Debating the Roles of Scientific Utility and Personal Curiosity in Citizen Science Projects

As detailed last week, reviewing hundreds of science-based projects on the most popular crowdfunding has taught me a lot about how citizen science is viewed by the public.  I've also gained some insights into what makes a successful crowdfunding campaign and an unsuccessful one.  More on that in two weeks.  But it's also given me a lot of insight into the different types of citizen science as viewed from outside our field, and outside academia.  Perfect for better understanding the business of citizen science and how citizen scientists can take advantage of it.

The first of these is an increased appreciation for the role of curiosity in citizen science projects.  This has led me to begin considering a new model for classifying citizen science projects that shows some promise for better understanding people's interest in citizen science and identifying new opportunities for expanding the field. Applying it to our crowdfunding research and comparing the results with results from some other models we've used may provide a lot of insight.  But before going further a little background might be useful.

Some of the most important insights came from the various emails and comments I received to those posts.  One person in particular asked about the uBiome project that was funded through IndieGoGo back in early 2013.  This was quite a success story. While only requesting $100,000 they quickly doubled it and have since earned (since the campaign is still open) over $300,000.  All in addition to money they earn from sales directly from their web site.

This is a very exciting science project that has developed kits for genetically identifying the bacteria growing in each person's gut; these are sold to the public that send in their samples and receive back results on bacteria in their own bodies.  So uBiome was not just funded by the public, but it's main sales audience is the general public and their research data is derived from the public participants. It's a very good science project. But is it a citizen science project?

On the one hand the Indiegogo description itself talks a lot about citizen science and using the data as part of a large citizen science project.  In fact this brought it to my attention from the very beginning. It is also highly dependent on public participation as the primary data source that fuels their scientific research, and then returns that analyzed data back to the user.  So in some ways a user is running a scientific test on their own bodies and getting results.  After aggregating all these results uBiome will be mining the data for important and novel research on the role of gut bacteria on human health.  All of these make this look like a citizen science project at first glance, and I even included similar types of projects (Genographic Project and Wisdom Panel) which do similar things with human and pet ancestry.

On the other hand, when looking closely at the citizen science definitions I initially couldn't fit this in. It was not organized or designed by a private citizen...it is run by a for-profit company managed by Ph.D. Scientists. It does not involve citizens in the hypothesis creation or sample analysis. Even the larger data analysis is not available to public participants. They just receive their own results.  Once received, this information does not have any practical utility or potential impact on the citizen scientist.  They can't (yet) use if to make medical decisions like a genetic test would, or learn about their ancestry; it's main use instead is satisfying intellectual and personal curiosity.  The closest they can come is ordering multiple kits and tracking changes over time (or as variables like diet change) That's not a bad thing, but again it does not support the "citizen science" label.

The final argument is that by signing up and sending in their samples, the public is acting as a data collecting "contributor" in much the same way they would send in bird sightings or amateur sky observations.  This is one of the primary ways citizen scientists get their start and is the base of my levels of citizen science involvement model. And it's not just a passive involvement; in many cases participants can be very passionate about those projects and devote significant time and money to the project.  There's a great example in this week's most recent issue of Science magazine, where the author (who has written often about citizen science projects in the past) get's involved for the first time with a genetic testing project.  But it's not just for curiosity' among the many genes she is having tested include many cancer indicators that may potentially run in her family.  So she can use that data to influence her own medical choices and inform the rest of her family who may also share those genes.  Citizen science is not just a passing fancy for her; it could save her life. So this level of involvement remains an important way to participate.

There is one other important side issue here. If a person's sole contribution to a project is as a human subject, is it still citizen science. I personally would argue "No", but for variety of ethical reasons (including some with my current employer), I can't fully go into it.  But it would be a great topic for further discussion.

Ultimately they are about satisfying a personal curiosity but not in breaking new research ground. And that's not a bad thing. So I'm adding uBiome back to my Citizen Science Crowdfunding list and re-evaluating some others I'd previously not included.  So thank you all who brought these issues to my attention.

Going through all the background now leads us back to the main question..."How do we classify projects that are 'Kind of' citizen science?"  One possible solution I'm considering is looking at the scientific "Utility" of the expected research results, and measuring that utility by analyzing each project's expected breadth, utility, and novelty.  This is very much a work in progress, but in other words, 1) for academic or theoretical research, will the results be broadly applicable to many issues and the scientific community, or will it be specific to a certain person or problem; 2) for non-theoretical research,is the data useful to an individual or answering a specific problem, or is it mainly to satisfy curiosity; and 3) has this research data been created before or is new ground being broken with the research.  Those three factors should help us separate projects into the following four categories:

1. Pure Research for Scientific Advancement: Addresses an issue of theoretical, academic, or general scientific interest.
2. Applied Research and Analysis: Uses scientific research techniques to address a specific real-world problem.
3. Curiosity Research: Uses scientific research techniques to answer an unknown question with little direct practical impact. On the citizen scientist?
4. Scientific Activities:  These do not generate any new information and the results do not have any direct application; instead the activity has educational or non-practical goals.

It's important to note that these classifications by no means indicates "better" or "worse", or that one is more "worthy" than another. Instead I think it's useful in helping people expand their definitions by providing a structure to view these alternative models with.  I also think we can build this out and find some intriguing insights on things that work best in one model but less well in others.  So it should have a practical purpose. And hey, creating models is academically interesting too.

Will this model be useful?  Am I making distinctions that don't exist?  Are my definitions to narrow or are my biases showing?  Let's test the model and find out.  I'll start working on that now and present the results in a future post.  But if you have your own thoughts let me know in the comments below.