i202 Fall 2010 School of Information, UC Berkeley

Did you enjoy working with the text tools?

Those of you who're interested in dashboards and how visualize complex information, might want to check out a source called Perceptual Edge. One of the partners of the company, Stephen Few, has done a lot of work studying the best ways to communicate complex business information in limited space. He was a guest lecturer in the InfoViz class last semester and provided a lot of good examples of well-designed dashboards. I believe he is also a lecturer at Haas, so he cares both about the business value of those dashboards and about their usability.

One interesting service that provides an ontology for common things is Freebase (which is now part of Google). You can look for a concept/person/place and Freebase will tell you different domains in which the concept is used. For example, if you look for Berkeley, you can refine your search for Berkeley (USA), Berkeley (UK), or Berkeley (University). You can go crazy and see that all the information that Freebase has about Berkeley is available as an RDF file.

Along the lines of my previous post about tagging usage in del.icio.us, you might want to take a look at TagWiz. Hyunwoo Park, Satish Polisetti, and Dhawal Mujumbar created this tool to visualize the tags of an individual user in delicious. It provides tag frequency distribution visualization and a metric of how important the long tail effect is.

To illustrate the point that Bob made in class about tagging and controlled vocabularies, you may want to take a look at SociallyDelicious. Prateek, Yo-Shang and I created this tool last year in IOLab. The main idea is to see show people tag bookmarks in del.icio.us and whether their tagging behavior is influences by their level of expertise.

Collecting information is not the same everywhere. This article by The Economist reveals different methods used to collect information for digital maps: from using sophisticated GPS systems in England, to note-taking in India and voluntary contributions in Nigeria. There is no single way to get data from every place, and different information is needed by different users in a variety of contexts. The following questions arise: How do we standarize all these different data-collections?

I was reading this article in The New Yorker about a book called "Eating animals" today and something came to my mind. Somehow categories define how we feel. I like eating "pork", but maybe I wouldn't like to eat "pig". We also do not want to have "cow sausages", let's better call them "beef sausages". Why don't we eat "dog" or "cat"? Well... because they are pets, aren't they?