Scalable web-embedded volume rendering

Raji, Mohammad; Hota, Alok; Huang, Jian

doi:10.1109/ldav.2017.8231850

Cited by 16 publications

(4 citation statements)

References 18 publications

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“…VegaPlus [15] proposes a similar system to automatically convert parts of the Vega transformation pipelines into SQL statements for server-side processing, albeit with slightly different design goals (notably not R3, see below). Tapestry [9] uses a similar client-server architecture to scalably embed interactive volume rendering visualizations in web pages.…”

Section: Background and Related Workmentioning

confidence: 99%

VegaFusion: Automatic Server-Side Scaling for Interactive Vega Visualizations

Kruchten¹,

Mease²,

Moritz³

2022

Preprint

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Figure 1: A generic Vega specification is automatically partitioned by the VegaFusion Planner into a runtime specification for the VegaFusion Middleware (describing operations on large datasets) and a client specification for Vega (describing the visualization of the output of these operations as well as client-side interactions). The Middleware dynamically responds to interaction signals from Vega by querying an out-of-browser, natively-compiled VegaFusion Runtime instance and relaying the results back to Vega. The pseudocode on the right illustrates a typical partition for a brushed histogram specification, including the dependencies between data and signals.

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Section: Background and Related Workmentioning

confidence: 99%

VegaFusion: Automatic Server-Side Scaling for Interactive Vega Visualizations

Kruchten¹,

Mease²,

Moritz³

2022

Preprint

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“…Taspestry can help other researchers to easily integrate their visualization into lightweight web pages. Previously, the authors developed a method for encapsulating and embedding interactive 3D volume rendering into standard web pages [147]. Particularly for scientific purposes, the incorporation of visualizations in informative websites can be a valuable addition to make research-based content more accessible to a broader audience.…”

Section: Cross Scientific Toolkits Supporting Scientific Visualizationmentioning

confidence: 99%

Modern Scientific Visualizations on the Web

Franke

Haehn

2020

Informatics

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Modern scientific visualization is web-based and uses emerging technology such as WebGL (Web Graphics Library) and WebGPU for three-dimensional computer graphics and WebXR for augmented and virtual reality devices. These technologies, paired with the accessibility of websites, potentially offer a user experience beyond traditional standalone visualization systems. We review the state-of-the-art of web-based scientific visualization and present an overview of existing methods categorized by application domain. As part of this analysis, we introduce the Scientific Visualization Future Readiness Score (SciVis FRS) to rank visualizations for a technology-driven disruptive tomorrow. We then summarize challenges, current state of the publication trend, future directions, and opportunities for this exciting research field.

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“…To visualize large data sets, prior work has either streamed subsets of the data to clients for rendering [41,42], or rendered it remotely on a server and streamed the resulting images back [12,19,[33][34][35]. Remote rendering approaches allow the application access to arbitrary compute capabilities to process massive data sets, although these approaches can face challenges with latency and cost.…”

Section: Scientific Visualization In the Browsermentioning

confidence: 99%

“…Porting the required native libraries and rewriting the application to JavaScript is a significant undertaking, and does not address the computational demands of the application. As a result, the majority of web-based scientific visualization applications rely on a backend server to perform data processing and visualization (e.g., [12,19,[33][34][35]), or to stream reduced representations of the data to reduce the demands placed on the browser (e.g., [16,29,41,42]). Using a server gives the application access to significant computational resources, at the cost of latency for users and financial cost to the developer to run the servers.…”

Section: Introductionmentioning

confidence: 99%