Conference on Public Participation in Scientific Research, Day 1 Session 2 – 8/4/2012
To Use or Not To Use: Is That the Data?
Examples of PPSR biogeography – huge collections with enormous monetary value. Can go back to the 1800s to understand egg laying for phenology changes. Everything was fine with older data – 800K eggs have been digitized, but newer data is problematic because eggs couldn’t be collected. So now nest record cards need to be digitized. These data were used to save peregrine falcon and brown pelican from DDT risks.
Starting in Victorian times, people were interested in learning more about what they saw but no field guides available – so Arm & Hammer distributed species cards in their baking soda! Has evolved into Christmas Bird Count through a circuitous route.
Once data were computerized, they started to find data could be used very well to answer RQs. Birdwatchers knew more about irruptive phenomena than scientists, probably caused by climate. Was then able to look at distribution and abundance from CBC data and find out the range change for species.
Many other data sets go way back, priceless info saved by hiding under a mattress! Many of the historical data are in private and museum collections. Big growth in large long-term datasets that are badly needed to address big questions. We are now poised on the edge of a huge explosion of data, but what does misidentification mean for data quality? We used to throw away these data, but now we can use smartphones with cameras and social networks to get info about many things from large number of people into scientifically useable datasets. iNaturalist a great example of how this is working really well – already seeing exponential growth and going viral soon. 3 yo can use it and get excited about finding out what a species is.
The Role of “Citizen Science” in Weather and Climate Research
Early traditions of weather observation started in US by Ben Franklin and Thomas Jefferson. They communicated to try to understand what was going on, but didn’t have spatial and temporal context. Smithsonian project from 1849 introduced new technologies, telegraph to share weather observations.
Analysis and interpretation of volunteer data more difficult than recruiting volunteers, getting as many as 500K data points/year, which was when standardization became a big issue. Took 12 years to report on the data, so volunteers had to be very patient.
Colorado state weather service started establishing state-based weather observing networks in the late 1880s with only $2K. Within 10 years there was a solid reporting network, led to nationwide “Cooperative Network” that continues today. First purposes were simple – climate resources of the country, particularly what crops could be grown where and when, also equally important to predict extreme weather.
In bigger picture, most of the data are very skewed geographically, but a very impressive foundation. Many applications, both scientific and practical, such as climate and health – “a stinking big deal.” Have learned from historical data that there are weather cycles that is helping model weather. Dustbowl and depression increased interest in weather and climate, advanced use of volunteer data. Majority of drought monitoring is from citizen science.
Naturally this leads to understanding climate change – CoCoRaHS is keeping this going. We need more rain gauges and finer granularity of placement.
Foldit and Games for Scientific Discovery
Many people playing video games, what if we could direct that to solving problems for science? Combining human and computational power, as well as a way to motivate people to engage and solve problems they didn’t think they could contribute to.
One area where there’s lots of potential is biochemistry – proteins and protein folding. Very important part of life. Two ways to look at it, sequences and 3D structures. Hard to solve folding problems algorithmically. Foldit lets gamers use the 3D visualizations and both human and computational tools to solve problems. Have had 250K people play the game, over 100 protein structure puzzles.
Scoring and leaderboards help promote competition which motivates gamers. Technical structures are complex, but robust for solving difficult puzzles. Constantly releasing new features and bug fixes, and giving players feedback. Worldwide community participating, multiple languages. Players have produced very exciting results, protein related to AIDS virus in monkeys, algorithms failed but players succeeded in 3 weeks!
Ended up implementing scripting structure for “recipes” so players could reuse functions – player algorithm independently discovered scientist algorithms, perform better! Made trophy for early winning player, keeps it on his desk. Also co-creating structures, now making interface tools for scientists – when tool is fun and easy for everyone, also useful for scientists.
The Many Benefits of PPSR
CBPR – community based participatory research – no research on us without us. Academic research may not be the right way to address problems.
Working with tribal groups on emerald ash borer in Maine – not many ash trees but they are critical to tribal traditions and economic opportunities. CBPR is growing just like citizen science – there are organizations, journals, and grants for training and cross-disciplinary support.
CBPR successes – adding rigor to data collection, need to merge professional and local knowledge to solve problems. Example from tribal lands in Nevada about nuclear contamination – researcher vector model didn’t take into community food sources. Other examples of ways that community knowledge is strengthening scientific outcomes, e.g. incinerators and air quality household health studies – very concerned about children but had concerns, wanted dialogue with researchers. Similar outcomes in emerald ash borer studies, nutritional studies.
Linking knowledge to action by bringing in local stakeholders; federal research agencies/foundations reviewing proposals differently to promote broader impacts. Using research cycle as tool to understand issues that emerge at each stage. Many questions remain about assumptions and unknowns.
Lots of resources at http://CCPH.info.