SPARQLing the BBC Programme Catalogue

Now that the BBC Programme Catalogue is live (see announcement from mattb) there’s another huge RDF data source ready for playing with.
To start the ball rolling, here’s a couple of SPARQL queries:

There’s some fantastic detail in some of the data, particularly Dr Who programmes. See for example the episode “Rose”:

Rose Tyler has an everyday job, working in a department store in London. But she gets a nasty shock in the basement, while trying to drop off some lottery money. Being chased by murderous shop window dummies nearly proves fatal, but a stranger called the Doctor saves her life. From that moment on, her life will never be the same again. Her boyfriend Mickey is swallowed by a wheelie bin & an evil duplicate replaces him, hell-bent on killing the Doctor. When Rose finally stumbles into the TARDIS, she realises the Doctor isn't all that he appears, especially after she watches him re-encounter his old enemy, the Nestene Consciousness. It is trying to take over the Earth using living plastic. Their army, deadly shop window dummies, known as Autons!

So not only is there a complete list of everyone in the episode, but a plot synopsis too. Some of the older episodes have other details, e.g. from Castrovala, episode 1:

TARDIS DATABANK: [FIRST STORY OF THE PETER DAVISION ERA] 1. ALIENS ENCOUNTERED IN EP1: Humans, The Master (Time Lord), Castrovalvans. 2. PLANET/LOCATION VISITED : Earth, Humanian Era, 20th Century; Castrovalva. 3. TARDIS CREW : Dr Who (Peter DAVISON); Dr Who (Tom BAKER); Adric (Matthew WATERHOUSE); Nyssa(Sarah SUTTON) Tegan (Janet FIELDING). The Doctor is incapacitated from his turbulent regeneration. His only hope is the Zero Room, a room of healing. Adric has been kidnapped by the Master. Nyssa & Tegan fly the TARDIS to Castrovalva to save the Doctor, but the haven is not what it seems & the Master never gives up.

There’s lots of detail in that “TARDIS DATABANK” section begging to be parsed out by some Dr Who geek.
There’s also some interesting mashup potentials with, e.g. taking the RSS 1.0 feed for individual programme entries and querying across that to collect, e.g. user reviews, annotations, still images, links to Amazon, etc.
Nice work.