Storygraph: Telling Stories from Spatio-temporal Data

Shrestha, Ayush; Zhu, Ying; Miller, Ben; Zhao, Yi

doi:10.1007/978-3-642-41939-3_68

Cited by 12 publications

(10 citation statements)

References 15 publications

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“…The space-time cube [24] maps time to a 3D axis vertically, resulting in a 3D trajectory for time series datasets. As the storygraph [25], it maps x and y coordinates of space to two vertical axes and time to the horizontal axis, which can show trends in time series datasets. This paper provides a cartographic method to encode the time component of spatio-temporal data.…”

Section: Methods and Datamentioning

confidence: 99%

An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China

Zhang

et al. 2017

Atmosphere

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In recent years, main cities in China have been suffering from hazy weather, which is gaining great attention among the public, government managers and researchers in different areas. Many studies have been conducted on the topic of urban air quality to reveal different aspects of the air quality problem in China. This paper focuses on the visualization problem of the big air quality monitoring data of all main cities on a nationwide scale. To achieve the intuitive visualization of this dataset, this study develops two novel visualization tools for multi-granularity time series visualization (timezoom.js) and a dynamic symbol declutter map mashup layer for thematic mapping (symadpative.js). With the two invented tools, we develops an interactive web map visualization application of urban air quality data of all main cities in China. This application shows us significant air pollution findings at the nationwide scale. These results give us clues for further studies on air pollutant characteristics, forecasting and control in China. As the tools are invented for general visualization purposes of geo-referenced time series data, they can be applied to other environmental monitoring data (temperature, precipitation, etc.) through some configurations.

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Section: Methods and Datamentioning

confidence: 99%

An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China

Zhang

et al. 2017

Atmosphere

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“…For disease spreading, this encoding can be used to show contacts in the same ward and forms a key part of our approach. Research in storyline visualization has focused on optimizing the compactness of storyline visualizations (either automatic or users-assisted) [4,23,37,47,48,51,61,62,67,68], reducing crossings [25,32,70,79], plotting approaches [60], combining storylines with event-based methods [3], genealogical data [31], streaming and dynamic data [66,81], and contacts between living things or actors exhibiting similar behavior [52]. Reda et al [52] is the closest approach to ours, but it needs to consider all contacts in the storyline.…”

Section: Related Workmentioning

confidence: 99%

In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals

Baumgartl

Petzold

Wunderlich

et al. 2021

IEEE Trans. Visual. Comput. Graphics

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“…Overloading users with an excessively comprehensive representation (by for example adding a third spatial dimension) does not necessarily boost analysis, especially when considering temporal dimension concurrently. The authors showed an interesting concept of space and time cubes to extract development of localization distribution of phenomena over time, but they concluded that most of the times simpler 2D time visuals serve better [ 43 ]. It is somehow in line with our expectations about the specific role of combined 2D-spatial-temporal visuals that could be served in the case of ECT data analysis.…”

Section: Specificity Of Ect Measurement Datamentioning

confidence: 99%

Interactive Timeline Approach for Contextual Spatio-Temporal ECT Data Investigation

Romanowski

Chaniecki

Koralczyk

et al. 2020

Sensors

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This paper presents a novel approach to a complex process of electrical capacitance tomography (ECT) measurement data analysis. ECT is frequently employed for non-invasive monitoring of industrial process phenomena. Proposed methodology is based on the premeditated integration of the spatial and temporal relations inherent in the measurement records into the workflow of the analysis procedure. We propose a concept of interactive timeline that enables arranging data visualization according to the user’s current focus along the process of analysis. We evaluated the proposed method using a prototype system in a task-based user study conducted with a group of domain experts. The evaluation is based on gravitational silo flow measurement datasets. Proposed prototype system enables diverse data manipulation in a more natural way allowing the user to switch back and forth between space and time domains along the data analysis trail. Experiments with the prototype system showed that the accuracy and completion times have significantly improved in comparison to the performance measured in the baseline condition. Additionally, the participants reported decreased physical load with improved efficiency measured with NASA task load index. Finally, a short discussion coupled with directions for the future of interactive spatio-temporal ECT measurement data analysis conclude the paper.

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Storygraph: Telling Stories from Spatio-temporal Data

Cited by 12 publications

References 15 publications

An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China

An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China

In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals

Interactive Timeline Approach for Contextual Spatio-Temporal ECT Data Investigation

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