An other thing I wished I had learnt… the black art of mapping parameters.

An other thing I wish I had learnt from an electroacoustic music course is the art of mapping parameters. Actually, this is applicable for all digital media.

This black art is at the *centre* of almost all digital art work. I’m calling it right here and now. The digital medium is hugely empowering because it allows working across many many mediums. But exactly how one crosses mediums is the driver of meaning in digital work. Its called parameter mapping, and I think it is central.


What happens if you map a cats random walk to a physical keyboard? What meaning is carried by the resultant sound?

This involves gathering data or content from one context … and using it to drive things in an other context. The black-art in it involves knowing, intuiting, designing exactly which parameters will be used to drive what. Its one of those things that is very easy to do, but its very difficult to do well … to do it in such a way that it carries meaning.

In the digital world, there is very little difference between audio, video, sensor data, spread-sheet data, data that represents waves, randomly generated data, algorithmically generated data, etc. It is all just numbers, and you can use those numbers as you wish. But where you get the numbers from, and what you choose to drive with those numbers is where the intelligent-creative-act lies.

I’d call this course Parameter Mapping. One assignment would involve getting students to each create an art-work but all from the one set of data. That would highlight the importance of how one chooses to interpret or map a dataset. What would be fantastic is permanently setting up a collection of sensors .. which broadcast their data over wireless network using OSC. Students must interpret that data in a meaningful way.

An other assignment would involve the inverse. The output format would be pre-determined (for example, a midi keyboard) and the students would have to collect data in any way they might choose … but explicitely to drive a midi keyboard. They might choose to generate data algorithmically, they might choose to generate random data, they might choose to analyse a video stream, or create midi notes by parsing emails received in real-time.

In both cases, the assignment would be marked on the resultant relationship between the source data-set and the finished output.

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5 Responses to An other thing I wished I had learnt… the black art of mapping parameters.

  1. I feel like I’ve hit the nail on the donkey, with this one.

  2. Ben X tan says:

    I would definitely do that course 🙂

    • Hi Ben 🙂

      Yes … I can see that your work with the Kinect, and probably lots of other stuff you’ve done has exposed you to the art of mapping parameters.

      Its interesting to see all the mapping work that is coming out with the Kinect. Its very similar to the exercise I mentioned …. given one input set of data … what can you drive … and what meaning is inferred.

  3. brogan says:

    Hi Etienne, great idea. Might have to steal and put into MEDA102…and get you to give a lecture. This potential to remap data is very evident in the tradition of alternative browsers – Mark Napier’s Shredder is a good example:
    Napier’s work has a critical edge and maintains recognisable aspects of the original web page elements. Difficult to do radical re-mapping that doesn’t simply render the data random input.

    • Hi Brogan,

      Feel free to use the assignment ideas… would be interesting to see the results.

      Yes, I think poor/unconsidered mapping causes apparent meaninglessness in the source data.

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