Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores

Abstract

This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.

A Survey of Approaches for Event Sequence Analysis and Visualization using the ESeVis Framework

“…These typically include visual-izations that combine simple visualization types such as bar charts, pie charts or box plots with means to convey some sequential information of the event sequence data. An instance representation inspired by [33] is shown in In this case, the progression of the patients' condition through the hospital process is displayed with bar charts. These charts are commonly used as additional views to the main visualization.…”

“…Kwon et al [39] Wang et al [84] Unger et al [33] Liu et al [67] Vrotsou et al [28] Nguyen et al [7] Chen et al [70] Guo et al [66] Guo et al [68] Jin et al [41] Law et al [63] Cappers et al [85] Chen et al [43] Loorak et al [40] Unger et al [33] Xu et al [47] Krause et al [64] Xu et al [47] Jin et al Isaacs et al [86] Zeng et al [46] Xu et al [47] Chen et al [27] Bernard […”

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“…There exist visual analytics approaches supporting analyses of event sequences. Unger et al [51] find categorical event sequences with high semantic and temporal similarities. Cappers and Wijk [14] detect event sequences satisfying user-defined rules.…”

Visualizing event sequence game data to understand player’s skill growth through behavior complexity

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