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abstract

A Framework for Interactive Exploration of Clusters in Massive Data Using 3D Scatter Plots and WebGL

Published: 09 November 2020 Publication History

Abstract

This paper presents a rendering framework for the visualization of massive point datasets in the web. It includes highly interactive point rendering, cluster visualization, basic interaction methods, and importance-based labeling, while being available for both mobile and desktop browsers. The rendering style is customizable, as shown in figure 1. Our evaluation indicates that the framework facilitates interactive visualization of tens of millions of raw data points even without dynamic filtering or aggregation.

References

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Sören Discher, Rico Richter, and Jürgen Döllner. 2018. A Scalable WebGL-Based Approach for Visualizing Massive 3D Point Clouds Using Semantics-Dependent Rendering Techniques. In Proceedings of the 23rd International ACM Conference on 3D Web Technology(Web3D ’18). Article 19, 9 pages.
[2]
Niklas Elmqvist and Philippas Tsigas. 2008. A Taxonomy of 3D Occlusion Management for Visualization. IEEE Transactions on Visualization and Computer Graphics 14, 5(2008), 1095–1109.
[3]
Peter Hofer, Lisa Perkhofer, and Albert Mayr. 2020. Interaktive Big Data Visualisierungen – Potenzial für das Management Reporting. Springer Fachmedien Wiesbaden, Wiesbaden, 159–187.
[4]
Daniel A. Keim. 2001. Visual Exploration of Large Data Sets. Commun. ACM 44, 8 (Aug. 2001), 38–44.
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Lars Linsen, Tran Long, Paul Rosenthal, and Stephan Rosswog. 2008. Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization. IEEE transactions on visualization and computer graphics 14 (11 2008), 1483–90.
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Arko Lucieer and Menno-Jan Kraak. 2004. Alpha-shapes for visualizing irregular-shaped class clusters in 3D feature space for classification of remotely sensed imagery. In Visualization and Data Analysis 2004, Vol. 5295. International Society for Optics and Photonics, SPIE, 201 – 211.
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Laura Po, Nikos Bikakis, Federico Desimoni, and George Papastefanatos. 2020. Linked Data Visualization: Techniques, Tools, and Big Data. Synthesis Lectures on Semantic Web: Theory and Technology 10, 1(2020), 1–157.
[8]
Markus Schütz. 2016. Potree: Rendering Large Point Clouds in Web Browsers. Ph.D. Dissertation.
[9]
Edward Wegman. 1995. Huge Data Sets and the Frontiers of Computational Feasibility. Journal of Computational and Graphical Statistics 4 (07 1995).

Cited By

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  • (2023)Study on Rainfall Runoff Prediction of Basin Based on Digital TwinProceedings of the 2023 15th International Conference on Machine Learning and Computing10.1145/3587716.3587811(576-583)Online publication date: 17-Feb-2023
  • (2023)Visualization of Source Code Similarity Using 2.5D Semantic Software MapsComputer Vision, Imaging and Computer Graphics Theory and Applications10.1007/978-3-031-25477-2_8(162-182)Online publication date: 2-Feb-2023
  • (2022)Hardware-accelerated Rendering of Web-based 3D Scatter Plots with Projected Density Fields and Embedded ControlsProceedings of the 27th International Conference on 3D Web Technology10.1145/3564533.3564566(1-5)Online publication date: 2-Nov-2022
  • Show More Cited By

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Published In

cover image ACM Conferences
Web3D '20: Proceedings of the 25th International Conference on 3D Web Technology
November 2020
201 pages
ISBN:9781450381697
DOI:10.1145/3424616
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 November 2020

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Author Tags

  1. WebGL
  2. cluster visualization
  3. framework
  4. massive data
  5. scatter plot

Qualifiers

  • Abstract
  • Research
  • Refereed limited

Funding Sources

  • This work has been supported by the German Federal Ministry of Education and Research (BMBF) through grant 01IS19006 (KI-Labor ITSE).
  • This work is part of the Software-DNA project, which is funded by the European Regional Development Fund (EFRE) and the State of Brandenburg (ILB).

Conference

Web3D '20
Sponsor:
Web3D '20: The 25th International Conference on 3D Web Technology
November 9 - 13, 2020
Virtual Event, Republic of Korea

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Overall Acceptance Rate 27 of 71 submissions, 38%

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Cited By

View all
  • (2023)Study on Rainfall Runoff Prediction of Basin Based on Digital TwinProceedings of the 2023 15th International Conference on Machine Learning and Computing10.1145/3587716.3587811(576-583)Online publication date: 17-Feb-2023
  • (2023)Visualization of Source Code Similarity Using 2.5D Semantic Software MapsComputer Vision, Imaging and Computer Graphics Theory and Applications10.1007/978-3-031-25477-2_8(162-182)Online publication date: 2-Feb-2023
  • (2022)Hardware-accelerated Rendering of Web-based 3D Scatter Plots with Projected Density Fields and Embedded ControlsProceedings of the 27th International Conference on 3D Web Technology10.1145/3564533.3564566(1-5)Online publication date: 2-Nov-2022
  • (2021)Software Galaxies: Displaying Coding Activitiesusing a Galaxy MetaphorProceedings of the 14th International Symposium on Visual Information Communication and Interaction10.1145/3481549.3481573(1-2)Online publication date: 6-Sep-2021

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