Participative Science: Encouraging The Best In Citizen Science


A quick introduction from Will Grant, Peta Ashworth and John Le Salle kicked this workshop off; we could see butchers paper, post it notes, pens and a whiteboard at the ready.

To get us focused, Will asked: How can platforms of citizen science better engage people in science? What have been the failures and successes; the impediments and solutions?

After a quick question about the definition of citizen science (good question!) a Wikipedia search as a rough starting point said: “Also known as crowd science, crowd-sourced science, or networked science, citizen science is scientific research conducted, in whole or in part, by amateur or nonprofessional scientists, often by crowdsourcing.”

John Le Salle said to not worry about the definition so much and Will exclaimed “Embrace ambiguity!”.

We broke into groups of about ten around our tables to discuss and identify our top three impediments. Butchers paper, pens and post its distributed and at the ready – check!


Some of the impediments discussed at my table included:

  • unclear values for getting involved in citizen science project, from both sides: researchers and citizens
  • competing commitments and interests and changing motivations resulting in projects not succeeding
  • the logistics: infrastructure, technology, how do people actually do things that are valuable
  • the risk of ‘real’ scientists losing their job as science outsourced to volunteers (one person at the table said that at the zoo she works at there are more volunteers than staff?)

Some visits from the Brains Trust helped us get to the top three impediments to go onto post it notes. John Le Salle said “the whole goal is getting people engaged in science. If the problem is we don’t have enough people volunteering – lots of projects but not enough people; how do we get a ten-fold increase in participation?”


After adding our top three impediments to the whiteboard the different groups talked through what they meant. We then split into smaller groups to conduct a magic mix-up of impediments, choosing three impediments that you didn’t come up with in your original group and then workshop solutions to the impediments.

  • Impediment: not knowing what to do, how to input data to website etc.

Solution: Training, sharing of knowledge. Could set up communities to support people working on these projects. Could have a formal working group looking at citizen science to share policies and grow awareness of the options for citizen science.

  • Impediment: workplace health and safety risks

Solution: clear guidelines, communicating limits to project so that people aren’t going too far (eg. walking off a cliff following a bird)

  • Impediment: expectations unknown or not met

Solution: Ensuring there’s a clear plan for the project, good communication throughout the projects so everyone knows their role and what they are getting back as the project progresses. Really working with citizens participating, scientists, wider stakeholders (eg. funders) so that there are clear expectations.

  • Impediment: Scientists trusting data and the citizens

Solution: show benefits and value and having case studies is a really important thing.

  • Impediment: lack of investment

Solution: funds for getting these kinds of projects up. Partnerships so that benefits outweigh risks.

  • Impediment: participation

Solution: access to different ways to get involved, fun, rewarded, easy.

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Everyone in the room was then invited to vote on the solutions they thought were the most important and these results will be amalgamated with the results for session two and discussed on day 2.



Still wondering about some cool citizen science examples and the impact this crowd-sourced science can have? Here are a couple project examples we heard people talk about?

  •, a citizen science project to report possible sightings of the parasitised bees in USA (
  • SETI project public volunteer computing project where people leave their playstations on to contribute their computing power to analyzing radio signals
  • Protein folding game. Citizen scientists solved the puzzle in 30 days whereas the researchers took 30 years. Games is a great way to do this.
  • Finding new galaxies among the stars by either providing computers to boost the computer power or actually looking at images and helping to classify them.

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