What is Citizen Science?

Let’s start with a definition for Citizen Science. I like definitions as they provide a common understanding of what a word or concept means. Citizen Science (CS) is a collaborative scientific investigation and exploration that strives to address community defined questions where a community is engaged in the entirety of the scientific process (1). This notion of CS does not sit in isolation, but rather fits into a spectrum of activities that engage citizens in some form of data creation. 

That spectrum is broad (Figure 1) and ranges from the simple ‘citizens as sensors’ where, for example, citizens passively provide location data through an app (2). The traffic app Waze is a good example. Waze gathers location and speed data from a users phone, aggregates those individual data with all other user generated data, creating information in the form of best routes and fastest times to a destination. The citizen in this example is not actively participating, but rather passively letting Waze access data on their phone to use in combination with other people’s data. There are a number of problems with this model that include privacy concerns and the financial motivation of those who make the app (3). How do they make their money? Do they sell the data that they collect from users? 

If the broad domain of CS exists within a continuum, Collaborative Science sits at the other end of the spectrum. Collaborative Science describes community members who are engaged from the conception of the project through to its conclusion, and act as equal partners with scientists.

Figure 1: Levels of Participation in Citizen Science(2)

A great example of Collaborative Citizen Science can be found with the Mapping for Change – Science in the City Project (4). Science in the City was a collaboration between communities in London, England, and a local city council. The goal of the project was to collect air quality data in a scientifically rigorous manner and then use that data to advocate for policy changes at the municipal level. Here is a great YouTube overview of the project.

For example, the goal of the Science of the City project was:

Science in the City was initiated with the aim to increase public understanding about air pollution, its causes, and effects, amongst local residents, and how concentrations of different pollutants vary over space and time.(5)

The main ingredients of the project were (a) the inclusion of a defined community to guide the questions being asked, and help define the range of policy outcomes desired, (b) scientists who knew the science of collecting air quality (and other) data and who could train community members, and (c) appropriate air quality sensing technology. And, as evident in the quote above, the motivation of this model is “.. to increase public understanding…”. There are no financial or privacy considerations.

The results from this Citizen Science study were impressive. In brief, the Barbican study indicated that:

  1. There is a great deal of spatial and temporal variation in air quality (PM2.5 and NOx)  within the study area (Note: this is of interest because it is a small area with a significant amount of spatial variation in air quality);
  2. That ambient air quality levels of NOx were intermittently above the European Union’s guidelines;
  3. Citizens were able to track the impact of a Sahara dust storm on AQ in London! (Note: this may be analogous to a BC forest fire impact in Alberta), and;
  4. Traffic did not have as big an impact on AQ as citizens thought it would.

The final paragraph of the report offers some great insight into the power of ‘Extreme’ Citizen Science:

The project’s success was made possible by combining residents’ local knowledge and their commitment, with the technical knowledge and experience provided by Mapping for Change… Local insights gave context to the monitoring programme making the data collected more relevant to those involved, adding scientific evidence to the residents’ opinions giving strength to the voice of the community. The results of this project offer a valuable resource which can be used as a foundation to effect change and tackle the problem of poor air quality in the City of London. (6)

The outcome of the Science in the City Project highlights that we are smarter and more capable together, as a group of people with a range of knowledge and experience, than each on our own as  individuals.

References:

  1. This definition is adopted from: Dosemagen, S. and Parker, A. (2019). Citizen Science Across a Spectrum: Broadening the Impact of Citizen Science and Community Science. Science & Technology Studies. Special Issue: Many Modes of Citizen Science. Volume 32, Issue 2.  
  2. From: Haklay, M.( 2013). Citizen Science and volunteered geographic information: Overview and typology of participation, Crowdsourcing Geographic Knowledge in Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge:Volunteered Geographic Information (VGI) in Theory and Practice. Berlin: Springer.pp 105-122 
  3. Haklay, M.( 2013). Citizen Science and volunteered geographic information: Overview and typology of participation, Crowdsourcing Geographic Knowledge in Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge:Volunteered Geographic Information (VGI) in Theory and Practice. Berlin: Springer.pp 105-122 
  4. The Science in the City: The Barbican Final Report can be found here: https://mappingforchange.org.uk/wp-content/uploads/2015/08/Barbican-Final-Report-draft_12012015_edited.pdf
  5. From pp. 6 of Science in the City: The Barbican Final Report.
  6. From pp. 34 of Science in the City: The Barbican Final Report.