With Tom Scott, we presented a talk on contextualising BBC programmes using linked data for the Linked Data London event. For the occasion, I made a couple of screencasts.

The first one shows some browsing of the linked data we expose on the BBC website, using the Tabulator Firefox extension. I start by getting to a Radio 2 programme, to get to its segmentation in musical tracks, to get to another programme featuring one of the tracks, to get to another artist featured in that programme. The Tabulator ends up displaying data aggregated from BBC Programmes, BBC Music and DBpedia.

Exploring BBC programmes and music data using the Tabulator

The second one shows what you can do by using these programmes/artists and artists/programmes links. We built some very straight-forward programme to programme recommendation using them. On the right-hand side of the programme page, there are recommendations, based on artists played in common. The recommendations are scoped by the availability of the programme on iPlayer or by the fact it has an upcoming broadcast. If you hover over those recommendations, it will display what allowed us to derive it: here, a list of common artists played in the two programmes. This work is part of our investigations within the NoTube European project.

Artist-based programme to programme recommendations

Also, as Michael already posted on Radio Labs, we gave a presentation to the London Web Standards group on Linked Data. It was a very nice event, especially as mainly web developers turned up. Linked data events tend to be mostly about linked data evangelists talking to other linked data evangelists (which is great too!), so this was quite different :-) Lots of interesting questions about provenance and trustworthiness of data were asked, which are always a bit difficult to answer, apart from the usual it's just the Web, you can deal with it as you do (or don't) currently with Web data, e.g. by keeping track of provenance information and filtering based on that. Somebody raised that you could make some statistics on how many times a particular statement is repeated in order to derive its trustworthiness, but this sounds a bit harmful... Currently on the Linked Data cloud, lots of information gets repeated. For example, if a statement about an artist is available on DBpedia, there is a fair chance it will get repeated in BBC Music, just because we also use Wikipedia as an information source. The fact that this statements gets repeated doesn't make it more valid.

Skim-read introduction to linked data slides