Via GenomeWeb's Daily Scan, some comments on the prospects for citizen science in The Chronicle of Higher Education.

Only one of the three appears to be an actual research scientist, but they make good points about the role of citizen science in research. For example, Clifford A. Lynch, Director, Coalition for Networked information:

I'm not wild about the term "crowdsourcing" and I think it's actually important to disentangle the developments.

One is the harnessing of massive citizen or crowd observational capabilities through distributed IT, sensors, and networking technology, keeping in mind that the human sensory system and the brain are incredibly powerful and versatile data collectors.

A second is the renaissance of what might be called amateur science (science purely for the intellectual love of it, as distinct from the highly professionalized and career-oriented science of universities and industry) that's enabled by the deluge of highly accessible data, powerful low-cost observational, computational and experimental gear enabled in part by digital technologies, and the ability to collaborate and disseminate results globally using the web.

Both types of contributions can be useful in particular cases.

However there is a risk of misunderstanding how science actually works here. In most examples of citizen science I've seen, the citizens are not actually doing the same type of science that is done by a professional researcher who runs a lab, writes grant proposals, and gives conferences. That is: citizens contribute by data collection, or more or less routine data analysis.

Routine doesn't mean boring or unimportant; what it means is that it is something done within a research framework set up by someone else who has great expertise in the overall field - someone who defined the important big question to be addressed, who came up with the big strategy for addressing that question, such as choosing one methodology over another, and someone with the technical chops to make persuasive arguments aimed at convincing the other professionals in the field.

Stuff like GalaxyZoo is a great way for everyone to participate, but someone had to lay out a rationale for why galaxy classification is important in the first place, and decide what characteristics galaxies should be classified by - basically what kinds of important questions will be answered by GalaxyZoo.

In other words, participation in these large projects is no substitute for understanding how to design your own project - how to identify an important question, formulate clear hypotheses, design experiments to test those hypotheses, and interpret what the results mean for your original question without fooling yourself. That needs to be taught in schools, through science reporting, and maybe via science fairs for interested amateurs who finished school long ago.

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