This was a way to demonstrate how data can be interactive. This backgrounds the fact that data itself is something that is interpreted and not fixed or purely objective. The ability to "play" the data as music leaves the interpretation up to the person viewing it. Check out the Coqui water sensor for a great example of how conductivity - a reciprocal of resistance - can be output as audio. I'm interested in other ways to represent and experience data through other senses. Most of the time, representations of data are ocularcentric- that is, very focused on image and spectacle. I was in a public space, and there was a meeting happening a few seats over.) (Apologies for the audio in this video not being very loud, ironically. (This is the Sparkfun tutorial I followed.) Thus, instead of playing my computer keys, I could then use the apples as an interface to the piano sounds. pencil lead-based drawings, bananas, cups filled with water, etc.), I mapped my computer keyboard to the board, then the board to some apples. Taking a MakeyMakey, which is an Arduino-based board that lets you create on/off buttons out of pretty much anything that conducts electricity (i.e. Your computer keys are programmed to play within the same scale as the musician, so you end up augmenting their performance with your own interpretive one. While watching and listening to a person play the piano, you can use keys on your computer keyboard to play along. This is an awesome interactive music project out NYU. If you imagine the individual bar charts as "notes" and the height of the bar chart as a proxy for "pitch" or "tone," you could almost map out a musical "scale" across the graph.
The bars reminded me of piano keys, which then prompted the thought: what if you could "play" data like you play a musical score?
While looking at the bar graph, I tried to think of other way to represent the data. Using Tableau, I made a simple bar graph: Then I wondered what the data might look like if broken down by the minute. So, I thought it might be fun to highlight the movement of Jeff's kayak as it moved through on river through time by plotting the same data on CartoDB and animating it: I was fascinated by the spatial mapping of the data, but the R markups were relatively static (though gorgeous). Jeff brilliantly rendered an R markup of his original data set and produced this map and this chart, which plots the GPS data and the temperature over time: In this sense, the data itself are not that compelling - but this is important, and I'll get to that later on in this write-up. As it happens, there was no significant change in temperature, as the data show. My attempt and resultsĭuring the kayak deployment, Jeff noted that he thought the water temperature by the outfall might be different than the rest of the river. The final slides from my presentation are here if you're interested in seeing them. Jeff was kind enough to send me the data (see GitHub) so I could try some stuff out. I was inspired by Jeff Walker's kayak deployment of the Riffle-ito (Riffle + GPS shield) back in early August and wanted to do something with the data collected from it.Īt MIT, I recently took a data visualization workshop in which we were asked to find a data set, identify a story, and visualize the data in a way that facilitated telling the story.
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