This document discusses citizen science, which involves members of the public collaborating with professional scientists on research projects. It provides several examples of citizen science projects that collect or classify data. Zoe and Street Spectra apps collect health and light pollution data contributed by citizens. Galaxy Zoo and Research Data Workbench involve citizens classifying galaxy images and electronic waste statements. Isala collects vaginal microbiome samples from over 4,500 women. The Noise Maps project in Barcelona engaged citizens in designing a project on noise pollution. The document outlines considerations for ensuring data justice in citizen science, including procedural, instrumental, rights-based and structural fairness. It recommends data benefit the contributing community and lists questions to ensure this. Recent papers on the topic are also

1. Gefion Thuermer
ECA Community Meetup , 27th July 2023
Ethical data collection and use
with Citizen Science

2. What is Citizen Science?

3. 3
https://actionproject.eu/toolkit/

4. IMPETUS
https://impetus4cs.eu/

5. Data collection with citizen science
Zoe App
• Developed by King’s researchers (among
others)
• Redeployed to study COVID symptoms early
in the pandemic
• Nearly 5m contributors
• Over 40 papers
• Aggregated covid data reflected to
participants
• https://health-study.joinzoe.com/data

6. Data collection with citizen science
Street Spectra
• Light pollution & new light sources
• Citizens collect data using mobile phone
cameras
• Then classify data on Zooniverse
• 500+ citizen scientists involved
• 800+ classifications
• https://streetspectra.actionproject.eu/

7. Data classification with citizen science
Zooniverse / Galaxy Zoo
• Started 2007
• Identification of galaxy shapes
• over 50m classifications
• Over 450 papers
• Data shared openly
• https://www.zooniverse.org/

8. Data classification with citizen science
Research Data Workbench
• International project run by Restart
• Electronic waste & CO2 emissions
• Built platform to classify statements in repair
reports
• 300 CS engaged
• >30,000 classifications
• Data used for European policy work
• https://therestartproject.org/

9. Citizen data sharing
Isala
• Interdisciplinary project based in the
Netherlands
• Citizen-science map of the vaginal
microbiome
• Collected samples with >4,500 women
• Strong focus on community, education and
awareness
• Data used for medical research
• https://isala.be/en/

10. Participatory design & Ethics with citizen science
Noise Maps
• Citizens of Barcelona
• Noise pollution
• CS initiated the project, designed the concept,
data collection and analysis together with
scientists
• Developed computational method to extract
types of sound from audio samples, in order to
protect privacy of bystanders
• https://actionproject.eu/citizen-science-
pilots/noise-maps/

11. Data Justice in Citizen Science
• Procedural: Fairness in the system’s
handling of data
• Instrumental: outcomes of data use,
fairness in the results of data processes
• Rights-based: basic data rights, including
data access, ownership, privacy, and
representation
• Structural: social structures that shape and
are shaped by the data systems and data-
related outcomes
• Distributive: Overarching. Fair
distribution of data results and just data
functioning requires fair distribution of
data-related resources.
Christine, Debora Irene, and Mamello Thinyane. ‘Citizen Science as a Data-Based Practice: A Consideration of Data Justice’.
Patterns 2, no. 4 (9 April 2021): 100224. https://doi.org/10.1016/j.patter.2021.100224.

12. Data Justice Plans
Data that is collected by and with citizens should benefit the community that they come from.
Think about how you can ensure that this happens for your project data.
• Who will contribute data to your project, and why?
• How will they benefit from what you plan to do with the data?
• How will this benefit materialize?
• Who will be responsible for making this happen?
• What will happen if the project does not go to plan – what can participating communities benefit from
partial results, or what additional results might become available?
• Who else will benefit from the data and how?

13. Recent papers
Data Management Documentation in Citizen Science Projects: Bringing Formalisation
and Transparency Together, with Esteban Gonzalez, Neal Reeves, Oscar Corcho and Elena
Simperl, which looks at how citizen science projects use data management documentation (or not).
https://theoryandpractice.citizenscienceassociation.org/articles/10.5334/cstp.538
Talking Metadata. Understanding Privacy Implications of Volunteer Contributions in
Citizen Science Projects, with Laura Koesten and Elena Simperl, which looks at issues with
metadata in citizen science.
https://www2.units.it/etica/2023_2/THUERMERETAL.pdf

14. Gefion Thuermer
Research Fellow
gefion.thuermer@kcl.ac.uk
+44 7580 752244
@gefiont@uxp.de
https://www.linkedin.com/in/gefiont
Thank you