Terrapattern provides an open-ended interface for visual query-by-example. Simply click an interesting spot on Terrapattern’s map, and it will find other locations that look similar. Our tool is ideal for locating specialized ‘nonbuilding structures’ and other forms of soft infrastructure that aren’t usually indicated on maps. It’s an open-source tool for discovering “patterns of interest” in unlabeled satellite imagery—a prototype for exploring the unmapped, and the unmappable.
This map offers an alternative way to browse the 2,619,833 images contained in the Internet Archive’s book collection. It shows 5500 different subjects which have been algorithmically arranged by their thematic relationships. The size of each link resembles the amount of images that are available for that topic. Clicking on a link will open the flickr page containing all the pictures for that subject.
http://incubator.quasimondo.com/internetarchive/InternetArchiveBookSubjectsMap.html
Our empirical and theoretical findings have cautionary implications for the future of social search, and crowdsourcing in general. Social search is surprisingly efficient, cheap, easy to implement, and multi-functional across aplications. But there are also surprises in the amount of evildoing that the social searchers will stumble upon while recruiting.
I was biasing the results by using full-text search to explore my email. I would look for the things I found interesting that day—searching on terms like “Google” or “literature” or “e-reader”—and see a chronological list of exactly what I said about those very terms. The pattern-seeking engine in my brain would fire on all cylinders and make a story of the searches, creating an unintentional email-chrestomathy, a greatest-hits collection of ideas I’d had around a single word or phrase. The results seemed weirdly definitive. I thought I was doing history in a mirror, but because the emails were pure matches for key terms, devoid of all but a little context, I fell for the historical fallacy