The RD4C Principles
Principles to guide responsible data handling toward saving children’s lives, defending their rights, and helping them fulfill their potential from early childhood through adolescence.
Engaging and informing individuals and groups affected by the use of data for and about children.
Operationalizing responsible data practices and principles by establishing institutional processes, roles, and responsibilities.
Ensuring the needs and expectations of children, their caregivers, and their communities are prioritized by actors handling data for and about them.
Prevention Of Harms Across The Data Life Cycle
Establishing end-to-end data responsibility by assessing risks during the collecting, storing, preparing, sharing, analyzing, and using stages of the data life cycle.
Aligning the breadth of data collection and duration of data retention with the intended purpose.
Protective Of Children’s Rights
Recognizing the distinct rights and requirements for helping children develop to their full potential.
Identifying and specifying why the data is needed and how the intended or potential benefits relate to improving children’s lives.
From our blog
New developments from RD4C.
New PublicationWrap-Up: The Responsible Data for Children Principles in Review
Over the past few weeks, the Responsible Data for Children initiative has provided an overview not only of its principles, but the ways they can be achieved. From Mongolia to Guatemala, from Indonesia to the Democratic Republic of the Congo, there are examples of responsible data use for children everywhere. If you missed our blog series, we encourage you to go back and look at the compelling examples and lists of available tools and resources available to help you promote responsible data in your own work. This series include blogs on: Proportional: Explains Proportionality through the lens of Cellule d’Analyse Intégrée, an operational research and analytics cell created by UNICEF to support responses to health emergencies in the Democratic Republic of Congo and elsewhere; People-Centric: Explains being People-Centric with the Aurora Project in Romania, a child protection platform that helps social workers and community health care providers to diagnose and monitor vulnerabilities experienced by children and their families; Protective of Children’s Rights: Explains how to Protect Children’s Rights using the example of UNICEF Indonesia’s efforts to launch an Immunization Chatbot; Professionally Accountable: Explains what is involved in being Professionally Accountable through the global Humanitarian cash Operations and Programme Ecosystem (HOPE), and the specificities of their instance in Ukraine; Participatory: Explains approaches to being Participatory with InForm, a platform that supported emergency response efforts in Mozambique and Zimbabwe. Prevention of Harms Across the Data Lifecycle: Explains ways to Prevent Harms using the example of CPIMS+/Primero’s deployment in Guatemala to assist in child protection work; and Purpose-Driven: Explains what it means to be Purpose-Driven through the lens of the Administrative Data Maturity Model, which enhanced efforts to harness administrative data systems for child welfare in Mongolia. We hope this work can highlight innovative practices around the world and inspire practitioners seeking new models to support children. No matter where you are, the Responsible Data for Children principles can be implemented. If you have any projects you’d like to highlight in the form of a guest blog or other collaboration, please reach out to us at [email protected].Read more
New PublicationIntro to the Responsible Data for Children Principles: Purpose-Driven
Today’s blog looks at the importance of being purpose-driven, how this principle was embedded in UNICEF’s work in Mongolia with the Administrative Data Maturity Model (ADaMM), and which resources are available to you to operationalise it. What Does Purpose-Driven Mean? A responsible data practice starts by being purpose-driven. When you seek to handle data you should identify why the data is needed to achieve the intended goal and how the benefits relate to improving children’s lives. If there is no clearly articulated benefit for children, either actual or potential, you should not collect data, store, share, or analyze it. You might consider specifying the purpose and the value of the data to those who have a stake in its collection and use, including children and their caregivers. A privacy notice, for instance, may be useful for this purpose. Defining a clear purpose has several benefits, including: Better Decision-Making: When there is a clear understanding of the purpose, it is easier to make decisions based on how they will or could contribute to achieve the goal. Evaluation: By defining clear goals and objectives, you can measure progress and determine whether the project is on track to achieve its desired outcome. Communication: A clear purpose makes it easier to communicate the objectives and results of the initiative to all stakeholders involved who, as a consequence, are on the same page and can work towards the same goal. Sharing the purpose with children and their caregivers can lead to several positive outcomes, including: Transparency: