had a lot of conversations with people in the open-data community. What they've been really good at is exposing a lot of data sets—it's been made accessible by the city and the government, and they've been good at exposing it in easy-to-inform ways, like a map or a web app that shows where the buses are.
That's been good because the data is now in front of people, because the normal consumer isn't going to go into a portal, and download a file, and open it in Excel. So what they've been really good at is bring that data to the people.
I think the next thing is using that to make inferences, to make predictions, to improve certain outcomes. So it's great that you can look at this data and see where the buses are, but the next step is to ask "can I improve the bus routes? Can I work with CTA to find better scheduling?" What I'm pushing them towards is taking the same data they've been having people look at, and asking "how can I improve the process that's generating this data?"
....The next step is not just looking at it, but using it to make predictions about the future and improving the outcomes for the people who are consuming those services