Problem context: The 17 Sustainable Development Goals (SDGs), launched by the UN in 2015, are underpinned by hundreds of concrete targets and indicators. However, for many of these targets and indicators, National Statistical Offices (NSOs) do not have the data collection capacity. Measuring progress towards the SDGs is thus a challenge that can benefit from non-standard data sources, such as Citizen Science (CS).
Importance for Society: The goal of the Crowd4SDG project was to research the extent to which CS can provide an essential source of non-traditional data for tracking progress towards the SDGs, as well as the ability of CS to generate social innovations that enable such progress. Based on shared expertise in crowdsourcing for disaster response, the transdisciplinary Crowd4SDG consortium of six partners focused on SDG 13, Climate Action, to explore new ways of applying CS for monitoring the impacts of extreme climate events and strengthening the resilience of communities to climate-related disasters.
Project Objectives: To achieve this goal, Crowd4SDG initiated research on the applications of artificial intelligence and machine learning to enhance CS and explored the use of social media and other non-traditional data sources for more effective monitoring of SDGs by citizens. Crowd4SDG used direct channels through consortium partner UNITAR to provide National Statistical Offices (NSOs) with recommendations on best practices for generating CS data for tracking the SDGs.
To this end, Crowd4SDG rigorously assessed the quality of the scientific knowledge and usefulness of practical innovations occurring when teams develop new CS projects focusing on climate action. This occured through three annual challenge-based innovation events, involving online coaching. A wide range of stakeholders, from the UN, governments, the private sector, NGOs, academia, innovation incubators and maker spaces were involved in advising the project and exploiting the scientific knowledge and technical innovations that it generated.
At the core of the project was a novel innovation cycle called GEAR (Gather, Evaluate, Accelerate, Refine), which ran once a year. The GEAR cycles involved online selection and coaching of citizen-generated ideas for climate action, using the UNIGE Open Seventeen Challenge (O17). The most promising projects were accelerated during an online two-month Challenge-Based Innovation (CBI) workshop. Top projects received further support at an annual SDG conference, the Geneva Trialogue.
Each Crowd4SDG GEAR cycle focused on a specific aspect of Climate Action and its connection with other SDGs. The first GEAR cycle was on Climate Change and its impact on Urban Water Resilience (SDG 6 and 11). The second GEAR cycle was on Climate Change and Gender Equality (SDG 5). The third GEAR cycle was on Climate Adaptation and Social Justice (SDG 16).
