metade.org

• The Tshirt and Tee Search Engine - PleaseDressMe
  T-Shirt search engine, provides a REST API
  (tags: t-shirts web2.0 search REST)

• Viagem a S. Tomé e Príncipe
  Blog with great photos of São Tomé e Príncipe, where I'll be going next week!
  (tags: saotome holiday)

• ACM SIGWEB - PhD and Masters Theses
  A repository of PhD and Masters theses on the field of hypertext and hypermedia.
  (tags: phd repository hypertext)
• BBC Radio: worse than I thought • Shane Richmond
  Someone criticises the music played on BBC Radio based on the playout data from the BBC Music Beta
  (tags: bbc music musicdisco radio)

• Linked Movie Database
  Linked Movie Database aims at publishing the first open semantic web database for movies, including a large number of interlinks to several datasets on the open data cloud and references to related webpages.
  (tags: semweb movies linkedata d2r)
• BBC - Music - Beta
  I made this!
  (tags: bbc music musicbrainz radio semweb)

At BBC Audio and Music Interactive, I’m one of the software engineers working on the BBC Music Discovery team. This week we launched the BBC Music Beta, which focuses in particular on publishing information about the artists broadcast on the BBC. You can read more about the site on Tom Scott’s blog and BBC Radio Labs.

Matthew Shorter describes at the bottom of his post how to use MusicBrainz to find a given artist. Here’s a little something to make that a touch easier: a BBC Music/MusicBrainz bookmarklet!

Drag this BBC Music/MusicBrainz link to your bookmarks bar in your browser. Now, when you’re on an artist page (e.g. Coldplay) click on the bookmarklet to switch between BBC Music and MusicBrainz artist page.

Enjoy!

When I presented my music recommendations hack at Mashed last weekend, I showed some examples by randomly browsing around the artists and brands pages.

When I came to the Giles Peterson show, I was surprised that the system was recommending artists such as ‘The Automatic’ and ‘Arctic Monkeys’.

This struck me as extremely unusual recommendations for a show featuring “Latin, funk, soul and hip-hop”, but I suspected that the data rather than the system was at fault. I had a quick look at the source data that had been fed into the system for this show and found:

• The Wombats (1)
• My Chemical Romance (1)
• Hard-Fi (1)
• Gideon Conn (1)
• Armand Van Helden (1)
• Editors (1)

Looking at this list, it seems that the recommendations actually make sense: there is very little data for the show, and actually it doesn’t even look correct!

This data has been generated from the digital play out system but we are unable to track some of the shows, especially specialist music shows such as Giles Peterson. The DJ might play directly off their own vinyl/cd/computer/other crazy device, or the show might be pre-recorded.

So what I’ve done is simply ignore brands with a low average artist play count (<=1.0), which should avoid this kind of situation.

I also want to point out that there is a basic API in place, although it still needs documenting. Just add '.json' at the end of brand/artist/last.fm profile URLs to get a JSON feed of the data.

I’ve just returned from Mashed 2008 where I formed part of the BBC Radio Labs contingent.

We were providing all sorts of fun things for people to play with, from live BBC Radio audio streams, feeds of what track is being played over the air and archives of both the audio and metadata feeds. All of the details are available on the BBC Audio and Music Interactive at Mashed 2008 site.

One of the things that I was directly involved in was the “How many times brands have played artists” data set. By matching the music tracks played on air to MusicBrainz artists, and then work out which radio show the track was played on, we can build this index of which artists were played on what shows. For example, we can see which artist Jo Whiley has played the most, or work out who’s been playing the Arctic Monkeys the most.

It is also a great resource for recommending artists and shows and shows to people. So what I did for Mashed was feed this data into the Semantic Space engine, developed at the University of Southampton by Jon Hare, and build a web app around it: music-recommendations.metade.org.

The site let’s you browse around artists and shows, and view lists of other artists and shows the system has recommended. It also provides recommendations based on a last.fm profile top artist feed.

There is a little more detail on how the technique works on the site (hint: it’s based on latent semantic analysis), and I intend to carry on working with Jon to improve both the quality of the recommendations and how they are visualised.

It’s brilliant to see the “Band in Your Hand” Augmented Reality feature built for Radio 1’s Big Weekend. There’s even a video showing Scott Mills trying it out!

Read more about it on the Radio Labs blog.

While talking about Augmented Reality, I was browsing through the recent O’Reilly “Augmented Reality - a practical guide” by Stephen Cawood and Mark Fiala. It looks like a great introduction to the subject, describing some of the new augmented reality frameworks that have improve on the trusty old ARToolKit. However, I felt that the demo application that the book presents could have explored the tangible augmented reality side of things more.

After nearly 11 years at Southampton University, I am finally leaving and heading off to London.

It’s been quite a ride: starting as an undergraduate, doing my PhD, and then four great years as a research associate/fellow at both IAM and LSL.

Tomorrow I start a new adventure, as a Software Engineer at Audio & Music Interactive at the BBC…

Back from Hack Day London - it was absolutely incredible! I had really great fun, did a lot of hacking/coding all night long!

I worked with Jon Hare, and we went for the augmented reality web service, which was pretty crazy. We made the ARToolKit, which you can see in the video below, into a web service!

Although it’s a little rough around the edges still, you can play with our hack online at: http://multimedia.ecs.soton.ac.uk/artheworld

I’ve also posted the slides from our 90 seconds presentation on Slideshare: