Jason Groth Wigs Out
Anyone who knows me is probably aware of the fact that I’m a keen amateur* musician. So I was very pleased to be able to work on a musical dataset while spending some sabbatical time at OeRC with Dave De Roure. The project has been focused around the Internet Archive‘s Live Music Archive. The Internet Archive is a “non-profit organisation building a library of internet sites and other cultural artifacts in digital form”. They’re the folks responsible for the Way Back Machine, the service that lets you see historical states of web sites.
The Live Music Archive is a community contributed collection of live recordings with over 100,000 performances by nearly 4,000 artists. These aren’t just crappy bootlegs by someone with a tapedeck and a mic down their sleeve either — many are taken from direct feeds off the desk or have been recorded with state of the art equipment. It’s all legal too, as the material in the collection has been sanctioned by the artists. I first came across the archive several years ago — it contains recordings by a number of my current favourites including Mogwai, Calexico and Andrew Bird.
Our task was to take the collection metadata and republish as Linked Data. This involves a couple of stages. The first is to simply massage the data into an RDF-based form. The second is to provide links to existing resources in other data sources. There are two “obvious” sources to target here, MusicBrainz, which provides information about music artists, and GeoNames, which provides information about geographical locations. Using some simple techniques, we’ve identified mappings between the entities in our collection and external resources, placing the dataset firmly into the Linked Data Cloud. The exercise also raised some interesting questions about how we expose the fact that there is an underlying dataset (the source data from the archive) along with some additional interpretations on that data (the mappings to other sources). There are certainly going to be glitches in the alignment process — with a corpus of this size, automated alignment is the only viable solution — so it’s important that data consumers are aware of what they’re getting. This also relates to other strands of work about preserving scientific processes and new models of publication that we’re pursing in projects like wf4ever. I’ll try and return to some of these questions in a later post.
So what? Why is this interesting? For a start, it’s a fun corpus to play with, and one shouldn’t underestimate the importance having fun at work! On a more serious note, the corpus provides a useful resource for computational musicology as exemplified by activities such as MIREX. Not only is there metadata about large number of live performances with links to related resources, but there are links to the underlying audio files from those performances, often in hgh quality audio formats. So there is an opportunity here to combine analysis of both the metadata and audio. Thus we can potentially compare live performances by individual artists across different geographical locations. This could be in terms of metadata — which artists have played in which locations (see the network below) and does artist X play the same setlist every night? Such a query could also potentially be answered by similar resources such as http://www.setlist.fm. The presence of the audio, however, also offers the possibility of combining metadata queries with computational analysis of the performance audio data — does artist X play the same songs at the same tempo every night, and does that change with geographical location? Of course this corpus is made up of a particular collection of events, so we must be circumspect in deriving any kind of general conclusions about live performances or artist behaviour.
Who Played Where?
The dataset is accessible from http://etree.linkedmusic.org. There is a SPARQL endpoint along with browsable pages delivering HTML/RDF representations via content negotation. Let us know if you find the data useful, interesting, or if you have any ideas for improvement. There is also a short paper  describing the dataset submitted to the Semantic Web Journal. The SWJ has an open review process, so feel free to comment!
- Sean Bechhofer, David De Roure and Kevin Page. Hello Cleveland! Linked Data Publication of Live Music Archives. Submitted to the Semantic Web Journal Special Call for Linked Dataset Descriptions.
*Amateur in a positive way in that I do it for the love of it and it’s not how I pay the bills.