Kepler Family Life Spans

September 25, 2011

Family Lifespan Project

Kepler Family Life Spans is my first original data visualization using processing. Since the summer,  I’ve been more interested in processing as a tool, data visualizations and generative art as well as my own genealogical history. So naturally, I wanted to figure out some way to visualize some of my family data. This project enables you to select a year starting with the earliest birth year that I have for my ancestors that I have a birth date and death date for. For each year, you can see the average life span for my family at that point all the way up to 2011. When a person dies, their representation goes red and stops progressing in age.

With this little project, my goals were to learn how to integrate data into processing, use the API to grab my genealogical data, and create something that was visually interesting. Because I was concentrating so much on the data aspect, it ended up not being as visually interesting as I planned on, but now I’m better equipped with the “how”, so that next time, I can concentrate on the cool factor a bit more.

As for the some interesting conclusions that I’ve come to, you can see the expected rise in average life span, thank goodness. In fact, the oldest person that has passed away was this year, with my grandmother at 96 years old. Also in the recent years, I thought it was interesting to see a 10 year gap in new babies, where with a family where I have cousins almost as old as my parents and as young as their mid 20s, I thought that there would be a baby born every year or two. Of course this data probably isn’t all that interesting to anyone outside of my family, so that brings me to what I plan on doing from here.

Since this data comes from what I’ve included in my account, I plan on making my work public so that other people can plug in their geni credentials so that they can come to their own conclusions. And with that, I will also need to make a javascript version or app so that people can actually use it. I also hope to figure out ways to improve on this and keep it updated as well as continue exploring how to visualize this data in interesting ways. I’m sure that there are more fun and interesting conclusions that can be found from this data too.

In the next post, I’ll go into what went into making this and what I learned from the process.