Friday, February 29, 2008
Wednesday, February 13, 2008
Nice Review of MacBook Air
There is a nice review of MacBook Air over at cnn.com:
"And while the MacBook Air's specs are inferior to those found on the cheaper MacBook, they compare more favorably when you look at other ultraportables, where a price premium is always exacted. For instance, both the Sony VAIO TZ150 and Toshiba Portege R500 cost hundreds more than the MacBook Air and feature slower CPUs and half the RAM as the Air."
A bit later:
While most hardware vendors offer a choice of mobile broadband options, Apple continues to offer none, which is disappointing for a system so clearly meant for life away from home and office.
...
One of the biggest drawbacks of the MacBook Air is the lack of a user-replaceable battery. While most laptops will be obsolete before their batteries wear out, we are sensitive to the desire to occasionally carry an extra battery for extended field use.
Saturday, February 9, 2008
Top 5 Research Challenges for Information Visualization
Georges Grinstein at UMass just asked me what the top 5 research challenges are for the field of information visualization. I thought I'd blog my response here that I wrote up in 15min:
Georges:
About 5-6 years ago I wrote up an article that was going to be published in a software engineering magazine about challenges in Visualization, and then they pulled the special theme after I submitted it. I wonder where that article is now....
In any case, briefly here is my updated list off the top of my head (in no particular order):
- Integration with data sources: This remains to be one of the major challenges that never seems to go away. It's just too damn hard most of the time to transform the data into a format that visualization tools can understand.
- Integration of interactivity with analytic algorithms: Most of the time visualization is still run with command lines in batch mode. it's still too hard to ask the 'what-if' questions. This was what my visualization spreadsheet system was trying to solve.
- Working together with social analysis of data sets: Most of the time visualization exists in a context where the data is being analyzed or consumed in a social setting. It's not create a pretty picture and then stop and done. It exists in a social setting where there is a lot of different annotations by different people and different ideas being tried. Think ManyEyes here or Data360....
- Perceptually or cognitively too hard to understand: Much of visualization is designed not for the masses, but rather for the specialist. A challenge is to design visualizations that can be easily consumed or laypeople can be easily trained to use. Think about treemap being used on SmartMoney.com. How many have really learned to look at it? That's a crucial question to study.
- Design Research: I call this one the "Beyond-Tufte problem". How do we get beyond having geeks and gurus tell us how to design visualizations? We need a rigorous HCI design research approach to visualization that encompasses ethnographic studies, user-need analysis, iterative design, and real evaluations beyond cute lab confirmation studies.
--Ed
Georges:
About 5-6 years ago I wrote up an article that was going to be published in a software engineering magazine about challenges in Visualization, and then they pulled the special theme after I submitted it. I wonder where that article is now....
In any case, briefly here is my updated list off the top of my head (in no particular order):
- Integration with data sources: This remains to be one of the major challenges that never seems to go away. It's just too damn hard most of the time to transform the data into a format that visualization tools can understand.
- Integration of interactivity with analytic algorithms: Most of the time visualization is still run with command lines in batch mode. it's still too hard to ask the 'what-if' questions. This was what my visualization spreadsheet system was trying to solve.
- Working together with social analysis of data sets: Most of the time visualization exists in a context where the data is being analyzed or consumed in a social setting. It's not create a pretty picture and then stop and done. It exists in a social setting where there is a lot of different annotations by different people and different ideas being tried. Think ManyEyes here or Data360....
- Perceptually or cognitively too hard to understand: Much of visualization is designed not for the masses, but rather for the specialist. A challenge is to design visualizations that can be easily consumed or laypeople can be easily trained to use. Think about treemap being used on SmartMoney.com. How many have really learned to look at it? That's a crucial question to study.
- Design Research: I call this one the "Beyond-Tufte problem". How do we get beyond having geeks and gurus tell us how to design visualizations? We need a rigorous HCI design research approach to visualization that encompasses ethnographic studies, user-need analysis, iterative design, and real evaluations beyond cute lab confirmation studies.
--Ed
Sunday, February 3, 2008
Will the MS/Yahoo deal work?
NYTimes had a great article on the potential implications of the Yahoo/MS deal. Moreover, it suggests that MS move are indicative of market forces that it is responding to, and these market forces in Silicon Valley forces technology developers to look way beyond the battle for search engine dominance.
Saturday, February 2, 2008
US Gov't funding on basic research
Lots of concern about the basic research funding in the US, especially because it has become a political issue that is being kicked around by both the congress and the president.
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