - HKBU United International College (China)
Patricia Menendez - Monash University (Australia)
Abstract: Multivariate spatio-temporal data have a spatial component referring to the location of each observation, a temporal component recorded at regular or irregular time intervals, and multiple variables measured at each spatial and temporal value. Often, such data are fragmented, reflecting a common practice of focusing on either spatial or temporal aspects separately. This fragmentation makes it difficult to handle them coherently and comprehensively. A new data structure is introduced to facilitate the study of different portions or combinations of spatio-temporal data for exploratory data analysis. The proposed structure, implemented in the R package, cubble, organizes spatial and temporal variables as two facets of a single data object, allowing them to be wrangled separately or combined while ensuring synchronization. Examples of creating glyph maps will be provided to visualize weather station data with cubble.
