A few months ago I posted a long series of blog articles on the keys to successful citizen science projects. It identified a number of major and minor themes that helped them attract users, develop good data, and lead to publishable results. But now that I've created this model...does it really work?
To start testing the theory I've organized all the projects previously featured on this blog and ranked each from 1-7 using the various success criteria. I chose 1-7 since it would allow a firm mid-point (for "Average" success on that trait) and would allow some differentiation between the poor performers (1-3) and high performers (5-7). Unfortunately I'm not confident that I can personally fine-tune the rankings much further to justify a 1-9 or 1-11 scale, but this should do for now. All this will let us create mathematical model that will hopefully predict overall success of a project, as discussed below. But first we need to validate the rankings.
You can find a full document with the traits and individual rankings HERE. I've created locked-down and public version of the document, so feel free to mark it up and add any important notes you'd like. Whether you disagree with the rankings or just want to know how each was evaluated, let me know in the comments section below or in the document itself. Only by working together can we create a model that works.
Finally, last week I asked everyone how to define "Success" in a citizen science project. I received a few good answer, like looking at number of publications (success from a scientific viewpoint), active users (from a participant viewpoint), or search popularity (from a marketing viewpoint). But I'm curious to hear if there are any more ideas? Let me know now as I look to evaluate the success of projects through some quantitative measures.
FOR MORE ON THE PREVIOUS SERIES: