Blog archive: Mashups

Collaboration with Universitat Pompeu Fabra (Barcelona)

One of the nice things about running your own business is that you can occasionally decide to spend a bit of time doing a bit of research into stuff you find interesting. The Normalisr is an example of this - an application that I built to reflect some of my ideas on attention data and what could be measured in listening charts.

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New-look Normalisr launched

Hooray! It's live! Your all-new "Normalisr" experience can now boast the following improvements:

  • A new URL -
  • A slick new design, including gig photographs
  • Thumbnail views of artist and album charts
  • The ability to manually find artists and albums that come from without a proper Musicbrainz ID - we're hoping that this will improve the accuracy of your charts
  • Proper Unicode support (fingers crossed!)
  • A graphical widget of your artist chart to add to your blog or profile

We hope you enjoy it. If you have any questions, feedback or issues to report, please use the feedback form.

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Normaliser v2 in production

After months of neglect, we've finally got round to working on an update to our normaliser application. We've decided to build the whole thing from the ground up using Python/Django, our new favourite toys. Version two will hopefully include the following improvements:

  • Proper unicode support.
  • The ability to find artists & albums that have a blank Musicbrainz ID in This will involve users doing an additional search for each artist, but it should vastly improve most people's charts. We will try to make the search process as easy as possible (see screenshots below).
  • A whizzy new design using gig photos from Flickr.
  • Updated XML format to mirror v2 of's data feeds (we will keep the older XML versions available on the same URL).
  • Hopefully, some form of export code that will allow charts to be shown on user blogs, etc.
  • We're still scratching our heads trying to think of ways we can make a few quid out of all the work we're putting into this...

Anyway, some work in progress screenshots below.


Continue reading » Normaliser - one year on

Our normaliser application recently celebrated its first birthday, and we're pretty pleased that not only has it lasted this long, but it still seems to be going strong. In that year, it has served up over a quarter of a million charts and now has over 215,000 albums in its cache.

It has been very interesting to compare usage with coverage - while most of our referrals come from itself, this article in Read Write Web, a link from Tom Coates and the launch of's directory of external applications all provided some welcome spikes in traffic.

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Usage statistics for the normaliser

We've just knocked together a stats page for our normaliser application, that rejigs your charts based on an estimate of how long you have actually spent listening.

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Another mashup - News about your favourite artists

I have just published a little application that grabs the top 50 artists from your profile and searches for the latests news about them from Google News. The results are produced in RSS format.

Continue reading » normaliser - algorithm change

After much head-scratching and a few hairy moments with the database this afternoon, we have updated the Normaliser to use median track length values in its calculations, rather than the arithmetic mean values used previously.

Hopefully, this should smooth out a lot of the issues people were reporting with a handful of extra-long or extra-short tracks skewing the figures for a particular artist or album. Normaliser updated

I have just updated the normaliser application to add a few new features, including album charts and different time periods. Full update history here. Normaliser - a mashup with Musicbrainz

After grumbling about the way calculates artist rankings, I realised that in the age of open data it shouldn't be too much hassle to knock together a little application to apply the normalisation calculation I discussed.

The application takes a username and recalculates the ranking based on an estimate of the amount of time you have spent listening to an artist, rather than the number of tracks played. It uses the excellent MusicBrainz web services to calculate an artist's average track length. Why not give it a whirl.

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