Informing children and their caregivers about the purpose of data collection promotes transparency, which can help build trust and credibility. Improved Data Quality: When children and their caregivers understand the purpose of data collection, they are more likely to provide accurate and complete information. This can improve the quality of the data collected, which can help you in return to gain meaningful insights and develop effective strategies. Improved Engagement: When children and their caregivers understand the purpose of the project and how their data will be used, they are more likely to engage with the project, participate more actively and feel invested in its success. How Have Others Pursued Being Purpose-Driven? An example of the purpose-driven principle can be found in the efforts conducted by the Government of Mongolia to develop an integrated data system. In partnership with the Asia Development Bank (ADB) and UNICEF, the National Statistics Office (NSO) of the Government of Mongolia has been working to enhance the country's capabilities in generating and using high-quality data and evidence. Among other things, the NSO intends to undertake a cross-sectoral assessment of the national data landscape, with the goal being to understand what data is scattered among the numerous administrative data systems and what data is lacking. This assessment aims to formulate a comprehensive roadmap for the development of an integrated data system to enhance the delivery of public services to children. To support this effort, UNICEF has recommended using the Administrative Data Maturity Model (ADaMM). This model will provide the NSO with a structured approach to identify strengths and weaknesses in the national administrative data landscape, prioritize areas for improvement, and allocate resources effectively. Because an integrated data system will allow the collection, processing, sharing, analysis, and use of information from multiple entities spanning diverse sectors, they will offer a more holistic understanding of the children whose data has been captured—regardless of the services they received in the first place and the administrative data system that originally captured their information. By identifying a purpose for separate streams of data collection, and a purpose for their integration, the country will be able to generate actionable insights on children's needs, measure progress and bottlenecks towards national goals and drive targeted public interventions to address them. More information can be found here. What Resources Can I Use to Be Purpose-Driven? In the RD4C toolkit, the 22 Questions methodology offers a set of questions for quickly evaluating projects or systems that manage data concerning children and can help you identify whether your work is purpose-driven and address any spotted gaps in this regard. Outside the RD4C Toolkit, practitioners may find useful models in The 100 Questions Methodology and Problem Definition Tool, both of which provide means of defining purpose. *** We hope this blog has been useful to you in helping you understand what it means to prevent harms across the data lifecycle. This marks the end of our Seven Principles series, but you can receive updates on future blogs by signing up to our mailing list here.Read more
New PublicationIntro to the Responsible Data for Children Principles: Prevention of Harms
This blog is part of a running series from the Responsible Data for Children initiative highlighting each of the RD4C principles and real-life efforts to realize them. You can learn more about this series here. Ahead of International Youth Day on 12 August, today’s blog looks at the importance of preventing harms for children and youth across the data lifecycle and which resources are available to you to operationalise it. It also highlights how UNICEF, the Ministry of Social Affairs and other partners in Guatemala embedded this principle into CPIMS+/Primero for uprooted children and youth. What is Prevention of Harms Across the Data Lifecycle? Data is a powerful tool. When used well, data has the potential to uphold children’s rights and offer critical insights to ensure informed services. Like any power tool, however, data needs safeguards. If used badly, data can erode children’s rights, including their right to privacy, and expose them to serious dangers and harms. This is especially true for children in vulnerable contexts such as uprooted children and youth (whether refugee, displaced or migrant children and youth). As data is not static, but exists as part of a process, the opportunities and risks generated by data handling vary depending on the stages of the data lifecycle (when planning, collecting, processing, sharing, analyzing, using data). Though the data lifecycle can take various shapes, RD4C has consistently referred to the following stages: Planning: Defining specific objectives of a data activity; Collection: Gathering data directly from the field or collating it; Processing: Removing irrelevant or inaccurate information; Sharing: Exchanging data and other information with relevant collaborators; Analyzing: Assessing the data to extract insights; Using: Acting on the insights derived. As part of a commitment to data