Lune

CHI2026顶会

Anu.js: Accelerating Web-based Immersive Analytics

David Saffo, Benjamin Lee, Feiyu Lu, Cheng Yao Wang, Blair MacIntyre

2026年份
1被引次数

摘要

We present Anu.js, a toolkit for web-based immersive analytics (IA). The IA design space is vast, multi-faceted, and everchanging, challenging development in the absence of robust authoring support. The web is a popular platform for visualization applications, research, and teaching, and by leveraging the benefits of web technologies and adopting imperative authoring paradigms we can achieve the necessary expressiveness, compatibility, and ergonomics to support IA research and development. Anu.js adapts D3’s data-binding model to 3D contexts, granting fine-grained control over the creation, representation, animation, performance, and interaction of 3D scene-graphs. Additionally, Anu.js offers declarative prefabs to support common visualization elements and interactions, and synergizes with popular visualization libraries which allows developers to leverage these proven utilities. We demonstrate Anu.js’s potential through our diverse example gallery, expert evaluation, and potential future applications. Through this, Anu.js empowers developers in accelerating the creation of novel and bespoke visualizations for immersive web-based applications.

问问这篇 Paper

问问你的智能体。

Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。

可以从这些问题问起

智能体调用

Lunesearch_papers

在 Lune 里问

免费开始,无需绑卡

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