learning-vue3 VS d3

Learning Vue 3.0

RacingBars is an open-source, light-weight (~45kb gzipped), easy-to-use, and feature-rich javascript library for bar chart race, based on D3.js.

D3.js Documentation

Honestly, I've been away from the field for quite a long time so wouldn't be up to date. But, if you want kind of a good framing of the field, how it evolved and how it's different from other kinds of visualization (like scientific) maybe start here [0]

0 - https://www.cs.purdue.edu/homes/xmt/classes/slides/CS530/Inf...

There used to be a lively research field for information visualization that studied current visualization techniques and proposed new ones to solve specific challenges -- I remember when treemaps were first introduced for example [1]. Large networks were a pretty big area of research at the time with all kinds of centrality clustering, and edge minimization techniques.

1 - https://www.google.com/search?q=treemap+visualization&tbs=im...

A few teams even tried various kind of hyperbolic representations [2,3] so that areas under local inspection were magnified under your cursor, and the rest of the hairball was pushed off to the edges of the display. But with big graphs you run into quite a few big problems very quickly like local vs. global visibility, layout challenges, etc.

2 - https://graphics.stanford.edu/papers/webviz/webviz/node2.htm...

3 - https://www.caida.org/catalog/software/walrus/

Not specifically graph related, but the best critical thinker I know of in the space is probably Edward Tufte [4]. I have some problems with a few bits of his thinking, and other than sparklines his contributions are mostly in terms of critically challenging what should be represented, why, how, and methods of interaction, his critical analysis has stayed up there as some of the best. He has a book set that's a really great collection of his thoughts.

4 - https://www.edwardtufte.com/tufte/

If you approach this problem critically, you end up at the inevitable conclusion that trying to globally visualize a massive graph in general is basically useless. Sure there are specific topologies that can be abstracted into easier to display graphs, but the general case is not conducive. It's also somewhat surprising at how small a graph can be before visualizing it gets out of hand -- maybe a few dozen nodes and edges.

I remember the U.S. DoE did some really pioneering studies in the field and produced some underappreciated experts like Thomas, Cook and Risch [5,6]. I like Risch's concepts around visualizations as formal metaphors of data. I think he's successful in defining the rigorous atomic components of visualization that you can build up from.

5 - https://ils.unc.edu/courses/2017_fall/inls641_001/books/RD_A...

6 - https://arxiv.org/pdf/0809.0884v1

One interesting artifact from all of this is that most of the research has long ago been captured and commoditized or made open source. There really isn't a market anymore for commercial visualization companies, or grant money for visualization research. D3.js [7] (and the derivatives) more or less took millions upon millions of dollars in R&D and commercial research and boiled it down into a free, open source, library that captured pretty much all of the major findings in one place. It's objectively better than anything that was on the market or in labs at the time I was in the space and it's free.

7 - https://d3js.org/

Built on Recharts, which is based on D3.

Repository: D3.js

Data Visualization Software is designed to help users create visual representations of their data. These tools are often used to create charts, graphs, and other visualizations that can help users understand their data better. Some popular Data Visualization Software includes Tableau, Power BI, and D3.js. Tableau and Power BI are both powerful data visualization tools, while D3.js is a JavaScript library for creating interactive data visualizations in the web browser. In summary, there are several types of data analysis software available, each with its own strengths and weaknesses. Statistical Analysis Systems are ideal for users who need to perform complex statistical analysis, while Business Intelligence Tools are designed to help users make better business decisions. Data Visualization Software is ideal for users who need to create visual representations of their data.

Interactive User Interface: Developing an interactive UI for visualizing the graph and its communities could make the summarization process more intuitive. Tools like D3.js or Cytoscape.js can be used to create dynamic visualizations.

Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/

d3 - very power visualization library enabling dynamic visualizations. docs