The following will describe how we created the piece Good Fences Make Good Neighborhoods for the San Francisco Urban Prototyping festival.  This piece was a data sonification of various pieces of information about the city.  What is a data sonification?  That's when you interpret data through sound rather than visuals.  For instance, an EKG or a fire alarm is a data sonification of sorts.  We wanted to make something that sounded cool, though, so we took some data about San Francisco that was compelling and available and ran it through our compositional filters.  

Why would we do this?  Well, the UP festival focuses on quick ideas to make cities better through constant engagement, and we (that is Emily Shisko and Shane Myrbeck) thought that we could create an engaging piece that explored information about San Francisco through a different sensory modality than we're used to.  Certain aspects of perception of sound, like the ability to experience patterns rather than just see them, the detailed temporal resolution, its immersive nature if presented properly, etc, make it an interesting method of conveying information.  Hopefully, the result was a unique and engaging experiment! 

Step 1: What Do You Want to Hear?

The first step is to choose what type of data you want to interpret through sound.  This will be a combination of what you think is interesting and what is available.  Your city will always have databases of information that are accessible to you, but the question is then if you can get it in (or get it into) a format which is malleable given your chosen sonifying tool.  For our piece, we chose:

-A database of trees planted in San Francisco since 1981 
-Tide time/location and water temperature for the month of June 2012
-Language demographics from the 2010 census 
-Wind data at 4 different locations over some months of 2012

We chose these four datasets because they represented two human-centered subjects - trees planted and the languages we speak, representing what we want our city to be and who we are, respectively.  Tides and wind are natural datasets, although as with everything in the urban environment, we affect those too...

We decided that although the different pieces of information represented very different timescales (from static to 30 yrs), we would present each for 3 minutes at a time.  This decision was made to exploit an inherently interesting aspect of presenting data through sound, that the our sensitivity to time as listeners is naturally acute, and also that time can be expanded and contracted with sound in a way that is difficult to do visually.  

Have fun choosing your datasets -- this is what will  make your piece cool!

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