Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low- and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas.

Data4HumanRights’ training materials have been developed as open-source and tailored to limited-resource settings, where community data collectors often live and work. Access to training on data collection, analysis, and visualisation to support the advocacy of vulnerable groups is essential, particularly in the context of increasing human rights challenges such as land rights, adequate housing, conflicts, and climate justice. This paper provides an overview of how the training materials were co-developed with community data collectors in Nigeria and Kenya, offering insights into the fundamental principles (i.e., inclusiveness, adaptive, limited resources, and being gender- and incentive-sensitive) and the structure of the open-access training materials. The development process resulted in 28 modules, each designed to be delivered in a face-to-face format in less than one day by a local trainer. To maximize adaptivity, the training modules can be mixed and matched (e.g., as individual modules or a learning path of several modules around a specific training need). The individual modules cover a range of methods and tools that are useful to human rights work and community advocacy, e.g., documenting evictions, performing rapid needs assessments after acute crises, community profiling, and monitoring community development indicators. The training materials contain instructions for the training facilitator(s) and all necessary training materials. To ensure inclusivity, the training covers both basic and advanced topics, with most modules designed to address basic needs that can be followed using a mobile phone, thereby avoiding the need for computers or printed handouts. The training results in Nigeria and Kenya showcase applications, including mapping waste problems and addressing forced evictions. Trained community groups produced maps of waste piles to prioritize community actions, such as finding space for urban agriculture, and conducted rapid needs assessments during a massive eviction. This approach helps reduce power imbalances and empowers community groups to effectively manage and utilise their own data.

Geographic information has become increasingly relied upon in supporting decision-making in public administration as well as humanitarian intervention. One domain where such information has been important is waste management, notably improving the mapping of areas with the highest waste accumulation, finding suitable locations for landfills as well as planning transport routes for collection services. The utility of geographic information here reflects the capacity of visual information to mediate between human actors (e.g. municipal authorities) and the world in which they wish to make changes . In this paper, we shall be presenting insights from five focus groups that were conducted to assess the impact of the visualisation of waste accumulation in the ‘slums’ and informal settlements in Nairobi, Kenya, along with factors that affected the readability and understanding of the visualisations presented in the focus groups. In this paper, we will be considering: i) the impact of design elements (e.g. level of detail and symbology) on raising problem awareness of the participants regarding the waste accumulation; and ii) the ethical and political concerns that arise from the way communities living in the DUAs are perceived from the visualisations.

Data4HumanRights training materials have been developed as open-source and tailored to limited resource settings where community data collectors often live and work. An overview of how the training material was developed together with community data collectors in Nigeria and Kenya is provided. The paper gives insights into the fundamental principles (i.e., inclusiveness, adaptive, limited resources, gender- and incentive-sensitive) and the structure of the open-access training materials. This resulted in 28 modules designed to be delivered in a face-to-face format in less than one day by a local trainer. To maximize adaptivity, the training modules can be mixed and matched (e.g., as individual modules or a learning path of several modules around a specific training need). The individual modules cover a range of methods and tools that are useful to human rights work, for example, documenting evictions, performing rapid needs assessments after acute crises, community profiling, and monitoring community development indicators. The training materials contain instructions for the facilitator(s) of the training and all necessary training materials to conduct the training. To maximize inclusivity, the training covers basic to advanced topics. Most training modules address basic training topics that can be optimally followed with a mobile phone (to avoid using a computer and printing handouts). The training was developed and implemented with local community groups in Nigeria and Kenya. The material is free to use, adapt, and translate into different contexts and languages.