Irma Kveladze

Narrative of the annotated Space–Time Cube – revisiting a historical event

ABSTRACT The Space–Time Cube (STC) is a suitable representation to display multiple characteristics of movement data and will especially reveal temporal patterns in the data. By adding annotations to the cube’s paths and stations, the narrative of the display is enhanced. To illustrate the STC’s storytelling capabilities, a historical event, Napoleon’s crossing of the Berezina River during his Russian campaign in 1812 is presented and linked to an event in 2012 when the authors made a similar trip. Also, a set of different visual queries and their results are presented, emphasizing the STC as an alternative addition to a more extended visualization environment.

Visual analysis of speed bumps using floating car dataset

ABSTRACT The analysis of traffic movements in urban populations is important for safety measures to control speed when the presence of pedestrians is high. Most of the studies in the traffic domain are directed towards statistical analyses of speed, also to measure the physical parameters of bumps on roads, and effect of speed-calming measures. However, less is known about the effectiveness of varying intervals between speed-calming measures and their influence on the driving behaviour of vehicles from a spatio-temporal perspective. To fill this gap and understand these aspects, in this research we propose visual analytics techniques. To explore the influence of the distance between bumps on speed change behaviour of vehicles in relation to the permitted speed limit, several use case studies were selected with the close cooperation of a traffic expert. The aim was first to study the influence of the speed bumps on speeding, and then establish any connection between speed bump intervals and vehicle speeding in the selected use cases. The results of our investigation did reveal minor differences and influence of a time aspect on traffic volume and speed development. Also, differences in actual speed of the vehicles in relation to the distance of installed bumps were detected.

The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets

A GeoVisual Analytics (GVA) environment is based on highly interactive and dynamic visualization techniques intending to reveal knowledge in complex and multivariate datasets. By depicting information, these techniques amplify human capabilities and facilitate the performance of cognitive tasks for pattern recognition, decision-making or analytical reasoning. However, the question is whether those visual representations are suitable for visualization of different types of data to perform similar tasks. The limited usability studies that have been done on interactive analytical environments have failed to yield a definite answer. Therefore, this paper presents an evaluation experiment on how an interactive GVA environment can be designed that will effectively support similar task execution processes for different use cases. In the GVA environment investigated, four graphic representations of the Space-Time Cube (STC) , graphs and maps are interactively integrated to allow data manipulation from location, attribute and time perspectives for overview and detailed analysis. The results of the experiment revealed that the four visual representations in a GVA environment appear to be effective and efficient to explore different datasets with similar tasks, but require some sophistication.