Measuring the Immeasurable: Researching Community Health
by Kristin Shoemaker - Sep. 09, 2008Comments (2)- Related Blog Posts
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An open source project is a complex organism. Like a carbon-based lifeform, an open source project is usually a fantastic mix of a number of systems (and theories) that vary in complexity, interact closely, and that can't function effectively (or at all) without support from surrounding components.
Lately, there's been a lot of talk about community. Community is a fairly abstract term, and to continue the "project as an animal" analogy, it's pretty safe to say that if the software is a measurable biological system, the community has long been equated with the "soul."
Sure, the community is the soul of any open source project. There isn't really a way to measure the "soul" of anything -- never mind an entire community. A community, ideally, is also a brain, directing the biological, measurable aspects of a project on how to function and grow. A brain? A brain is something that can be looked at, physically, analytically, to get a good handle on the health of the project and the community.
Jono Bacon, community manager for Ubuntu, puts forward some of his ideas for a decidedly analytical approach to assessing the growth and trends in the community. He postulates that just because community management by nature is a "soft science," doesn't mean that there aren't good markers of where the community is headed buried in readily available hard data. It can stretch far beyond the number of downloads of any given release, and delve into bug report statistics, and feature requests.
He makes a really good argument and case for this approach. But even better, he doesn't imply that the data collected and examined will reveal the cold hard truth in every case, or couldn't point to a number of very different scenarios. Just like an animal is more than a set of biological processes working together, a community is more than a set of numbers that can be manipulated to prove (or disprove) a point about a project's worth, growth, or future.
This is a tremendously encouraging approach to assessing and fostering the community. The data collected can point to potential problems or shifts in focus (desired or undesired) in the project long before the community is consciously aware that these events are happening. It can help the community plan to move forward more cohesively and effectively.
The trick for community managers, developers, end users, and even businesses thinking of investing in or deploying open source software will be to accurately weigh data interpretation with the human element of community. There is no perfect way of doing this -- the same dataset that might be a positive sign for a small, highly specialized community could indicate a larger, more generalized community is in serious trouble.
Communities are what make open source projects unique. They draw new users in, and get them excited and involved. Managing a community is a rough, but necessary, job -- because communities are vital. A scientific approach might not yield all the answers for a community manager, but it could at least help minimize those sleepless nights.
