Open Source Computing and Citizen Science Innovation - Where They Start and End

The last few weeks I've been fleshing out thoughts on citizen science business models in preparation for next year's Citizen Science Conference in San Jose.  There is so much to sift through and people to talk with that I wanted to hit the ground running.  Of course there won't be nearly enough time to discuss everything during a two-day conference, but I hope this will start a discussion there, and on this blog, for a long time afterwards.

One interesting book I came across was "Making Open Innovation Work" by Stefan Lindegard, which offers great insights on companies harnessing the innovation of external researchers.  Many of these lessons can be applies to our discussion, but that's not why I'm writing.  Instead it forces me to ask a question that has bothered me a for a while but I've never successfully answered.

What is the dividing line between citizen science and open-source computing?  Is there one?

The reason I ask is the book discusses the work of TopCoder.com, a web site that connects open-source computer programmers with companies looking to pay for code.  Think of this as a for-profit version of the site Github.com.  In many ways what they do is scientific and many of the same citizen scientists in our field are the same as people drawn to open-source computing.  But the two fields have never really connected and we don't often hear them talked about in the same context.  Is this just a remnant of people not understanding the fields of data science/computer science, or is there something deeper? I have ideas on some of the differences but I want to hear yours.

Let me know your thoughts in the comments below.  I'll keep answering this question online before the conference and keep this conversation going.  But I think it's an interesting discussion regardless of a future presentation.