Dr. Andreas Wenninger is a scientific officer at bidt and heads a DFG project on good scientific practice in Citizen Science, also known as citizen science.
In your new project, you are investigating the “evidence culture of Citizen Science”. What exactly do you mean by this?
In our society, what is considered scientifically evident is what has been tested and confirmed by science in the respective fields.
Usually, only professional scientists with the corresponding “certified expertise” are involved in this process. In this process, different cultures of evidence develop depending on the discipline. Ideally, this validation process is the prerequisite for scientific knowledge to be recognised as consensus knowledge outside the scientific community.
Investigating the evidence culture of Citizen Science is exciting because citizens who do not have certified scientific expertise are now also involved in the process of knowledge production. In our project, we choose a practice-theoretical approach. We investigate how evident knowledge is produced and presented in Citizen Science. We want to find out which forms of evidence culture emerge in Citizen Science.
As a layperson, one would assume that it is completely clear what is scientifically evident.
In our project, we want to show that it is not that simple. What is considered scientifically evident changes historically and varies from discipline to discipline. Which groups produce evidence is also variable. It also concerns what is accepted as plausible in a society at a certain time – if you think of the debate about the safety of nuclear power plants, for example.
Also, to give another example from a sub-project in our research group, there are different practices for creating evidence in nutritional sciences. Besides science, this comes from consumers and the media, who set their standards and sometimes moralise strongly.
What is the goal of Citizen Science, where everyone can support science?
Citizen Science tries to enrich classical academic knowledge and integrate knowledge outside of science into academic research. This applies, for example, to local expertise in environmental research or when patients in medical research contribute personal experiences that are neglected in classical clinical studies.
The citizen sciences try to generate evident knowledge in their projects but also face scepticism. On the part of classical science, there are doubts that citizen science can develop robust scientific knowledge.
In Citizen Science projects, volunteers support scientists. The Federal Ministry of Education and Research has funded several such projects since 2016.
This internet platform provides information about the opportunities for participation.
How does this affect the projects?
In Citizen Science, scientific evidence is strongly thematised, often talking about scientific quality and scientificity. In the new project, the focus is less on individual Citizen Science projects but rather on cross-field attempts to improve the quality of Citizen Science.
To this end, many Citizen Science associations and initiatives have been formed across projects. For example, they often deal with the collection of data. In this context, whether the data from citizen science projects meet classical scientific quality standards is always questioned. In some cases, tests are carried out with comparative data collected by professional scientists to better assess the data quality. Qualitative differences can sometimes be compensated for by the larger amounts of data in citizen science projects if statistical procedures are used to factor out these errors.
In general, attempts are being made to establish more general standards so that the data from different citizen science projects can become interoperable, i.e. can complement each other meaningfully.
Many projects try to solve potential quality problems by having specifications on how the data is entered and processed, which corresponds to professional control. We speak of a “mechanisation of scientific expertise” in this context. Digital technologies generally play a major role in this.
So does citizen science benefit from digitalisation?
Yes, massively. Digital tools allow many citizens to contribute to scientific research projects.
Being equipped with digital technologies makes long-term and large-scale data collection much easier. But also in data analysis, online platforms and digital tools are important prerequisites for the mass participation of citizens. For example, many projects in species and nature conservation aim to record the occurrence and behaviour of certain animals.
Will the classical academic criteria for scientific evidence prevail in Citizen Science?
First, there is the question of whether this is desirable. There are different positions on this in Citizen Science, which can be simplified into two currents.
On the one hand, there is the attempt to conceive of Citizen Science as high-quality science according to the model of classical academic science, i.e. to implement primarily classical criteria for good science in Citizen Science as well. The other current warns that this would, however, destroy precisely the hoped-for potential of citizen science, namely to involve laypersons intensively and to include alternative bodies of knowledge.
Rather, openness and versatility are important so that as many citizens as possible get involved and thus, evident knowledge becomes possible. Ultimately, what is being worked on here is a specific culture of evidence that is more appropriate to Citizen Science.
In our project, we want to investigate what dynamics develop because there are different ideas of what good scientific practice should be in Citizen Science. In doing so, we are also contributing to the debate on how science can respond to challenges such as fake news and sustainability in today’s world.