Types of Citizen Science

Citizen science projects can be categorized in many ways, e.g., by geographical location, discipline, volunteers' involvement level and other. In this course we will discuss two typologies, which are these:

1. Involvement level and
2. Discipline (field of science)

1. Involvement level

Citizen science projects have different levels of engagement, and this is one of the most important aspects that characterise these activities. For example, the standard typology dimension distinguishes citizen science projects according to the level of citizen involvement in the research process.

British scientist Muki Hackley (2018) has proposed a classification of citizen science based on the level of engagement of citizens in scientific research. According to this classification, there are four levels of engagement levels:

Level 1 (Crowdsourcing): At the first (lowest) level, citizen involvement is minimal and limited to providing resources or data. An example is a citizen's voluntary consent to allow researchers to access resources on his or her personal computer. Another example is researchers asking participants to carry sensors and send data. The advantage of this type of research is that the scientific process is highly controllable, but at the same time, it wastes the potential of using participants' cognitive abilities.

Level 3 (Participatory science): This level is particularly relevant in community science and is often called 'participatory science'. This is the level at which participants define the problem, and the data collection method is chosen in consultation with scientists and experts. Participants then collect the data but need expert help to analyse and interpret the results.

Level 4 (Extreme science): This is the level at which citizen science is fully integrated into the research activity. Participants can choose their own level of involvement and potentially be involved in the analysis, publication, and publicity of results. This form of citizen science can be called 'extreme citizen science'. This level also opens up the possibility of citizen science without professional scientists planning the whole process, conducted and controlled by citizen scientists.

2. Citizen science types by discipline: Natural sciences, Social Sciences

The fields of citizen science projects are diverse: astronomy, ecology, engineering, genetics, computer science, medicine, psychology, statistics, and many others. Zooniverse is the world's largest and most popular volunteer research platform. Recently, it connects 77 active projects and this number is changing constantly as more new citizen science projects are added to the platform. More than a 2 millions people around the world help professional researchers on Zooniverse. Anyone can build a Zooniverse project. They need just upload their data and choose the tasks they want the volunteers to do. Teachers, instructors and volunteers can access a variety of educational resources on the Zooniverse Classrooms platform.

CS in Natural Sciences

The natural sciences include the life and physical sciences and study nature through observing and understanding phenomena, testing hypotheses, and performing experiments. Key principles such as reliability, validity, objectivity, and predictability are achieved through transparent assumptions, methods, data, interpretations, and multidisciplinarity.

Bringing together existing research, it becomes evident that while citizen science is well established in the natural sciences, no thematic boundaries seem to exist to integrate and use its manifold potential. In some other areas, for instance, chemistry, citizen science is largely absent.

A broad field of natural sciences involving citizens is the life sciences, especially biology. As mentioned in the introduction, humans have observed natural phenomena for centuries and contributed to understanding nature. They described species and observed plants and animals' spatial and temporal (phenological) distribution. Many projects today deal with the observation and interpretation of wildlife data, often with management approaches supported by tools for data collection and analysis (Frigerio et al., 2018).

Biodiversity monitoring mainly profits from a citizen science approach, as working with citizen scientists in monitoring biodiversity networks increases the amount of data (and, therefore, their reliability) and expands the temporal and spatial scales of the investigation. As over 80% of European biodiversity data is recorded by citizen scientists, it is unsurprising that the spatial and temporal coverage of biodiversity assessment depends largely on volunteers’ availability and ability to travel to areas of interest (Frigerio et al., 2018).

One of these projects is Iberian Camera Trap Project. The main aim of the project is to develop a tool for the census and monitoring of biodiversity from the Iberian Peninsula. that helps wildlife researchers and managers in their purposes of knowing and protecting our nature. Volunteers collaborate in identifying the photo-trapping pictures. Most of the images have been given to researchers by people interested or involved professionally in camera trap photography.

CS projects in Astrophysics and Astronomy

The Galaxy Zoo Project has an amazing global community which helps to classify data, acts as  moderators and a participate as beta testers on pilot projects. Over more than fifteen years, volunteers help to explore galaxies near and far – from Hanny's Voorwerp to Green Peas,  Cloudspotting on Mars and even the alphabet of galaxies.

The Zooniverse hosts a list of publications based on Galaxy Zoo data and written by the Galaxy Zoo team.

The NASA Citizen Science website allows citizens to participate in real NASA science projects. The main areas are the universe, the solar system, and observations of the Sun, and the Earth.