responsibility, people handling data for and about children in any way, at any of the stages of the cycle, can assess and take action to prevent risks across the full data lifecycle. This work includes avoiding risks of misuse (i.e. ensuring protection of data and preventing a use of data that would erode children’s rights) and missed use (i.e. ensuring promotion of data and preventing a situation where data could be used to uphold children’s right, but is not). This concept is called end-to-end data responsibility, which is essential for ensuring trust. How Have Others Pursued Prevention of Harms Across the Data Lifecycle? The CPIMS+/Primero is an open-source child protection system used in more than 50 countries. It provides clear workflows to assist social services workers with documenting case management processes — from identification and registration, to assessment, case planning, referrals and transfers, and case closure. Designed with and developed by child protection caseworkers and social service providers, it allows users to define who can see specific data and perform determined actions to ensure confidentiality, privacy and security. By allowing many organizations and users to securely manage their caseloads on a single database, CPIMS+/Primero helps ensure that the data is of high quality, without duplication, and therefore reliable for analyses and reporting. Together with UNICEF in Guatemala, the Ministry of Social Affairs (Secretaría de Bienestar Social, SBS, in Spanish) rolled out a customized version of CPIMS+ in 2021—prioritizing its implementation in shelters and departmental agencies for returnee children from Mexico and the United States of America. With the thorough assessment and analysis of the data collected, the Government is taking a proactive approach to improve the insights generated about and enhance case management of children—including referral to appropriate child protective services for vulnerable, excluded, or at-risk children, family search and reunification and/or alternative family care, as well as follow-up and support for children and families. Careful attention to harm prevention at each stage of the data life cycle is necessary, but can be quite time-intensive. To overcome these challenges, CPIMS+/Primero provides accountability and supervision features that ensure individual and safe oversight throughout the management of a case. Access is role-based to allow only authorized staff to access sensitive information. Additionally, UNICEF and the SBS, share an agreement that specifies how the safety of data will be handled and what the responsibilities between the institutions and the system are. Two of the most important clauses guarantee the responsibility of the State to protect CPIMS+ data and specify the modalities of data sharing between UNICEF and SBS through information exchange protocols. What Resources Can I Use For Prevention of Harms Across the Data Lifecycle? The RD4C Studio Methodology provides a tool for organizations striving to address children's needs through data to assess the risks and opportunities related to that data at each stage of the data lifecycle. The Methodology comprises a sequence of interdisciplinary participatory workshops following a five-step approach, namely (1) Kick-off, (2) Research, (3) Convene & Ideate, (4) Output Draft, and (5) Release. This stepped approach empowers organizations to prioritize pressing issues, gather diverse insights from key stakeholders, including children and youth, and work collectively towards impactful and responsible data use throughout a project for the well-being of children. *** We hope this blog has been useful to you in helping you understand what it means to prevent harms across the datalifecycle. Please return to our blog next week when we’ll discuss our next principle or subscribe for updates to the RD4C initiative by signing up to our mailing list here.Read more
New PublicationIntro to the Responsible Data for Children Principles: Participatory
This blog is part of a running series from the Responsible Data for Children initiative highlighting each of the RD4C principles and real-life efforts to realize them. You can learn more about this series here. What Does Participatory Mean? The Participatory principle highlights the necessity of actively involving and seeking input from those who are impacted by data use, such as children, their caregivers, and the communities in which they reside. Within the context of a data-based initiative, it is imperative for actors to inform and engage with individuals and groups, paying attention to marginalized and vulnerable populations. By adopting a participatory approach, actors can gather valuable insights and perspectives from key stakeholders. This approach goes beyond simply informing individuals and groups; it involves engaging them in meaningful dialogue and decision-making processes to ensure their voices are heard, their needs are understood, and their concerns addressed consistently throughout the entire lifecycle of data initiatives, from the planning to implementation, to ensure the activities capture people’s insights and feedback regularly and are relevant to their needs. The participatory principle is related and complementary to the