1. Information Visualization

2. Information Visualization (Ch. 1), Stuart K. Card, Jock D. Mackinlay, Ben Shneiderman in Readings in Information Visualization: Using Vision to Think

3. Use graphics to – communicate – think

4. Information visualization Medium that assemble data objects into pictures that reveal patterns.

6. Visualization The use of computer-supported, interactive, visual representations of data to amplify cognition The main goals of this insight are discovery, decision making, and explanation

7. Visualization Do sophisticated algorithms make visualization obsolete? – E.g. The phone example or the stock trade. Do we use visualization as a division of labor between what the computer is good at and what we’re good at? Eventually, if the goal is clear can’t we program the computer to attain the goal? – Does visualization then become unnecssesary?

8. How do you know that temperature is more important than damage location?

9. Knowledge crystallization implies visualization is the end product, rather than discovery. Is there a maximum amount of data that can be conveyed? A maximum number of variables?

10. information workspace” and “visual knowledge tools” levels; however we are lacking at utilizing “infosphere”-type visualizations. My understanding is that the infosphere level refers to visualizations which display aggregate data from the web or corporate networks for example –> essentially the “infosphere” is an alternative way to browse information across sites / information provide

11. Instead of a visualization that makes one or two points very obvious (ie. focusing on transforming the data to make in depth analysis easier), is there a way to create a visualization that makes recognizing many different vectors easy, with each one not having very much depth?

12. sense.us Voyagers and Voyeurs: Supporting Asynchronous Collaborative Information Visualization

14. Information Visualization Information visualization leverages the human visual system to improve our ability to process large amounts of data. Extends cognition or sensemaking to social process

15. Hypothesizes that doubly-linked discussion interface would make the visualization a social place Goals: – To understand emergent usage patterns ins social data analysis – To learn how well the various features of the system supported this analysiss – Extend past work with a comprehensive design for asynchronous collaboration around interactive data visualizations

16. Do people socializing spend more time in deeper analysis and asking questions?

17. Is there a difference between socializing and collaborating? – Collaborate: to work jointly with others or together especially in an intellectual endeavor – Work: to fashion or create a useful or desired product by expending labor If so, which one does this paper address?

18. In the job study, is it realistic that they have no purpose? Why do people browse if they don’t have a purpose? Are the users doing what they think the researchers expect them to do?

19. What would happen in a company if this were sales data and they needed to decide on where to market new products? Would people be less or more collaborative? If this were campaign workers deciding where to campaign?

20. Accuracy Is there wrong insight? E.g. was the operative definition correct? People said they learned something, but did they learn the “truth” or did they learn things that were “false”? Is good data visualization unbiased? – Does socializing infoviz bias? Does socializing create false gossip or wikipedia?

21. What are the next research steps?