The Waterproofing Data project explored how to build communities’ resilience to flooding, by engaging them in the process of generating the data used to predict when floods will occur. The project team developed a functional citizen-science mobile app prototype and a model school curriculum, which has been successfully co-produced and trialled with more than 300 students from over 20 schools and civil protection agencies of five Brazilian states (Acre, Mato Grosso, Pernambuco, Santa Catarina and Sao Paulo). The app and curriculum enabled the communities involved to democratise flood data, raise awareness of flood risks, and co-design new initiatives to reduce disaster risks to communities. The project invited participants to co-create a dataset that continuously describes the areas in which flooding impacted their territory. Through this process, the team sought to enhance knowledge about floods among those engaged with the project. This dataset showcases collaborative maps of two flood-prone neighbourhoods in Brazil. The maps were co-created and evaluated with the help of community members and school students living in underserved areas. Data was generated using the SketchMap tool https://sketch-map-tool.heigit.org. The tool supported i) printing paper maps of the neighbourhoods, ii) participants' drawings with the areas they perceived flooding risks, and iii) digitising those areas in a format suitable for cartography. The purpose of this process was to gather input from locals and identify areas that are prone to flooding in the two neighbourhoods. Labels and legends are written in Portuguese. This dataset is complementary data for our publication “Dialogic data innovations for sustainability transformations and flood resilience: The case for waterproofing data” available here https://doi.org/10.1016/j.gloenvcha.2023.102730Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to scientific "centres of expertise", and then flood-related alerts and interventions flow back down through local governments and into communities. Rethinking how flood-related data is produced, and how it flows, can help build sustainable, flood resilient communities. To this end, this project develops three innovative methods around data practices, across different sites and scales: 1) we will make visible existing flows of flood-related data through tracing data; 2) generate new types of data at the local level by engaging citizens through the creation of multi-modal interfaces, which sense, collect and communicate flood data, and; 3) integrate citizen-generated data with other data using geo-computational techniques. These methodological interventions will transform how flood-related data is produced and flows, creating new governance arrangements between citizens, governments and flood experts and, ultimately, increased community resilience related to floods in vulnerable communities of Sao Paulo and Acre, Brazil. The project will be conducted by a highly skilled international team of researchers with multiple disciplinary backgrounds from Brazil, Germany and the UK, in close partnership with researchers, stakeholders and publics of a multi-site case study on flood risk management in Brazil. Furthermore, the methods and results of this case study will be the basis for a transcultural dialogue with government organisations and local administration involved in flood risk management in Germany and the United Kingdom.

Around 15 stakeholders that included community members and school students living in underserved, flood-prone neighbourhoods in Brazil, were invited to analyse and discuss the data diaries generated in the initial phases of the project. The two focus group workshops included stakeholders involved in flood risk management and monitoring. The results were compiled using a geospatial data format that summarises the perceptions and discussions about past flooding events linking them to specific spaces and roads within the neighbourhood.