Quantified Self is a really cool movement of people doing self tracking using technology — for example, one might use a device to monitor their heart data or when they’re at home, and then analyze it. One idea several people around the lab have been toying with is applying these ideas to organizations one is a part of. Just like individuals can benefit from Quantified Self by gaining objective information about themselves, organizations may be able to similarly benefit. (We admit, our motivations mostly boil down to: data  is cool and graphs are pretty.) The natural place to begin, of course, was with hacklab!

We (Sen and Chris) were really excited about this and have done some initial analysis. Hacklab (like, we think, most hackerspaces) had a lot of sources of data laying around, waiting to be analyzed:

• doorbot (in my opinion, our gold mine)
• Google Calendar
• IRC Traffic
• Twitter Traffic
• Mailing List Traffic
• Blog Hits
• Hacklab Public Computer Activity?

So far, we have only worked with the doorbot data.

Activity Levels

Unless the door has been unlocked, entering Hacklab requires one to use a small fob, unique to each member. The program responsible for processing these, doorbot, will unlock the door if it detects a member. It also logs the entry in a database. This is a valuable source of data about activity at the lab, but there are a number of ways in which it can be flawed. If a member works on a project on the side walk outside, they may enter and leave a number of times in a matter of minutes, but this doesn’t actually mean there was more activity. On the other hand, a member may enter along with another or on when the door is unlocked, making them invisible. Furthermore, Fob’s may be reassigned over time, and we have no way to know who the former owner was. The first concern is mitigated in the following data by considering only the number of entries by unique members each day.

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