In the upcoming blog mini series, COMPAIR will examine potential risks and compliance challenges that projects may face when running citizen science campaigns. We will start by looking at citizen science as a tool for civic engagement (blog one), then will draw some lessons from successful projects and best practices in the field of air quality monitoring and mobility (blog two), before finally concluding with recommendations on how to tackle specific risks and challenges linked to ethics, privacy and data quality (blog three).
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What is Citizen Science?
The European Citizen Science Association describes Citizen Science as “an umbrella term that describes a variety of ways in which the public participate in science” (ECSA, 2022). This definition points to different important aspects about what can be understood by Citizen Science. There are boundaries of what can be considered Citizen Science. At the most basic level, to be considered Citizen Science there has to be some contribution/participation by non-professionals (citizens) to scientific activity or research (Haklay, 2013; Haklay, et al., 2021). Depending on the project, citizens can volunteer in every step of a research project: data collection, analysis, problem definition or dissemination (Land-Zandstra, Agnello, & Gültekin, 2021). Important to note is that participation in Citizen Science differs from being a respondent in a survey eg. However, by calling it an ‘umbrella term’ the ECSA description also illustrates that it’s difficult to construct one all-encompassing definition of ‘Citizen Science’. A lot of different definitions and descriptions of what is understood by ‘Citizen Science’ can be found (see Haklay, et al., 2021, p. 15-18 for a limited list).
The fact that a lot of different definitions exist also points to certain specific aspects of Citizen Science. The practice of Citizen Science is not limited to a certain academic discipline. To a certain extent the roots of Citizen Science can be traced back to environmental research. A lot of Citizen Science projects can still be found in this field, but nowadays Citizen Science has been applied in virtually every scientific discipline, from humanities and social science to medicine to natural sciences (Haklay, 2013). The definition that someone uses in general tells something about the perspective or idea of the project. In that sense the lack of one single definition is an advantage. It makes it possible to include a variety of different approaches to Citizen Science. Every Citizen Science project needs to create its own identity within the basic boundaries of Citizen Science (Haklay, et al., 2021).
Since it is explicitly part of the scientific process, the goal of Citizen Science projects is to generate knowledge. However, in a sense Citizen Science challenges our preconceived ideas of the way knowledge is produced and who can produce it. As mentioned above, modern science is structured around disciplines and subdisciplines. These are generally highly specialised and have their own traditions and practices. Citizen Science cuts across these structures and in that sense challenges them. Within academia, very strict protocols that describe the ‘correct way of doing science’ are used to limit uncertainty in the scientific process. The practice of Citizen Science shows that uncertainty is an integral part of data collection and that you don’t have to be a long trained scientist to contribute to scientific data collection (Haklay, 2013). This can be seen also in the fact that Citizen Science projects can be initiated by different actors, both from within and outside academia. Not only scientists themselves, but also government agencies, civil society, NGO’s or individuals can take the initiative for a Citizen Science project.
Several rather recent trends made the growing popularity of Citizen Science possible (Haklay, 2013). Firstly, there are technical evolutions that contributed. The growth in internet connections makes it easier to register observations. Smartphones on the other hand are having more and more features that can be used to make observations without much effort (think about GPS, microphones,…). Secondly, thanks to the growing educational levels more people become familiar with scientific practises. Besides, we see a bigger interest in scientific research although it is not part of people's day to day job. Thirdly, an increase in leisure time outside of working hours makes it possible for people to act upon this interest and wish to contribute to scientific research. These trends opened up possibilities for participation of non-professionals to the scientific practice that are new. Citizens can now engage in research with more ease and in a higher number of ways than before.
The above shows that practitioners/people involved have to make clear from the beginning what is understood by Citizen Science in their project (Haklay, et al., 2021). In other words, it should be clear how and to what extent citizen science participants are involved and participate in the project. As we have seen, all Citizen Science projects have some form or level of participation or engagement. It’s therefore important to think about how citizen participation can take form and what kinds of participation exist. These lead to different kinds of Citizen Science projects. The next paragraph delves deeper in the question of participation in Citizen Science.
Participation in Citizen Science
To have a clear picture of Citizen Science, it’s important to look at the meaning of participation within a Citizen Science project since “participation is the differentiating element between what is now called Citizen Science and public engagement with science” (Haklay, 2018). In part, thinking about participation is thinking about the relationship between professional scientists and the wider public. This relationship is historically complex and a gap between both exists. Like already mentioned above, participation of citizens in scientific research challenges the idea that only full-time professional scientists can produce knowledge. However, this doesn’t mean that the need for ‘professional science’ will disappear. In general, citizens still acknowledge the expertise of scientists, but they build their own expertise (Haklay, 2013). This stimulates scientists to think about how they relate to the wider public. Citizen Science is about citizens as scientists, but also about scientists as citizens. A first step in thinking about participation and engagement in Citizen Science is about who exactly it is that participates.
Who participates
In theory, everyone can participate in a Citizen Science project. However, in practice we see that not everyone participates equally. The drivers of the growth in Citizen Science that we’ve mentioned also explain in part the Participants of Citizen Science projects are “predominantly male, well educated and from higher brackets of the income scale” (Haklay, 2013). It is well documented that educational level is a driving characteristic of who participates in Citizen Science, whereby higher educated participate more. This is especially true when the complexity of the expected tasks becomes higher.
