ccNetViz: a WebGL-based JavaScript library for visualization of large networks

Saska, Aleš; Tichy, David; Moore, Robert E.; Rasquinha, Achilles; Akdas, Caner; Zhao, Xiaodong; Fabbri, Renato; Jeličić, Ana; Grover, G. K.; Jotwani, Himanshu; Shadab, Mohamed; Helikar, Resa; Helikar, Tomáš

doi:10.1093/bioinformatics/btaa559

Cited by 5 publications

(6 citation statements)

References 7 publications

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“…WebSockets are used for back-end and front-end communication. Examples of works that exploit WebGL to produce visualizations of large graphs include [7], [12], [17], [22].…”

Section: B Web-based Visualizationmentioning

confidence: 99%

“…ccNetViz [22] is an open-source WebGL-based JavaScript library for network visualization. It supports animation features (nodes and links).…”

Section: A Tools In Literaturementioning

confidence: 99%

“…Graphistry is a commercial graph-based analysis tool. It supports WebGL acceleration and provides a Python library called PyGraphistry 22 which acts as a client to extract, transform, and load graphs into Graphistry. An alternative Graphistry client is the GraphistryJS JavaScript library 23 .…”

Section: B Open Toolsmentioning

confidence: 99%

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Dash Sylvereye: A Python Library for Dashboard-Driven Visualization of Large Street Networks

Garcia-Robledo,

Zangiabady

2023

IEEE Access

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State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support simultaneously polylines for edges, navigable maps, GPU-accelerated rendering, interactivity, and the means for visualizing multivariate data. To fill this gap, the present paper presents Dash Sylvereye: a new Python library to produce interactive visualizations of primal street networks on top of tiled web maps. Thanks to its integration with the Dash framework, Dash Sylvereye can be used to develop web dashboards around temporal and multivariate street data by coordinating the various elements of a Dash Sylvereye visualization with other plotting and UI components provided by the Dash framework. Additionally, Dash Sylvereye provides convenient functions to easily import OpenStreetMap street topologies obtained with the OSMnx library. Moreover, Dash Sylvereye uses WebGL for GPU-accelerated rendering when redrawing the road network. We conduct experiments to assess the performance of Dash Sylvereye on a commodity computer when exploiting software acceleration in terms of frames per second, CPU time, and frame duration. We show that Dash Sylvereye can offer fast panning speeds, close to 60 FPS, and CPU times below 20 ms, for street networks with thousands of edges, and above 24 FPS, and CPU times below 40 ms, for networks with dozens of thousands of edges. Additionally, we conduct a performance comparison against two state-ofthe-art street visualization tools. We found Dash Sylvereye to be competitive when compared to the stateof-the-art visualization libraries Kepler.gl and city-roads. Finally, we describe a web dashboard application that exploits Dash Sylvereye for the analysis of a SUMO vehicle traffic simulation.

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“…WebSockets are used for back-end and front-end communication. Examples of works that exploit WebGL to produce visualizations of large graphs include [7], [12], [17], [22].…”

Section: B Web-based Visualizationmentioning

confidence: 99%

“…ccNetViz [22] is an open-source WebGL-based JavaScript library for network visualization. It supports animation features (nodes and links).…”

Section: A Tools In Literaturementioning

confidence: 99%

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Dash Sylvereye: A Python Library for Dashboard-Driven Visualization of Large Street Networks

Garcia-Robledo,

Zangiabady

2023

IEEE Access

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show abstract

“…WebSockets are used for back-end and front-end communication. Examples of works that exploit WebGL to produce visualizations of large graphs include [7], [12], [17], [22].…”

Section: B Web-based Visualizationmentioning

confidence: 99%

“…react-force-graph is implemented as a React library. Its graph renderer is based on ShaderMaterial from the Three.js 3D JavaScript library 22 . It supports both 2D and 3D graph rendering.…”

Section: ) Gpu-accelerated Toolsmentioning

confidence: 99%

Dash Sylvereye: A WebGL-powered Library for Dashboard-driven Visualization of Large Street Networks