people-centric principle. However, while the people-centric approach means considering the effects of data practices on children and communities, prioritizing their well-being over efficiency gains, being participatory underscores the importance of engaging and informing individuals and groups affected by data use. Both approaches are complementary and essential for ensuring ethical and impactful data use. When being participatory, it is important for the organization leading the data initiative to give particular attention to marginalized and vulnerable populations, as they may have unique challenges and perspectives that need to be taken into account, so as to avoid perpetuating and generating new discriminations through the use of data. To engage with these groups in a just and ethical way, it is important to approach them being mindful and respectful of the challenges and vulnerabilities these individuals may face. Proper training for enumerators, officers, and all involved in the data initiative is essential to equip them with the necessary skills to approach conversations with empathy, respect, and cultural sensitivity, ensuring the well-being and safety of those involved. In addition, it is important for the organization to ensure the engagement with vulnerable populations is coordinated, so as to prevent the burden of overlapping or duplicative activities. Collaboration among multiple actors and organizations involved in data initiatives is crucial for streamlining efforts and minimizing disruptions within these communities. Through the ethical involvement of these groups, and by gaining their unique and marginalized perspective, organizations can hope to address potential biases, inequalities, and power imbalances that may exist in the data ecosystem. How Have Others Pursued Being Participatory? An example of the Participatory principle in action can be observed through the deployment of InForm, an Open Data Kit-based data collection and management tool. InForm centralizes dispersed data streams, ensuring the secure storage of collected data on a single platform, and facilitating data analysis and visualization. An impactful instance of using the InForm platform occurred during emergency response efforts in Mozambique and Zimbabwe. In March 2019, Cyclone Idai struck near Beira City, Sofala Province, causing immense devastation through powerful winds and heavy rainfall. This disaster resulted in the loss of numerous lives, destruction of livelihoods, and damage to property. The region witnessed hundreds of fatalities, with Mozambique alone facing a staggering 2.2 million people requiring urgent assistance. InForm's participatory nature is especially reflected in its reliance on collaborative engagements. Indeed, the initiative actively involves and seeks input from various stakeholders, including the local communities affected by the cyclones, partner organizations such as the World Food Program (WFP) and United Nations High Commissioner for Refugees (UNHCR), and other key actors. By incorporating their perspectives, needs, and local knowledge, InForm ensures that the data handling processes are shaped by the insights and expertise of those directly impacted by the disaster. What Resources Can I Use to Be Participatory? RD4C has developed two tools in particular that may be useful in an effort to be participatory. First, the 22 Questions methodology offers a set of questions for quickly evaluating projects or systems that manage data concerning children, adopting a participatory approach. Additionally, the RD4C Studio Methodology provides a participatory tool for organizations striving to address children's needs through data. The Methodology comprises a sequence of interdisciplinary participatory workshops following a five-step approach, namely (1) Kick-off, (2) Research, (3) Convene & Ideate, (4) Output Draft, and (5) Release. This participatory approach empowers organizations to prioritize pressing issues, gather diverse insights from key stakeholders, and work collectively towards impactful and responsible data use for the well-being of children. *** We hope this blog has been useful to you in helping you understand what it means to be participatory. Please return to our blog next week when we’ll discuss our next principle or subscribe for updates to the RD4C initiative by signing up to our mailing list here.Read more
The RD4C initiative is a joint endeavor between UNICEF and The GovLab at New York University to highlight and support best practice in our work; identify challenges and develop practical tools to assist practitioners in evaluating and addressing them; and encourage a broader discussion on actionable principles, insights, and approaches for responsible data management.
The work is intended to address practical considerations across the data lifecycle, including routine data collection and one-off data collections; and compliments work on related topics being addressed by the development community such as guidance on specific data systems and technologies, technical standardization, and digital engagement strategies.
Additional tools and materials are coming soon and will be posted on this website as they become available. Join the conversation to receive regular updates.