The RD4C Case Studies aim to provide insights on promising practice as well as barriers to realizing responsible data for children.
The case studies analyze data systems deployed in diverse country environments, with a focus on their alignment with the RD4C Principles.
ZimbabweMICS Zimbabwe Domestic Violence Module
UNICEF launched the Multiple Indicator Cluster Surveys (MICS) in 1995 to support governments in monitoring the situation of children around the world. Over the past 25 years, this survey has become the largest source of statistically sound and internationally comparable data on women and children worldwide. MICS surveys are conducted by trained fieldworkers who perform face-to-face interviews with household members on a variety of topics. The surveys have been a major data source for assessing progress for international development goals. More than 330 MICS surveys have been carried out in more than 115 countries. Throughout the years, MICS has been updated at the start of each round with new and improved questions and methodologies. Zimbabwe was part of MICS’s rounds in 2009 (MICS3), 2014 (MICS5), and 2019 (MICS6). For the 2019 deployment, Zimbabwe’s National Statistical Agency approached the MICS team to integrate a domestic violence module to counteract the lack of data on the incidence of domestic and gender-based violence. The insights generated from the work subsequently informed national legislation and a variety of national initiatives to combat domestic violence. Deployment of MICS in Zimbabwe captured the RD4C principles of being purpose-driven (targeted at filling a specific data gap and informing ongoing policy discussions), participatory (involved a wide variety of stakeholders in managing each phase of the effort), and preventative of harm across the data lifecycle (relied on techniques through collection, processing, and analysis to guarantee the safety and confidentiality of respondents). It is a useful example for RD4C because it demonstrates how responsible practices can evolve and be supplemented over time. It also demonstrates how principles can be realized in the field in an open, participatory fashion and the challenges that practitioners can face with field work.Purpose-Driven Professionally Accountable ParticipatoryRead article
AfghanistanNutrition Online Database
Afghanistan’s Nutrition Online Database is a web-based information system providing access to aggregated nutrition data to inform planning and service delivery at the national, provincial, and zonal level. The Public Nutrition Department (PND) within the Afghanistan Ministry of Public Health (MoPH) leads database management, with UNICEF Afghanistan acting as the lead technical developer and providing ongoing technical support. The system exists because missed use of potentially valuable data is a common challenge across the children’s data ecosystem Afghanistan. The Nutrition Online Database tries to spur the use of existing and newly developed nutrition data streams that otherwise might not inform potentially life saving nutrition planning and service delivery. It is the product of a participatory development process with key stakeholders across sectors and actors within beneficiary communities. PND, UNICEF Afghanistan, and other stakeholders support professionally accountable data use through training efforts and working groups but remain challenged by the fragmentation of nutrition systems, mandates, formats, and indicators. These factors could contribute to challenges in tracking decision-making processes affecting data responsibility across the nutrition data ecosystem.Purpose-Driven Professionally Accountable ParticipatoryRead article
RomaniaThe Aurora Project
The Aurora Project is a child protection platform developed by UNICEF Romania in collaboration with NGO and government partners. The system enables social workers and community health care providers to diagnose and monitor vulnerabilities experienced by children and their families. Through the administration of a child protection questionnaire, the system supports the determination of a minimum package of services needed by children and their families. It also enables child protection evaluation and planning work at the national level. The Aurora Project reflects many of the RD4C Principles through its collection of data for clear and well- defined purposes and the various training and guidance materials provided to users. UNICEF Romania and counterparts in the Romanian Government are still working to address challenges related to sensitive group data and the potential for disproportionate data collection and retention.Protective of Children’s Rights Professionally Accountable Purpose-DrivenRead article
Childline Kenya is a helpline offering services for children subjected to violence or neglect. Since it began operations in 2006, trained counselors have responded to calls, logged major components for reporting purposes, and redirected callers to relevant services. The organization emphasizes training and the rights of children while ensuring its data collection is proportional and purpose-driven. Given the sensitivity of its work, it faces some difficulties with duplicative and complex data.Professionally Accountable Protective of Children’s Rights Proportional Purpose-DrivenRead article
UNICEF and its partners collect and use large amounts of data to support their operations, emergency response efforts, and partnerships. In an effort to address significant disparities in how different offices within UNICEF handle this data to support their activities, UNICEF launched a pilot and engaged with partners to develop a platform that would allow for data centralization and standardization. The result was InForm, an Open Data Kit-based data collection and management tool that centralizes dispersed data streams, secures collected data in a common platform, and enables data analysis and visualization. Deployments of InForm in Mozambique to respond to Cyclone Idai and Kenneth demonstrate how InForm captures the RD4C Principles of being purpose-driven (by having a user-centric design approach); participatory (by both relying on and enabling collaborative engagements); proportional (by allowing agencies to centralize data instead of conducting duplicative collections); and prevention of harms across the data life cycle and professionally accountable (by centering data protection). To further advance its responsible data approach, standard operating procedures for handling sensitive data could prove useful. Personnel might also seek to remain cognizant of the time and resource constraints on implementing parties and the need to engage partners early in deployment.Participatory Prevention of Harms Across the Data Life Cycle Professionally AccountableRead article