The Responsible Data for Children (RD4C) initiative—a collaboration between The GovLab and UNICEF to promote the more responsible handling of data for and about children—has spent much of 2022 developing ways to socialize and operationalize the principles that put the best interests of children and a child rights approach at the center of our data activities.. From publishing new case studies that provide detail on what a responsible data approach looks like in action to supporting UNICEF and UNHCR country offices in helping them implement a responsible data for children approach to their operations to expanding its offerings in different languages, we’ve sought to help organizations understand what responsible data for children means and how they can realize it in their day-to-day operations. Today, RD4C is continuing this work with self-guided training. Based on the tutorials offered to UNICEF staff in early 2022, these slides are a resource for organizations seeking to understand ways to operationalize the RD4C principles and implement the RD4C tools.

1. Responsible Data for
Children Training
Responsible Data for Children
November 2022

2. Session 1:
Everything You Wanted to Know about
Responsible Data for Children But Were
Afraid to Ask

3. Agenda
Primer on Responsible Data for Children
Principles and Lessons from the Field
An explanation of what the Responsible Data
for Children principles are and why they are
relevant to development organizations
Surfacing Fears, Challenges, Pain Points,
and Promising Practices
Discussion questions for data practitioners to
reflect on their responsible data questions
and experiences

4. Responsible Data for Children is a joint
endeavor between UNICEF and The GovLab at
New York University to highlight and support
best practice in handling data for and about
children; 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.
What Is Responsible Data for Children?
https://rd4c.org/

5. The Responsible Data for
Children Principles

6. What Are The Principles?

8. WHAT IT IS: InForm is 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. It supported Cyclone Idai and Kenneth response.
HOW IT IS PARTICIPATORY: Any deployment requires connecting
disparate sources held by various parties. It calls on agencies to work
together to ingest and centralize many data sources instead of having
them engage only with their own data systems and data collection
processes.
Example: InForm
PARTICIPATORY

9. CHALLENGES:
● Securing Buy-In: Partners can have different priorities and it can be
difficult to convince them to exert effort to an initiative unless they
see it as directly connected to their needs.
● Time and Resource Constraints: Data practitioners often operate
with severe limitations on their capabilities, limitations that can
impede pre-planning or engagement activities.
ENABLERS:
● Engage with affected communities: Engaging with local
communities can increase situational awareness and provide
insights that may not otherwise be represented in the data.
● Assess contextual data risks and opportunities: Certain types of
data about children are always sensitive but others might only be
sensitive in particular environments — engagement with experts
and affected communities can help surface these issues.
Challenges & Enablers
PARTICIPATORY

11. WHAT IT IS: Afghanistan’s Nutrition Online Database was 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 Nutrition Online Database tried 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.
HOW IT IS PROFESSIONALLY ACCOUNTABLE: Afghanistan and
partners provided training to data users to more effectively monitor
conditions. Administrators also received manuals with guidance on
how to avoid unauthorized access. It recommended maintaining an
up-to-date user list and conducting regular checks for risks of
unauthorized access. The manual also encouraged administrators to
carefully check the list of users for whom the administrator is
responsible and to block users when they leave the organization.
Example: Nutrition Online
Database
PROFESSIONALLY ACCOUNTABLE

12. CHALLENGES:
● Fragmentation: A wide array of stakeholders can be involved in
systems. These stakeholders can include actors exerting
decision-making power over distinct but closely related systems.
Fragmentation can disrupt efforts to promote common standards.
● Embedding good practices: While organizations can establish
policies and procedures to promote accountability, additional steps
to socialize and embed them in day-to-day practice can be
challenging.
ENABLERS:
● Manage internal access: Ensure only authorized personnel have
access to children’s information and establish an audit trail.
● Clearly define lines of responsibility: Many decisions are made
across the data life cycle, and establishing and making visible who
is responsible (and accountable) for those decisions can guard
against confusion or gaps.
Challenges & Enablers
PROFESSIONALLY ACCOUNTABLE

