Interactive Big Data Visualization Using HTML5, JavaScript, and Bootstrap

Authors

DOI:

https://doi.org/10.66592/26sg8v45

Keywords:

big data visualization, interactive visualization, HTML5, JavaScript, Bootstrap, WebGL, Canvas, data aggregation, prefetching, event streaming, cloud computing, dashboards

Abstract

Visualization is how most people make sense of data, and the web browser is where most people now look at it. Big data strains browser-based visualization, however. Rendering millions of points can freeze a page, transferring raw data can take minutes, and interactions that do not respond within a fraction of a second break the flow of exploration. This article proposes an architecture for interactive big data visualization built on HTML5, JavaScript, and Bootstrap and backed by cloud services. The architecture combines a responsive Bootstrap layout, a rendering layer that chooses between SVG, Canvas, and WebGL according to data size, declarative specifications for linked interactive views, and a client data layer with caching and prefetching. On the server side it uses a cloud aggregation service that sends summaries rather than raw records, event-driven streaming for live data, and autonomous agents that keep the backend responsive. It also connects visual insight to action through configurable workflows. Using a design-oriented approach grounded in ten studies published between 2016 and 2025, the article sets out design techniques for rendering, data reduction, responsiveness, and accessibility. It illustrates the architecture with an insurance claims monitoring dashboard that combines tens of millions of historical records with a live claims stream. It argues that interactive big data visualization depends on moving computation to where it is cheapest and sending the browser only what it needs to draw.

Published

2026-10-01

How to Cite

Interactive Big Data Visualization Using HTML5, JavaScript, and Bootstrap. (2026). Journal of Integrated Science, Technology and Management, 2(04), 19-23. https://doi.org/10.66592/26sg8v45