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Large Network Renderer #229
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Hello @jingjingbic |
NRNB has been accepted as a mentoring organization for GSoC 2024. The contributor application period is March 18 – April 2. Here are some useful links: GSoC contributor guide |
Thank you so much for the info . I'll make sure to check out these resources. |
How can we communicate, here or there is any irc or discord or slack channels? @khanspers |
Hi @tausiq2003, we don't have Slack/discord/irc channels for NRNB. The best way is to communicate directly with the potential mentors here. @jingjingbic @d2fong @keiono. |
Thanks, @khanspers . Hi @jingjingbic @d2fong @keiono glad to meet you all. I am Tausiq Samantaray, currently a pre-final year student from India. So, I am just going over those resources, will message you in 2 days. And, can I contribute, to the above repos, or if I am selected then, I can contribute, Thanks. |
From my primary intuition, we have to contribute toward the large-graph-renderer right? I mean that's a javascript library. |
@tausiq2003 Yes, the library is written in TypeScript. |
Hey So in order to understand deck.gl I build a project to get familiar with the framework. |
Thanks for your interest Rohan. It looks cool! We will take a closer look of your repo and get back to you soon. |
Thank you for your feedback, I truly appreciate it. Please review the project again, as I've added more functionality to make it even more interactive for users. |
@jingjingbic @keiono @d2fong Could you please provide me your email address or another medium of communication? I would like to seek feedback from you regarding the proposal before submitting it. |
Please send an email to devs at ndexbio.org and I will reply to you. |
Background
The rise of web-based visualization tools has significantly impacted data interaction, especially in the biomedical sector. However, a major challenge persists: efficiently rendering very large networks, which often comprise 500,000 to 1 million elements, including nodes and edges. Current web visualization tools struggle with such extensive datasets, resulting in performance bottlenecks and limited user interactivity.
The "Large Network Renderer" project seeks to overcome these limitations. This JavaScript library will significantly enhance the Cytoscape Web project by enabling the effective rendering of large-scale CX networks in web browsers. Its key advantage is the capability to manage very large datasets while ensuring fluid performance and interactive user experience. Beyond Cytoscape, "Large Network Renderer" will serve as an indispensable tool for other web applications handling extensive network visualizations, like the Network Data Exchange (NDEx) and NDEX-IQuery. This endeavor is vital for the progression of web-based data analysis tools, empowering researchers to delve into large, complex datasets with newfound depth.
Goal
The objective of this project is extending the initial proof of concept already developed as a prototype. Our focus will extend to supporting a list of commonly used visual properties in this renderer. Key tasks will include:
Adding more visualization capability to the renderer
This application is built on top of the popular WebGL-based data visualization framework Deck.gl. Since this is a high-level library designed to visualize large data set, you can write the additional features without deep knowledge of WebGL low-level API.
How to Start
Interested applicants should:
Difficulty Level: Medium
Size and Length of Project
Skills
Public Repository
Potential Mentors
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