Interview Questions for Dilek Fraisl, Research Scholar at IIASA

Interview Questions for Dilek Fraisl, Research Scholar at IIASA

In the realm of data collection, citizen science is making a significant impact, extending beyond environmental indicators to support the United Nations Sustainable Development Goals (SDGs) in various sectors.

Citizen science projects have demonstrated potential contributions in areas such as education (SDG 4), sustainable cities and communities (SDG 11), zero hunger (SDG 2), and socio-economic and community-centered indicators. For instance, municipal solid waste monitoring and urban environmental quality data can help advance sustainable communities (SDG 11). Similarly, public participation and capacity building initiatives align with education-related indicators.

Interestingly, agricultural or food security-related data can be gathered via citizen science, particularly in global south projects (GS), contributing to SDG 2 - zero hunger. While direct contributions to SDG indicators in non-environmental domains are less frequent, indirect contributions exist across 22 indicators spanning SDGs 1 to 16, indicating a broad relevance beyond just environmental metrics.

Socio-environmental data collected by citizen science can enhance our understanding and reporting of social benefits linked to projects, such as economic activities, community health, and impacts on vulnerable populations. Frameworks like the Carbon Crediting Data Framework aim to standardize socio-environmental data, including these community and economic dimensions, pointing to further integration with SDG data systems beyond environment-focused indicators.

Water quality monitoring is another area where citizen science supports SDG 6 (clean water and sanitation) by providing locally-grounded data used for official reporting. This demonstrates how data collection by the public can empower action on social infrastructure and public health targets.

Other promising areas include health (SDG 3), gender equality (SDG 5) and reduced inequalities (SDG 10), innovation and partnerships (SDG 9 and SDG 17). Citizen science projects often foster multi-sector collaboration, including academia, private sector, and international organizations.

Despite these advancements, data gaps persist. A UNEP study shows that 58% of environmental SDG indicators lack data, and only around 20% of countries have data for Goal 13-climate action. Citizen science data can help fill these gaps, particularly in monitoring SDG indicator 16.6.2, "proportion of population satisfied with their last experience of public services."

Moreover, citizen science data can potentially contribute to SDG monitoring in areas such as sexual violence, access to basic services, child development, and child labor. Projects like Safecity can provide data on sexual harassment and abuse in public spaces, helping to identify factors causing violence and working on strategies for solutions.

Standardization can help make different citizen science data sets comparable and improve data quality. A study published by IIASA in 2020 shows that citizen science data can support the monitoring of one-third of SDG indicators, with the greatest contribution being in environmental indicators.

However, it's important to note that while citizen science has shown capacity to support SDG data, the strongest documented impacts remain in environmental and community sustainability arenas, with emerging opportunities in socio-economic and health-related targets. The 2022 SDG Report highlights significant data gaps in terms of geographic coverage, timeliness, and level of disaggregation of data.

In conclusion, citizen science is proving to be a valuable tool in bridging data gaps and supporting the Sustainable Development Goals. By encouraging community-driven monitoring and action, citizen science projects are helping to empower individuals and communities to contribute to a more sustainable and equitable world.

1. AI and data policy should consider the potential contributions of citizen science research in areas such as education, sustainable cities, zero hunger, and socio-economic and community-centered indicators.
2. The integration of technology, and data-and-cloud-computing, in citizen science projects can help advance our understanding of climate-change and environmental-science, supporting the United Nations Sustainable Development Goals (SDGs).
3. Businesses can benefit from the implementation of environmental-science and AI-driven data in their strategies, promoting personal-growth, innovation, and partnerships (SDG 9 and SDG 17).
4. By fostering multi-sector collaboration, such as academia, private sector, and international organizations, citizen science projects can fill data gaps in areas like clean water and sanitation (SDG 6), health (SDG 3), gender equality (SDG 5), reduced inequalities (SDG 10), and climate action (SDG 13).
5. Standardization of data collected by citizen science, like the Carbon Crediting Data Framework, can improve data quality and help standardize socio-environmental data, making it comparable across various sectors and SDG domains.
6. Education-and-self-development programs can integrate AI, data, and citizen science to promote critical thinking, problem-solving, and community engagement in support of the SDGs.
7. Citizen science data has the potential to support SDG monitoring in areas such as sexual violence, access to basic services, child development, and child labor, addressing geographic coverage, timeliness, and level of disaggregation of data in the 2022 SDG Report.

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