On this week’s Innovators show I got together with David Huynh, whose work with MIT’s Project SIMILE wowed me last year. David recently joined Metaweb. His first project there, Parallax, creates a new way to browse Freebase, the structured wiki that also wowed me earlier last year.
What struck me about SIMILE and Freebase was the way in which both projects cut through the fog of semantic web technologies and terminologies and got down to brass tacks: How do you get people to want to contribute structured knowledge? You have to appeal to natural instincts and, as I explored in my writeups of both projects, they do.
In the case of SIMILE, when somebody sees an interactive, data-rich Exhibit, the natural response is: “Cool! How do I get one of those for myself?” The answer is: “Pretty straightforwardly, by cloning the example you see and then massaging your data into an easily-written format.” The hidden agenda is: “You may not know or care, but once your data is in that format, it can federate.”
In the case of Freebase, the reciprocal nature of data relationships creates a kind of social glue. People who contribute to Wikipedia, or Freebase, or to the web in general, hope those contributions will be read and appreciated. The genius of Freebase is that, when I define a relationship between one of my records and one of yours, both come into view. I may notice something missing from yours and add it. You’ll in turn notice my contribution and may reciprocate. As we advance our own interests, we naturally find ourselves advancing others too.
Parallax, as you can see in the screencast David has embedded on the project’s home page, is a new way to explore Freebase. In the standard interface, you have to do some digging to trace connections to related sets of information. Or you might even have to drop into the API to do programmatic search. Parallax brings those relationships to the surface. One of the examples in the screencast asks and answers the question:
What were the schools attended by children of Republican presidents?
This boils down to a query that finds a set of Presidents, then a set of Republican Presidents, then a set of children, then a set of schools. With Parallax you perform that query interactively, by following links that surface as you pivot from set to set.
This is a great way to browse the structured corpus, but how does it motivate people to provide more and better contributions? Here’s one way: By exposing the completeness — or incompleteness — of sets viewed in relationship to one another.
As I was browsing the set of U.S. Presidents, for example, Parallax surfaced the connection Works written. But there wasn’t much there: Jefferson and Adams for the Declaration of Independence, Madison for the Federalist Papers, and a few recent books by Jimmy Carter and Bill Clinton.
So I created an item in Freebase for Richard Nixon’s Six Crises, linked it to Nixon’s record in Freebase, and went back to Parallax. Sure enough, there were Nixon and Six Crises. The set of books written by U.S. Presidents had increased by one. Along the way, a new book record was created in Freebase, and an existing person record was enhanced.
As I mentioned to David in our interview, this strikes me as a really powerful way to motivate contributors. In Wikipedia there’s no easy way to observe an implicit set. You can only look at explicit sets, like the lists of Presidential ages and religious affiliations. Somebody might decide to make an analogous list of Presidential books, but that would be much more likely to happen if the partial list that’s already implicitly in Wikipedia could be brought into focus.
When shown partial patterns, people naturally want to complete them. Parallax looks like a great way to tap into that instinctive urge.