Garcia‐Robledo¹,

Zangiabady²

2021

Preprint

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State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support simultaneously polylines for edges, navigable maps, GPU-accelerated rendering, interactivity, and the means for visualizing multivariate data. The present paper presents Dash Sylvereye: a new Python library to produce interactive visualizations of primal street networks on top of tiled web maps to fill this gap. Dash Sylvereye can render large street graphs in commodity computers by exploiting WebGL for GPU acceleration. Dash Sylvereye also provides convenient functions to easily import OpenStreetMap street topologies obtained with the OSMnx library. Thanks to its integration with the Dash framework, Dash Sylvereye can be used to develop web dashboards around temporal and multivariate street data by coordinating the various elements of a Dash Sylvereye visualization with other plotting and UI components provided by Dash. We conduct experiments to assess the performance of Dash Sylvereye on a commodity computer in terms of animation CPU time and frames per second. To further illustrate the features of Dash Sylvereye, we also describe a web dashboard application that exploits Dash Sylvereye for the analysis of a SUMO vehicle traffic simulation.

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A Comprehensive State-of-the-Art Survey on Data Visualization Tools: Research Developments, Challenges and Future Domain Specific Visualization Framework

et al. 2022

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Data visualization is a powerful skill for the demonstration of meaningful data insights in an interactive and effective way. In this survey article, we collected 70 articles from last five years (2017)(2018)(2019)(2020)(2021)(2022) to identify, classify, and investigate the various scopes, aspects and theories of data visualization. We also investigated the powerful applications of data visualization in various domains and fields such as visualization apps for health sector, Internet of things (IoTs), business dashboards, urban traffic management, smart buildings and environmental data visualization. However, after thorough investigation and classification, we conclude that, a comprehensive study is still missing about interactive, effective and efficient data visualization survey explaining basic current state-of-the-art best interactive visualization techniques, webbased tools and platforms, best performance theories, data structures and algorithms. In this survey article, we perform a thorough investigation to fill the gap on theoretical, analytical, statistical models and techniques for improving the performance of visualization. Current primary and domain specific future challenges are also reviewed, and related future research directions and opportunities are recommended. 13 14 ''Interactive'' and ''Web-based'' are the most searched key-42 words during journals analysis process.43 A. TAXONOMY OF DATA VISUALIZATION ARTICLES 44 The taxonomy of data visualization is laborious task. Since, 45 several data visualization techniques, tools and platforms are 46 available to generate effective and interactive visualization. 47 However, in this survey, we classify data visualization with 48 respect to various scopes and applications where advanced 49 and interactive visualization techniques are still required to 50 make better informed decisions. In the first stage, this sur-51 vey collects 70 articles from last five years (2017-2022) 52 to identify the various scopes, aspects and application of 53 data visualization. We divide the 65 articles into 7 different 54 scopes. We also classify these articles according to their 55 domain research and approaches. The contribution of each 56 article has been highlighted and cited in the Table 1. In this 57 initial stage, this survey discusses the various aspects of 58 7 scopes. In Scope-1, the techniques to handling of various 59 types of data, graphs, colours interaction and its integration 60 are discussed. In Scope-2, the focus is on the data mining 61 networks, environment and structure. In Scope-3, the role of 62 decision-making techniques in data visualization is empha-63 sised. In Scope-4, data visualization for big data and its 64 emerging applications are analysed. Scope-5 shares the visu-65 alization competencies in data security. In Scope-6, the key 66 role of statistical analysis for visualization is explored. In the 67 final Scope-7, various applications are reviewed to check 68 the performance of visualization in specific domain. The 69 contribution of each sco...

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ccNetViz: a WebGL-based JavaScript library for visualization of large networks

Cited by 5 publications

References 7 publications

Dash Sylvereye: A Python Library for Dashboard-Driven Visualization of Large Street Networks

Dash Sylvereye: A Python Library for Dashboard-Driven Visualization of Large Street Networks

Dash Sylvereye: A WebGL-powered Library for Dashboard-driven Visualization of Large Street Networks

A Comprehensive State-of-the-Art Survey on Data Visualization Tools: Research Developments, Challenges and Future Domain Specific Visualization Framework

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