Annette Olson is helping AAAS engage the science-fascinated citizens who were a force for AAAS and science in its early years.
William Redfield, who as the association’s first president in 1843, was a steamship company owner whose interest in weather led him to make some of the pioneering observations of how hurricanes behaved. Today, as many as one million or more volunteers already help scientists gather and share data, and AAAS CEO Rush Holt has called that revival “one of the important movements in science today.”
Olson, a biologist, has been involved with public-aided research (i.e., where public citizens volunteer time and sometimes resources to help with scientific research) since her early work studying African mongooses. After stints at the National Zoo and the U.S. Geological Survey, also involving projects aided by the public, she joined the AAAS Research Competitiveness Program in 2012, where she leads panels to assess and guide research programs. Last year, she formed an employee AAAS interest group on citizen science, which is trying to find new ways to enlist and engage the public in AAAS-related projects and research.
What does AAAS consider “citizen science?”
Actually, that’s one of the first questions we need to clarify among ourselves, as there is quite a range of definitions.
One of the things about citizen science is that it doesn’t just include the commonly thought of scenario, where adults and schoolkids are trained by scientists to collect biological field data, such as sampling for insects in stream communities. Citizen Science may also include activities such as providing one’s computer to automatically run computations behind the scenes (especially at night), thus creating greater bandwidth for analyzing data. Some consider that citizen science, some do not — but this effort can assist scientists in their work. Recently, there has been the gamification of data analysis: public citizens can play games that help solve research questions.
But critically, the data can also be for citizens and communities. For instance, “Crowdsourcing” doesn’t necessarily have the training component — though there can be some training involved — instead it depends on a crowd of participants to help get the most likely answer. For instance, one can upload a picture of a plant to a website and ask the crowd to identify it. Tons of people volunteer, especially people with a love for plants, to identify the plants. Examples include local list-serves and Facebook groups like Texas Flora, and more regional and national groups, like Bugguide.net, which helps provide identification of insects, and iNaturalist, which covers a broad range of species.
Then there’s the type of citizen science where patients or public citizens are involved from the initial design of the experiment through to the data collection and interpretation of results. This is starting to happen a lot right now, especially in health … Patients say, "I have this disease. I want to help fight this disease," and then, in collaboration with a scientist, they help design experiments. They may volunteer for experiments, or they may help with the interpretation of the data.
Theresa Harris, a Project Director in the AAAS Scientific Responsibility, Human Rights and Law program, has in the past few years been getting requests from citizens — she’s worked with some in Colombia and Mexico — where they feel there has been a human rights violation. They want to know how to determine the extent of the problem, and study how to improve a situation. She has worked to bring in scientists to work with these citizens to train them on how to collect and interpret the data.
A lot of early science was citizen science. What’s changed for lay people as the disciplines have become more professionalized? What’s the potential today?
There’s a lot of work going on where research is very professional, i.e., it has to be very detailed, well-funded over a length of time, and peer-reviewed. In other words, it needs a specialist employed full-time to conduct the research. But there’s still this remaining strong component of people who are vastly interested in science. There are those who assist scientists, and they generally are called/call themselves citizen scientists, but there are also people who consider themselves hobbyists. They can make valuable contributions — as we have seen in the news with amateur astronomers, and people sighting rare species, but where they publish is generally different, because they don’t do so much peer review. Now they share their information more on blogs or some similar sites.
My gut reaction is that there is a even-broader community of people who are vastly interested and who can contribute to science. I think of a birder friend of mine, who keeps a record of birds she has sighted, but she doesn’t do anything with it — she’s just very fascinated with it. Now, with the Internet, there’s more of an opportunity for people to learn more about what they are discovering, but also for people to share and discover each other’s data. Data is being mined from Flicker about bird distributions, for instance, depending on the level of detail and permissions with the photos.
How does your own background inform what you’re doing now?
I used to be a field biologist. I got a doctorate at the University of Miami and studied mongooses in Africa for about a year and a half. There I hired and trained some local people to help me radio track mongooses, but I also had volunteers help with data collection occasionally.
Then I came to the National Zoological Park in D.C. and studied the same species of mongoose there for a while. I worked with two student volunteers who helped me collect behavioral data, and it helped tremendously; as I could set up double-blind experiments, and their data collection helped save months at least in the experiments. My work at the zoo helped lead to a position at the National Museum of Natural History for about eight years, with the last five as a specialist in the Mammal Department bringing in the research and helping design the Behring Family Hall of Mammals.
That work gave me a lot of background in how to communicate with the public. But there are only so many biology exhibits a museum can build, so after that, I went to the U.S. Geological Survey. I served as the liaison between the scientists and information technologists pulling data together mega-data sets that could be used for meta-analysis. Many of these data sets had citizen science contributions. A lot of the data I was looking at were from people collecting data about species distributions — “I spotted a peccary here in Arizona,” or “I spotted a butterfly here.” I didn’t work so much on invasive species, but that was a big component of our program, as it can be critical to have early detection of and information about invasive species, to yield a rapid control response. So-called early detection — rapid response (EDRR) tools were being built while I was there.
What are some of the most popular fields for citizen science? Have those changed recently as some subjects get more attention?
I would say it’s ecology, medical, and water quality. Water contamination and pollution is a big area … Another aspect is education; AAAS has a long history of collaborating on education projects with aspects of citizen science. Most people in some way are engaged in wondering about their environment. And with smart phones nowdays, that’s a data collection tool in many respects. People have access to more tools. It’s a really exciting time.
What are some of the barriers citizen scientists face, and how can we overcome them?
That’s one of the reasons we’re talking to citizen science organizations, especially the Citizen Science Association. We have representatives on the committee from many different groups with AAAS, and we’re trying to find out what the needs are in citizen science so AAAS can potentially help.
For example, there’s always a variety of data collectors, and one of the key things is to make sure you’re using the same terminology, the same data collection techniques, and that the data are then strong. Some groups are going to rely on just anecdotal data, whereas multiple other groups may collect twice a day, but at different times, and you’re trying to merge these data sets.
Merging of the data is a huge issue. It’s what I focused on at USGS for eight years. The Citizen Science Association has a data quality working group, and we’re hoping to make their resources available through an online AAAS citizen science community.
But also having the time and resources to train citizen scientists is important. The people involved really want to learn, but they also bring tools and capabilities. There are always citizen science efforts at national parks, but the question is, are there enough people to help the citizen scientists help science? AAAS can help mobilize experts to help answer questions like this, and even provide training, as mentioned earlier.
I do know that, in general, projects don’t lack for volunteers. People are interested in not only helping support science, but in being part of it.
We just saw an example of an amateur astronomer scoring a first — capturing the first burst of light from a supernova. How often does something like that happen these days?
It’s actually quite common. It’s just there are different fields where it’s less likely to happen — in medicine, for instance. In ecology and environmental science — in Flint, Michigan, for example, the discovery of lead-contaminated water was a result of citizen scientists starting the process, then they brought in a scientist to help.
When I was at USGS, I worked a lot on ecological situations, and one of the things I focused on was species data. As part of that focus, I created an image library, where anybody could upload images they thought might be scientifically relevant. There were amazing discoveries there, like sightings of giant armadillos in places nobody thought of … changes in habitat over time were also very useful. Right now, a great example of citizen science in the field is the example of the National Phenology Network. It’s volunteer supported. People around the world are recording when flowers start blooming. Having repetitive data annually and by a variety of people helps build the data for that.