Participants with a higher educational level can be an advantage for a Citizen Science project. By engaging with Citizen Science, it becomes possible to harness the research skills and knowledge of a higher (and longer) education for a socially beneficial outcome. On the other hand, it shows that Citizen Science doesn’t reach the entire population sufficiently, which is important if the goal is to engage every group of society. It is clear that the question of who participates/about the characteristics of the participants is closely related to what is expected from them. Citizen Science projects differ in the kind of tasks they ask citizens to conduct. For example, volunteers can contribute actively (by consciously recording observations eg) or passively (by acting as an observation platform). This leads to different levels of participation or engagement (Haklay, 2013; Land-Zandstra, Agnello, & Gültekin, 2021).
Levels of participation/engagement
Haklay (2013) made the following typology of participation within Citizen Science, depending on the level of engagement of participants in the project:
Figure 1: Levels of Participation in Citizen Science (Haklay, 2013)
At the basic level, citizen science participants act as sensors, by carrying around sensors or sharing GPS data e.g. This means that at the cognitive level, their contribution is very limited. This is the difference with the second level, where the cognitive skills are being used by asking participants to do some interpretation of the data they observe. Participants often receive a basic training to enable them to do the required tasks. At these two levels, participants only engage in a data collection process developed by scientists. This changes on the third level, where citizens are engaged in the problem definition and, together with scientists, develop a data collection method. When participants are also involved in the data analysis and dissemination of results, we talk about ‘extreme Citizen Science, or collaborative science’. This fourth level involves citizens in all parts of scientific research. Scientists often act as facilitators rather than experts at this level (Haklay, 2013).
With this ladder of participation, it’s possible to describe the level of engagement of volunteers within a Citizen Science project. Practitioners should find the most appropriate level of engagement for their project. Not all projects should strive for the deepest level of participation or engagement. This also means that there is no value judgement attached to the different levels or the position of a project on the ladder (Haklay, 2013; Land-Zandstra, Agnello, & Gültekin, 2021).
Projects can differ on their level of participation, where they are at the ladder or can move from one level to another during the course of a project. Not only between projects or over time the level of participation can change, also within a project at a certain point it’s possible to find different levels of participation. This points to something called participation inequality. This means that not every participant contributes to the same extent to a Citizen Science project. Moreover, in practice often only a small number of the people subscribed make the most of the contributions. This has positive consequences, like some participants being very committed to the research and becoming experts in the subject matter. On the other hand, it also has possible negative consequences in the fact that the level of engagement of most participants is often rather limited (Haklay, 2018).
All the above points to the advice to look for the most appropriate level of engagement, both for the project as a whole as for different groups of participants. Projects should strive for the highest level of engagement suitable for the project. Furthermore, if appropriate projects should enable participants to be engaged on different levels with a project and to switch between levels during the course of a project. This can stimulate people with different interests to participate. Different participants require different approaches to engage and motivate them and the level of training necessary to participate (Haklay, 2013; Land-Zandstra, Agnello, & Gültekin, 2021; Senabre Hidalgo, et al., 2021). This leads us back to the fact that Citizen Science deals with uncertainty in a different way. Data collected through Citizen Science is heterogeneous, meaning that data quality might vary according to the number of participants, their characteristics, level of engagement or training required to contribute. This shows that from the start, initiators of a Citizen Science project should carefully consider how participation and citizen engagement, the core of Citizen Science, will look like in the project.
References
ECSA. (2022). What is citizen science? European Citizen Science Association. https://ecsa.citizen-science.net/
Haklay, M. (2013). Citizen Science and Volunteered Geographic Information - overview and typology of participation. In D. Sui, S. Elwood, & M. Goodchild, Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice (pp. 105-122). Berling: Springer.
Haklay, M. (2018). Participatory Citizen Science. In S. Hecker, M. Haklay, A. Bowser, Z. Makuch, J. Vogel, & A. Bonn, Citizen Science: Innovation in Open Science, Society and Policy (pp. 52-62). London: UCL Press.
Haklay, M., Dörler, D., Heigl, F., Manzoni, M., Hecker, S., & Vohland, K. (2021). What Is Citizen Science? The Challenges of Definition. In K. Vohland, A. Land-Zandstra, L. Ceccaroni, R. Lemmens, J. Perelló, M. Ponti, K. Wagenknecht, The Science of Citizen Science (pp. 13-33). Springer.
Land-Zandstra, A., Agnello, G., & Gültekin, Y. S. (2021). Participants in Citizen Science. In K. Vohland, A. Land-Zandstra, L. Ceccaroni, R. Lemmens, J. Perelló, M. Ponti, K. Wagenknecht, The Science of Citizen Science (pp. 243-259). Springer.
Senabre Hidalgo, E., Perelló, E., Becker, F., Bonhoure, I., Legris, M., & Cigarini, A. (2021). Participation and Co-creation in Citizen Science. In K. Vohland, A. Land-Zandstra, L. Ceccaroni, R. Lemmens, J. Perelló, M. Ponti, K. Wagenknecht, The Science of Citizen Science (pp. 199-218). Springer.