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Interview Questions for Dilek Fraisl, Researcher at IIASA

Discussion with Dilek Fraisl, a researcher from NODES Research Group under IIASA's Advancing Systems Analysis Program, focused on incorporating novel data sources into standard statistics to tackle global sustainability issues.

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Interview Questions for Dilek Fraisl, Scholar at the International Institute for Applied Systems...
Interview Questions for Dilek Fraisl, Scholar at the International Institute for Applied Systems Analysis (IIASA)

Interview Questions for Dilek Fraisl, Researcher at IIASA

In a world where data gaps persist in various aspects of the United Nations Sustainable Development Goals (SDGs), particularly in environmental indicators, citizen science is stepping up to fill the void.

According to the 2022 SDG Report, significant data gaps exist in terms of geographic coverage, timeliness, and level of disaggregation of data, with only around 20 percent of countries having data for Goal 13-climate action. However, citizen science data can make a substantial difference, especially in monitoring SDG indicator 16.6.2, "proportion of population satisfied with their last experience of public services."

Citizen science projects, such as Safecity, collect data on sexual harassment and abuse in public spaces, providing valuable insights for individuals, local communities, and local administrations. These initiatives can help identify factors causing violence and work on strategies for solutions.

Beyond environmental indicators, citizen science efforts are extending to areas like behavioural science, technology, and social data collection. Behavioural science projects engage communities and decision-makers to collect data and promote behavioural changes critical to SDGs like health, education, gender equality, and poverty reduction.

Technology-enabled social data collection leverages ethical artificial intelligence and digital governance to support SDG data needs in areas such as conflict-related sexual violence, health, education, and workplace safety. Participatory monitoring using AI, apps, and real-time reporting allows citizens to contribute data on social issues, directly feeding into SDG monitoring frameworks.

Community participation in socio-economic and health data collection is another crucial area where citizen science excels. Citizen-led data collection around community health, nutrition, education attendance, and economic activities can supply vital information to SDGs related to no poverty, zero hunger, and good health and well-being.

The following table illustrates some key examples and data types collected by citizen science projects in various SDG areas:

| SDG Area | Citizen Science Example | Data Type Collected | |---------------------------|-------------------------------------------------------------|---------------------------------------------| | Health and Well-Being | Community health surveys, real-time disease reporting | Disease incidence, health behaviours | | Education | School attendance tracking campaigns, learning assessments | Attendance data, educational attainment | | Gender Equality | Reporting on gender-based violence via confidential apps | Incidents, survivor support needs | | Social Inclusion & Poverty| Participatory economic activity mapping | Employment status, income data, resource access | | Conflict & Human Rights | Documentation of conflict-related sexual violence | Incident reports, survivor testimonies |

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 from citizen science data in environmental indicators. Despite this, scientific literature shows that citizens can make valuable and scientifically valid contributions to data collection.

However, national statistical offices may hesitate to incorporate citizen science data into official statistics due to concerns about data quality. To address this, the International Criminal Court (ICC) has been working with UNEP to improve their methodology to align with the 14.1.1b global methodology. This will enable the uptake of data collected through local citizen science initiatives using the ICC methodology to be more easily scaled for SDG monitoring and reporting efforts globally.

Lack of awareness of citizen science within the official statistics community is another reason for hesitancy. Projects like the one led by Dilek Fraisl, a researcher working on integrating new data sources into official statistics to address global development challenges, are helping to bridge this gap. Fraisl's project with IIASA, Ghana Statistical Service, and others integrated citizen science beach litter data into the official statistics of Ghana, making it the first country to report on the SDG indicator related to marine plastic litter (14.1.1b).

In conclusion, citizen science projects can extend beyond environmental monitoring to support integrated, people-centered data collection essential for tracking and achieving multiple SDGs. By bridging gaps between science and society, making science more relevant, contributing to decision making, and promoting participation and transparency, citizen science data can play a crucial role in advancing the SDG agenda.

  1. Research indicates that citizen science data can support the monitoring of one-third of UN Sustainable Development Goals (SDG) indicators, with the greatest contribution from citizen science data in environmental indicators.
  2. Technology-driven social data collection, utilizing ethical artificial intelligence and digital governance, is essential for meeting SDG data needs in various areas, including health, education, and conflict-related issues.
  3. Citizen science projects, such as those focused on school attendance tracking campaigns and reporting on gender-based violence, can provide crucial data for SDGs related to health, education, gender equality, and social inclusion.
  4. National statistical offices may be cautious about incorporating citizen science data into official statistics due to concerns about data quality, but efforts are being made to improve methodologies and bridge awareness gaps.
  5. Personal growth, career development, and learning can be enhanced through skills training programs that focus on areas like data-and-cloud-computing, AI, and environmental-science, as these skills are increasingly valuable in the collection and analysis of citizen science data.
  6. Policy-makers can benefit from citizen science data, as it offers valuable insights for identifying factors causing social issues and developing effective solutions, such as strategies for poverty reduction and gender equality.
  7. The future of citizen science lies in its ability to extend beyond environmental monitoring and support integrated, people-centered data collection essential for tracking and achieving multiple SDGs, ultimately advancing the global development agenda.

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