Data quality is one of the main concerns of the citizen science community. Working group 1, led by Bálint Balázs, aims at providing a sound understanding of the current practices involving the collection, description, and validation of data gathered and analysed by citizens.
Bálint is Senior Researcher and Executive Manager at ESSRG, a small Hungarian research and development enterprise working on the boundaries of environmental and social sciences. He has extensive experience in food system research and participatory practices.
During the last coffee break of the Erice Training School, in which he participated as a speaker, we had the chance to chat with him about his interests and points of view on the current trends in the field of citizen science.
What is, for you, the best definition of citizen science.
Citizen science is a passionate methodology for doing proper research and produce scientifically robust findings. For me, it is an ideal way of doing research because it sets you in a very reflective mode which helps you discover problems and make them explicit.
There are multiple ways to engage public perspectives and public knowledge in scientific discourse and in policy-making. Citizen science is a specific form. I advocate the social role of citizen science, that is, to provide empowering tools for citizens to develop solutions to the problems of their communities. In this sense I tend to see it as an approach to social innovation and socio-technical transitions.
Therefore, I would like to promote the idea that citizen science is much more than public engagement or informal learning. I sympathise with these ideas, but I think citizen science needs to be established as a participatory methodology for doing science: a passionate and collaborative way to do research.
Which field of citizen science are you most interested in.
I see my role in providing a critical understanding from the perspective of the social sciences and trying to be helpful in developing a robust methodology. Bringing back the social aspect into the environmental citizen science is one of my primary interests.
I am also an enthusiast of citizen social sciences, which is a less visible part of citizen science that directly works with social sciences and humanities. As part of the InSPIRES project, I also seek ways to rejuvenate the science shop concept.
You often talk about the invisibility of citizen science, what do you mean?
For decades citizen science was invisible for most professional scientists and policymakers. To avoid distrust of colleagues and resistance from policymakers, many professional scientists have often published their results completely hiding the fact that they were working with citizen scientists. Fortunately, this has changed, as it is now more acknowledged that citizen science practitioners and professional scientists can learn a lot from each other.
The second type of invisibility of citizen science is experienced in social sciences and humanities, as most citizen science projects are in environmental and natural sciences.
Finally, there is invisibility of citizen science practices in the non-western countries. In many central European countries, even the term is not recognised. This apparent division in the performance of citizen science between eastern and western countries reflects an unequal knowledge production.
Is citizen science perceived differently throughout the different cultures in Europe?
Completely different understandings of citizen science are embedded in different science cultures. My arrival to the European citizen science community goes back to my personal experience that the term has travelled unevenly across Europe. In most western European countries, it has become trendy and well-funded. But, in the east, these initiatives are silent; hardly any projects can be identified that use the term for self-definition. As the word has limited acknowledgement, neither researchers nor citizens are very much involved.
In my country, Hungary, citizen science is also in its infancy. We have partnered with a digital civic technology platform through which citizens can report malfunctioning public services in the city. Járókelő is a Hungarian version of the FixMyStreet app. By linking problems perceived by passers-by with the responsible authorities, this initiative is actually creating citizens. People who otherwise would only be passers-by become citizens. When you participate, you co-create the urban public services. Finally, it is also creating entirely new knowledge and learning communities about the city.
Associations and networks such as ECSA, or our Cost Action, have been born in recent years all over the world, also at a national level. What do you think their role should be?
Their central role is networking: to create learning communities that help us become better citizen scientists. The secondary role is outreach and upscale: they should promote as much as possible the involvement of scientists and practitioners from areas where citizen science has not yet flourished.
What would you say is the major challenge citizen science is facing?
Data quality is and will be for a long time the primary challenge for citizen science. There are plenty of reasons why data quality can go wrong and make the validity and reliability of results flawed. Often, we see that there is hardly any protection against users who do not respect data collection protocols. Also, the low-cost sensors themselves create inaccuracies and cause abandonment from users. Protocols need verifications from broader use-contexts, authorities and stakeholders.
We are in a relatively early stage in the development of data quality standards for citizen science. Citizen science has a lesson to learn from the replication crisis that led professional science to completely re-visit its classic results, for example, in social psychology or medicine. From the very beginning, citizen science should make data open and emphasise triangulation of data. If you think of Wikipedia, you will realise that citizen scientists are usually eager to help identify and validate other citizen scientist’s observations, so this could easily be an inbuilt mechanism of any project.
As for usability, expert verification is usually expensive, but varied stakeholders can participate in data curation partnerships. In several initiatives, the mobile sensors can offer integrated data assurance mechanisms, filters, qualifying and reputation systems.
As a sociologist, I see data quality as a key legitimacy factor in citizen science projects. Data quality is probably the top priority to upscale citizen science and to gain more recognition from fellow scientists, decision makers and various stakeholders.
You are Chair of Working Group 1, which focuses on data quality. Can you tell us about the work is being done there?
The practical goal of our working group is to learn how we can ensure the validity and reliability of citizen science data. What are the mechanisms that provide high-quality data from participants, so that citizen science produces fit for purpose data in all possible intended use domains.
In a more philosophical tone, we seek to understand how citizen science data could more correctly represent the real world to which it refers. Since citizen science is now entering a new phase through mass-produced citizen science datasets, the data consistency is becoming a challenge.
Similarly, data completeness, availability, validity, timeliness and accuracy are essential. All in all, it is hard to define what is the essence of data quality in citizen science as there are several dozens of such terms with little agreement in their definitions or measures.
We foresee as the first output from our working group a data quality review tool, a harmonised approach to data quality assurance across different citizen science projects.
Some of your work as a researcher is on food systems. Could you tell me an example of citizen science in this field?
There is a new call under the Horizon 2020 program that looks into citizen science in food systems. But, apart from this, citizen science is not very often considered to address meaningful research questions about the challenges of our food system. Mostly, citizens are invited to collect data on pollinators or pests.
One initiative that I particularly like is called Sourdough, a mixture of flour and water that is left to ferment and then used to make bread. The idea is to analyse and compare the microbial communities in sourdough starters collected from citizen scientists from around the world. This a successful example explicitly calls itself citizen science and has already lead to results on how bacteria and yeast affect flavour.
I am also looking at initiatives that link farmers with consumers, and that help consumers to decrease food waste or to make better food choices regarding their diets. Grow Observatory, for example, crowdsources soil related data. It also seems that some initiatives do not explicitly start as citizen science but could be later turned into one.
Finally, in order to help reduce the invisibility of citizen science in social sciences and humanities, could you tell us an example in this field?
I am fascinated by applications that arise from social sciences and humanities but never considered themselves citizen science. Fortepan and Fortego are Hungarian initiatives to collect good quality amateur and old private photos from people or institutions and make them publicly available. It enriches your view of the city and the city life in a particular neighbourhood.
These kinds of initiatives could eventually be transformed into citizen science. They are not conceived as citizen science, but they could be, since they are creating a common digital heritage. Moreover, they are creating great research opportunities for historians.