tons of bad data?

Christopher Stumm (Microsoft) and Lang are in town this week, to see if we can do reliable science with unreliable data. Stumm designed, wrote, and operates our Flickr pool in which we calibrate amateur astrophotography just as if it were professional data. Now we want to use those data as if they were professional data, since they certainly contain tons of information. But the challenge is accounting for the fact that data of unknown provenance will, in general, contain unknown artifacts, errors, and noise. We started on project specification this morning.