I wasn't 100 % sure from which angle to judge the paper: What's the intended audience?
It's dedicated to visualization developers. I'm focussing on the process of creating web-based visualizations, not on visualizations in general. That's why mapping isn't covered in detail. I'm not intending to cover many application scenarios. Just enough to get the idea.
Related: maybe this paper should cut faster to the meat and don't spend so much time explaining a methodological framework of analyzing information viz tools? How would this read as a large blog post or CT article? I'm aware that thesis have an expected format. Still, could the paper get faster to its point?
I'm afraid I can't leave that out. However, once I'm done, I'll probably publish a Substance article containing just the essentials. Deal? :)
In general, I'm missing geographical data vizualisation, mapping. I get that the paper focuses on graphing, but I'm missing at least the distinction.
Will try to make this more clear.
Narrative Viz: http://one.org/us/actnow/horn.html is a great example
Bought!
Curious: Why did you not include voronoi in network?
Mhh. I have to admit, I'm not fully aware of the use-cases of Voronoi. Is it actually suitable for encoding relationship?
The Les Miserable matrix is awesome, did you do it?
Nope, Bostock and Heer. Many of the examples are taken from there: http://portal.acm.org/ft_gateway.cfm?id=1805128&type=pdf
I'm sometimes missing the browser support angle. It is critical in practical application and the fact that canvas is not supported in IE<=8 is a biggie.
Will try to cover that.
Not sure I follow here: (3.4.5) The implementation of a node forms a single instruction that operates on multiple data items. This means that visualizations can deal with any number of data items, which is particularly interesting in the context of Information Visualization.
Will be fixed.
I love Flot - it's a great micro library and maybe worth a mention. We use the crap out of it.
Flot is dedicated to charting. I've put my focus on more generalized libs, that allow full customization (instead of parameterization of predefined Charts. See 3.2 - Visualization Systems)
In practical terms, where do you see the sort of platform independence that uv.js offers come into play?
Basically the renderer can be switched out. WebGL with an orthogonal view would make a lot of sense (in terms of performance optimization). Also porting it to Javascript hosted desktop environments, such as Plask would be possible. The point here is that for retargeting the specification syntax doesn't need to be touched.
Is that true? SVG 'performs better' than HTML5 canvas as in 'faster'? Which browsers? 2008 is a little while ago. "They found that SVG performs better than HTML5 Canvas, given that the number of objects do not become too high."
Yeah that's tipsy. Will remove that.
This is contradicting the benchmarks (emphasis added): While D3’s expressive syntax and deep integration with developer tools is suitable for many visualization tasks, Unveil.js may be a good fit when it comes to high performance rendering involving a high number of animated objects (such as particle systems) or approaching complex visualization tasks through object-oriented abstraction
Mhh true. I was surprised SVG performs that fast in Chrome/Safari. At least for that particular test.
I love the comparison, not sure how i feel about the scoring especially as the author's sofware wins :) I'd just leave it out and add a comparison table and use symbols instead of numbers (full dot, empty dot, dash, like when you buy a car?).
Yeah that's tricky indeed. I personally don't like the quantification of qualitative evaluations. However, this time it needs to be scientific - you know. ;) Also, I wouldn't consider Unveil.js more advanced than D3. Unveil.js is still experimental and currently not under active development. This is rather a clean-room evaluation emphasizing on the main characteristics of both libs. Maybe I should make this more clear.
- There's a "constrast"
Fixed.
- "HTML5 is ahead" should be "HTML5 Canvas is ahead"
Unclear:
This principle is referred to as The Information Seeking Mantra and serves as a starting point for creating visualizations. Based on that, Shneiderman also proposes a Type by Task Taxonomy (TTT) of Information Visualizations. He assumes, that users are viewing collections of items, each having multiple attributes.
Based on Shneiderman’s work, the following sections introduce Tasks and Data Types, complete with illustrative examples
The jump from "TTT" to "Tasks and Data Types" is not clear - how do these terminologies connect?
Will be fixed.
And thanks a whole lot! :)