SXSW 2008: Panel Picker open for business!

SXSW Interactive lets the public decide what they want to see at the conference. All you have to do is go to the Panel Picker, sign up for an account, and then start rating your interest in the 683 proposed topics. Vote before midnight on Friday, September 21st.

These are the proposals I submitted:

Hack Day: Machine Tags

The first talk I was able to attend at Hack Day was by Flickr’s Aaron Straup Cope and Dan Catt, about Machine Tags. I’m really interested in this because it adds another layer of metadata to tags, allowing them to be read by machines. I’ve heard them described as triples, and in a way I suppose that’s true, but these are not like RDF triples. Basically, a machine tag consists of a namepace, a predicate, and a value organized in a certain syntax. It’s pretty simple, but should allow services to make use of the additional data pretty easily. I scribbled a note on my paper that says:

  • folksonomy :: taxonomy
  • machine tags :: RDF

That’s a simplification, of course, but it seemed to be a good way to describe the relationship. The two main issues that will affect the adaption of machine tags are:

  1. What can you do with them? I think the answer to this one is pretty wide open. You can make apps that will use machine tags to express relationships between content, people, etc, and trigger all kinds of behaviors. Flickr’s API lets you query machine tags, and basically what you do with it is just limited by your imagination.
  2. Where is the data coming from? The question is, though, will anyone aside from you, be adding the kind of machine tags that will make your application work? This is really two questions.
    1. What’s going to make me go back into nearly 1500 photos and add more tags to them? Something needs to be done to make this a little easier or people will never do it. I’m a pretty dedicated information geek. I’ve spent an hour disambiguating two names on Wikipedia. But I’m already dragging my feet adding my backlog of Flickr photos to the map, I can’t see sift through all of them again.
    2. Even if I do, what’s to say my machine tags will be compatible with your application? Do we need some kind of standards? Or are we expecting people to add new machine tags to their content for each application they want to contribute to?

Clearly, what’s needed is something that will assist users by automatically generating suggested machine tags that they can then revise, approve, or decline. Interesting things to think about at Hack Day…

One of the big winners of the day was a hack that used machine tags – Flickr Tunes by Steffan Jones. Basically, it was a Mac OX widget that used the BBC Muiscbrain database (I think) and the Flickr API to match machine tagged photos with a song. So, if a person took a photo that they felt illustrated a particular song, and they used the appropriate machine tags to capture the song name (and even a time code), then the images would display while the song played, as a sort of slide show, even keying to the specific moment in the song, if indicated.

Pretty cool, but as I mentioned, how much data would need to be entered to make it a valuable experience for fans of all different kinds of music?

Folksonomy versus Taxonomy

My colleague Seth Earley wrote an interesting post on a topic I’ve been thinking about lately, the relative merits of Folksonomy versus Taxonomy. I agree with the points he’s making, though I think there’s room to go a little deeper into the appropriate uses of each. I’ve seen some great applications of user-generated tagging, and I’ve also seen some poor applications that were clearly designed to save time and resources, with no real thought as to why people would be motivated to contribute meaningful information (I’m looking at you,!).