Article in the Flowing Data blog by Nathan Yau, which addresses the predicted rise of the "data scientist" (someone who can take information & visualize/ present it a simple way)
Review Article by Robert Kosara (Eager Eyes blog), comparing the qualities & aspects of the 2 social visualization websites, Swivel & Many Eyes.org
Short Article by Robert Kosara (Eagle Eyes blog) about the shift in users of Visualization
Article by Christian Marc Schmidt in Form follows Behavior blog on how every visualization is defined by a hypothesis on the part of the author.
Article by Christian Marc Schmidt (Forms Follows Behavior) on data visualization, art & point of view.
Summary of a very heavy paragraph:
1. Visualizations are subjective translations
2. Visualizations are metaphorical (indirect meanings) when viewed with its context
3. Metaphors translate actual data into a visual concept
4. Therefore, visualization itself is always up to the nature of the translation/ metaohor.
Accuracy matters in the meaning of data - needs to be accepted regardless of presentation
Does this mean the accuracy doesn't matter? Sounds like letting the data speak for itself, in spite of how it is presented
"Own meaning" - can be/ seems very subjective - suggests a high level of expertise needed (see analogy in previous sentences)
What is "directionally-correct"? Does that mean the results of the analytics will be dependent on thr situatuion/ context?
Not just the data itself, or the accuracy, or the presentation, or the context it is used in - also the status & personality of the presenter. Subjective factor.
Quality of data/ methodolgy is SEPARATE from results/ implications
Need for visual analytics software to:
(A) Reach a broader market OR (B) have a more active role in daily life.
Visual analytics still a closed maeket? Still a high expertise specialty?
Analytics companies view themselves as different from "traditional" business analytical means. NOTE: interesting use of adjectives for description.
Turned out to all be assumptions
Visual analytics can be applied to the more "normal" problems to make it more approachble & less elite.
Tackle the repetitive/ necessary tasks first before proceeding onto more complex data.
Advice to tackle the smaller/ more basic sets (Excel) of data, instead of the larger ones.
Does that mean the larger the data sets, the more specialized the task becomes.
No need for extensive, new visualizations. Can be solved by existing diagrams, midels. Does the meaning change when new visualizations are used?
Visual analytics provide insight, but provide time-saving opportunities more
A call to decentralize the specialty of visual analytics - decentralization to the market allows analysts to develop better products & do more complex problems
Modern approaches to Data Visualization (Article)
The Power of Faceted Analytical Displays. By Stephen Few
Newspaper Article feat. Jeffery Heer on Thu, May 21, 2009.