In Backyard World: Planet 9, citizens help scientists search for new objects at the edge of the solar system and distinguish between real celestial objects and the visual artefacts from NASA's Wide-field Infrared Survey Explorer (WISE) mission.

Social Citizen Science

The social science disciplines have more to offer to citizen science than bridging and mediating, and citizen social science has many more facets than merely mimicking natural science approaches. Based on the long tradition of participatory approaches in the fields of participatory action research (PAR) and the co-production of knowledge, tools and concepts in the social sciences are available to impart both scientific rigour and inclusivity to knowledge production. On the other hand, the social sciences can learn from citizen science about new forms of mobilisation, technological platforms, and socio-technical skills.

Understanding how projects and participation are organised, and their locality, sociopolitical contexts, and distributed interests are important since these all co-shape the methods developed and used in projects:

• coordination,
• participation,
• community,
• evaluation,
• openness,
• entrepreneurship,
• locality.

Key issues for Citizen Social Science:

• Diverse Interests and Motivations

Some of the biggest challenges facing citizen-led social science are related to addressing and possibly resolving the competing motivations and divergent interests of those who promote and participate in citizen-led social science projects. In addition, many citizen social science topics deal with complex issues, such as listening to citizens' voices in urban infrastructure development and experiments to improve community mental health.

• Ethical Issues

While ethical review procedures in research and higher education institutions are a good starting point for discussions, what happens when projects are initiated by people working outside these institutions? Who then oversees the ethical issues of the project? A related challenge is using the data generated by citizen-led social science projects. How can the generated data be compatible with official data sources where appropriate or in a format that can be re-analysed or, if possible, re-used?

• Hierarchical Power Relations Between Researchers and Non-academic Partners

Academic researchers often have unequal power dynamics when collaborating with non-academics, so one of the challenges in civic social science is to strike the right balance between academic and non-academic actors and between different types of experts. In many cases, civic social science projects use approaches that ideally involve a process of mutual learning and co-creation.

• Evaluation

Similarly to other community-based participatory research, evaluation schemes for citizen social science should be designed according to the project's objectives and the participant's expectations. Still, they should also be flexible enough to accommodate changes in the dynamics of participatory research routines. The challenge is, therefore, to plan and develop the skills and incentive structures necessary for such an inclusive evaluation system so that evaluation is not left to the end of the project but is actively and continuously implemented from the planning stage of the research. Evaluation should include often overlooked aspects such as trust building and power relations.

• Hollowing Out of Terminology

Many of the terms used in citizen science are often used interchangeably but often with different meanings and disciplinary understandings, resulting in vacuous terminology. The overuse and misuse of terminology, especially terms such as citizen, social, laboratory, experiment and participation, have robbed these terms of some of their meaning and made them increasingly imprecise. This is one of the main reasons for our cautious approach to citizen social science.

To summarise the main features of citizen social science and citizen science, the following differences can be identified: 

References:

Albert, A., Balázs, B., Butkevičienė, E., Mayer, K., & Perelló, J. (2021). Citizen social science: New and established approaches to participation in social research. Chapter 7 (pp: 119-138). In: Vohland K. et al. (Eds). 2021. The Science of Citizen Science. Springer. https://doi.org/10.1007/978-3-030-58278-4 . 

Chandler, M., See, L., Copas, K., Bonde, A. M., López, B. C., Danielsen, F., et al. (2017). Contribution of citizen science towards international biodiversity monitoring. Biological Conservation, 213, 280–294. https://doi.org/10.1016/j.biocon.2016.09.004

Frigerio, D., Richter, A., Per, E., Pruse, B., Vohland, K. (2021). Citizen Science in the Natural Sciences. In: Vohland, K. et al. The Science of Citizen Science. Springer, Cham. https://doi.org/10.1007/978-3-030-58278-4_5

Haklay, M. (2018). Participatory citizen science. In: Citizen science: Innovation in open science, society and policy, 52-62. https://www.jstor.org/stable/j.ctv550cf2.11

Marks, L., Laird, Y., Trevena, H., Smith, B. J., & Rowbotham, S. (2022). A scoping review of citizen science approaches in chronic disease prevention. Frontiers in Public Health, 953. https://doi.org/10.3389/fpubh.2022.743348 

Schmeller, D.S., Henry, P.Y., Julliard, R., Gruber, B., Clobert, J., Dziock, F. et al. (2009). Advantages of volunteer-based biodiversity monitoring in Europe. Conservation Biology, 23, 307–316. https://doi.org/10.1111/j.1523-1739.2008.01125.x