|Photo Courtesy: Richard-G|
In some ways this is simple...you can't put science in the hands of amateur citizens without believing in them. That's obvious. But it hits on many more levels than just that. For even if a project scientist has faith in the public's ability to collect data, but doesn't trust them enough in these other ways, the project still won't be successful. So let's take a quick look at these, shall we?
- Encourage Dialogue: Actively listen to your users. This doesn't mean just allowing comments and paying lip service to getting feedback. It goes further by acting on the comments and taking particpant ideas to heart. If they see problems with the data or flaws in your project, use their help to improve the project. If they identify hidden trends or come up with alternative hypotheses to those you are testing, follow up on those leads. Not only does the science benefit but showing users you take their comments seriously provides respect and encourages them to continue participating. We saw this in the Hanny's Voorwerp case where project scientists actively encouraged an active community of users and built in systems for users to report "oddities" in the data. One of these was noticed by a young high school teacher intrigued by an eerie green glow in Hubble telescope images...this turned to be an undiscovered quasar illuminating a stream of interstellar gas. Not bad for a volunteer! As any good husband/wife will tell you, it's not enough to hear your partner, you have to listen to them.
- Provide Data Access: Projects need to both give and take. In other words, don't make participants work hard to provide data and then just hoard it for yourself. Let them take advantage of it too. Not only is this "fair", but it let's researchers gain insight from citizen scientists in he field who may provide creative insights into them. It also helps them do their job better. They can see where potential data quality issues can crop up and can alter their techniques accordingly. It can even help them maximize their data collection. For example, FireflyWatch project asks users to report the location and date of firefly sightings across the country. The project also makes this data available to all it's users. By looking at the first and last sightings of previous years, participants can time their observations so they don't miss the first sighting of the season and that they stick around long enough for the final sightings. All ensuring the most complete set of observations possible.
- Allow for Errors: Trust the people AND the crowd. For many projects the observations and analyses performed by citizen scientists are very complex. No matter how much projects train users the work can require levels of precision and practice not available to the average user. So researchers may be understandably afraid to trust users to provide accurate data. But we've seen time and time again that even if individuals user data is off, the collective wisdom of the crowds can be spot on. Don't be afraid to trust the combined data of users. When averaged together it can be just as precise, if not more precise, than alternatives using computers, experienced scientists, or overworked graduate students. The Agent Exoplanet project is a prime example. Volunteers examine star data for signs of changing brightness and to track tiny motions across the sky. This creates "light curves", and the more accurate the light curves the orbit calculations of far away planets become more accurate. The project scientists have repeatedly tested user results against their own results from well-trained observers, and the citizen science data has proven itself many times.
- Be Audacious: Don't be afraid of challenging users. Just because citizen scientists don't have the experience level of trained researchers doesn't mean they can't do big things. For starters, relying on the crowd of citizen scientists to collect data and "cancel out" each others errors makes big project possible. And some participants flock to the excitement and challenge of difficult projects. For example, I will soon blog about the Sungrazer project for detecting comets around our sun. Using the NASA SOHO satellites, participants download image data on a real-time basis and use photo editing software to spot potential comets. These appear as bright pixels and can be tracked through a series of consecutive images. While this project requires some work by volunteers to set up the programs and patience to comb through each, it has been highly successful as over half the discoveries have come from citizen scientists. It was never even designed as a public project...users just let loose their creative energy and accepted the challenge on their own. So scientists should not be afraid of big projects...trust the volunteer community and they will help you do great things.
Finally, I'd love to hear more from you on this post or any other in the series. I gain new insights each week and hope to keep revising them as the issues become clearer. But I can only do that with your help. So please, leave your thoughts/ideas/compliments/criticisms below. The more minds participating the better!
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