The third and last day of dotastronomy 5 started with reports of the outcome of the Hack Day. Various extremely impressive hacks happened, way too many to mention, but including a very impressive video about planet naming, by Deacon and Angus and others, an automated astronomer-career mapping app by Foreman-Mackey and others, a XBox-Kinect doppler-shift app by Lynn that got everyone in the room dancing and spinning more than once, and (near and dear to my heart) improved functionality for the Zoonibot by Barentsen and Simmons and others. That latter hack is an extension of the the bot that got started by Beaumont and Price-Whelan (at, I am proud to say, my suggestion) at dotastronomy 4.
Among the talks, one of the highlights for me was Trouille (Adler) talking about the Galaxy Zoo Quench project, in which Zooites are taking the project from soup to nuts, including writing the paper. She spent a time in her talk on the problem of getting the participants to boldly play with the data as professional scientists might. It is a rich and deep piece of public outreach; it takes self-selected people through the full scientific process. Another highlight was Microsoft's Tony Hey talking about open access, open data, open science, libraries, and the fourth paradigm. Very inspiring stuff.
Related to that, there was great unconference action in a session on open or low-page-charge publishing models, led by Lynn (Adler) and Lintott (Oxford), in which Simpson (Oxford; and our fearless dotastronomy leader) got emotional (in all the right ways) about how crazy it is that the professional societies and individual scientists have signed away their right to their own work that they researched, wrote, reviewed, and edited for the literature. Testify!
I ran a short unconference session on combining noisy information coming from Zoo participants (or equivalent) in citizen-science and croud-sourcing situations. A good discussion of many issues came up, including about the graphical model that represents our assumptions about what is going on in the projects, about active learning and adaptive methods, and about exposing the internal data in real time so that external (third-party) systems can participate in the adaptive decision-making. I also advocated for boosting-like methods, based on the idea that there might be classifiers (people) with non-trivial and covariant residual (error) properties.
It has been a great meeting; Rob Simpson (Oxford) and Gus Muench (Harvard) deserve huge thanks for organizing and running it.