I like to think of data visualization as a story. The main character is the user, and we can go two ways. A story of charts and graphs maight read a lot like a textbook; however, a story with contet, relationships, interactions, patterns, and explanatioins reads like a novel. This is not to say that one or the other is better. There are plenty of interesting textbooks, and probably just as many-if not more-boring novels. We want something in between the textbook and novel when we visualize personal data. (查看原文)
Good form design doesn’t draw attention to itself and should be nearly invisible
“Don't ask the user to do what you can do--or dicover--on your ownn”
One of the secrets of email surveys is that the second mailing to the same list generally receives just as many responses as the first. (查看原文)
“you’re dealing with extremely thin data sets, so the quality of that data is really important.” In other words, when important decisions are base on the answers given by only a few hundred people, those answers had better be great (查看原文)
The Point
Data visualization is often all about analytics and technical results, but it does not have to
be—especially with personal data collection. People who collect data about themselves are not necessarily after the actual data. They are mostly interested in the resulting information and how they can use their own data to improve themselves. For that to come through, people have to see more than just data in the visualization. They have to see themselves. Life is complex, data represents life, and users want to understand that complexity somehow. That does not mean we should dumb down the data or the information. Instead, we use the data visualization to teach and to draw interest. Once there is that interest, we can provide users with a way to dig deeper and explore their data, or mo... (查看原文)
What infrastructure we have must be carefully employed: we can begin to better use data by understanding both probabilities and the limits of probability, and by remaining careful of the cognitive biases that cloud interpretation. (查看原文)
