Larvae Data Visualization
HERE is the app… it takes some time to load… and it runs slow in the browser.
Last week’s Visualizing Data was all about the grub, or ‘larvae’. As mentioned earlier in my Larvae! post, this week is the first time we are working with a large, structured, data set (xml). The first thing I had to do before I could get to the visualizing part was get all the data into my app nicely organized. Luckily enough I scraped together a few simple routines to make that happen. HERE is a link to a processing sketch that simply gets the data from the HUGE (>5bm) xml files and quickly draws the paths and gradients to the screen.
After that, twas all about making a tool to explore the boring old xml data.
I decided to take a very direct approach (crazy I know) and draw all the paths to the screen with the larvae animating over them; as a kicker though, I let the user filter how they want to see the paths… grouped by ‘left olfactory’ larvae, ‘both olfactory’ larvae, or ‘all’. I also let the user track individual larvae as they make their journey toward the odor source, or see them as a group.
All in all I think it tuned out well, although I think it needs work on communicating the smell and point of the experiment itself… ie, if a person had read the research paper on the experiment where this data came from, they would be in the know’ but if they just stumble across my app on the internet, then they may not fully get the picture….
Terrific work Thomas. Such a different perspective on the data too & gives the scientist much more specific info about the gradient! I’m quite intrigued by the “larvae drop zone” — you’ll have to tell us about it in class. I know Dr. Vosshall will find it illuminating.
We’ll talk more about the “reading” of the visualization in class.