Thanks to the Creative Producers development scheme I was able to attend the SXSW 2011 conference with an incredible group from across the UK. A common theme in the sxsw sessions I most enjoyed was making use of large amounts of data.

In "All These Worlds Are Yours: Visualizing Space Data" Douglas Ellison covered NASA's experiences in making large amounts of data understandable. Initially external developers would take the openly released imagery and data and create their own visualisations. These would occasionally get covered in mainstream press, getting attention for NASA for no work of their own. Other tools would turn out to be useful for the mission planners who then went on to ask the community what they should photograph.

As well as allowing the community to make their own vizualisations they created tool for ordinary users to view the data themselves at http://solarsystem.nasa.gov/eyes/. "Hey taxpayers, here's your fleet of satellites" as the speaker remarked.

Finding Music With Pictures: Data Visualization for Discovery by Paul Lamere also focused on comprehending data. I particularly liked "Music that makes you dumb" for correlating bands as listed on facebook profiles with average SAT scores of the college attended. Rather than simply showing the data as it currently is it adds a new context to produce some unexpected insight.

This reminds me of "Gowallahol" which works in a similar way. It uses data from Gowalla, where people announce where in the world they are, combined with facebook and electoral registrations to attempt to predict where drunk driving is most likely to occur.

Finally "Machines Trading Stocks on News" showed how financial organisations are data mining the news to automate trading. Particularly amazing was that they used the tweets of farmers to predict how well a harvest may go. They also discussed the difficulties of allowing a machine to understand sarcasm, accidental obituary publications and identifying out of date news articles. No mention was made of the correlation between Anne Hathaway and Berkshire Hathaway.

Now to figure out how this can be applied to the cultural sector. There are vast amounts of museum & gallery collections and theatre performance metadata. What insight can be found within?