13. ● Used to identify key decision points and
determine which internal and external parties
influence those decision points.
● The Decision Provenance Mapping focuses on
the principle of Professionally Accountable,
providing ways for actors to ask:
○ Are roles and mandates defined and
understood?
○ Is the decision flow sufficiently transparent?
○ Is there communication between
decision-makers across the data lifecycle?
○ Are decision-making processes captured by
knowledge management systems?
https://bit.ly/RD4CDecProv
PROFESSIONALLY ACCOUNTABLE
Tool: Decision
Provenance Mapping

15. WHAT IT IS: The Aurora Project is a child protection platform
developed by UNICEF Romania with 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.
HOW IT IS PEOPLE-CENTRIC: The Aurora platform and its
components were crafted in recognition of the influence and
importance of not just a child’s experience and needs but also that of
their caregivers. Frontline workers using the system are guided
through a clear and well signposted process of engaging and drawing
relevant information from children and others in the household.
Example: Aurora Project
PEOPLE-CENTRIC

16. CHALLENGES:
● Clarifying Public Perspectives: Even with a people-centric
approach as a “North Star,” practitioners can face challenges in
determining what children and their communities deem to be
important (or inappropriate) uses of data for and about them.
ENABLERS:
● Prioritize Creating Human Value: Effective data use can
create many benefits, including efficiency gains. While
valuable, a responsible approach prioritizes benefits for
children and their communities over process improvements.
● Scrutinize Inferred Data Prior to Use: Inferred personal data
is information about a child that can be interpreted through
multiple pieces of existing data.
Challenges & Enablers
PEOPLE-CENTRIC

18. WHAT IT IS: UNICEF launched MICS in 1995 to monitor the status of
children around the world. MICS surveys are conducted by trained
fieldworkers who perform face-to-face interviews with household
members on a variety of topics. For the 2019 deployment, ZIMSTAT
approached the MICS team to integrate a domestic violence module
to counteract a lack of data on the incidence of domestic and
gender-based violence.
HOW IT IS PREVENTATIVE OF HARMS: The MICS team emphasized
that ensuring the security of the data was paramount. During survey
collecting, they discussed how data collected in the field undergoes
rigid checks for quality during the interview process—checking and
cross-checking data across the interview. Data is then uploaded to a
secure cloud server which is accessed by the national implementing
partner and UNICEF.
Example: Multiple
Indicator Cluster Surveys
PREVENTION OF HARMS ACROSS THE DATA LIFE-CYCLE

19. CHALLENGES:
● Procedural Challenges and Delays: Careful attention to harm
prevention at each stage of the data life cycle is necessary but can be
time intensive.
● Identifying Group Data Risks: Aggregated data can still pose risks to
groups of children is not handled carefully; yet group data risks — e.g.
the mosaic effect — can be difficult to identify and mitigate.
ENABLERS:
● Research the policy ecosystem and previous practice: Build
projects following a detailed review of legal and policy frameworks,
existing services, guidance, and capacities that may have
implications for the development of a data initiative
● Take a lifecycle approach to risk assessment: Risks (and
opportunities) can emerge at each stage of the data lifecycle;
examining each stage in turn can help guard against oversights.
Challenges & Enablers
PREVENTION OF HARMS ACROSS THE DATA LIFE-CYCLE

20. ● A set of questions that lets organizations take
stock of the Responsible Data for Children
principles and how they might be realized in a
data project or system.
● Avoiding unintended negative consequences
on data subjects and beneficiaries requires
organizations handling data for or about
children to understand what dangers they need
to be cognizant of.
https://bit.ly/RD4COpRisk
Tool: Opportunity and
Risk Diagnostic
PREVENTION OF HARMS ACROSS THE DATA LIFE-CYCLE

21. ● For rapidly assessing initiatives or systems
that handle data for and about children
against the Principles.
● The Audit Tool’s 22 questions are derived
from combinations of the Responsible Data
for Children Principles.
● It helps these actors move quickly on urgent
challenges and act on opportunities.
https://bit.ly/RD4C22Qs
Tool: 22 Questions to
Assess Responsible
Data for Children
PREVENTION OF HARMS ACROSS THE DATA LIFE-CYCLE

23. Example: Cellule d’analyse
Intégrée
PROPORTIONAL
WHAT IT IS: CAI is an operational research and analytics cell
created by UNICEF to provide local and national officials, UN staff,
and associated partners with integrated and actionable evidence
to respond to public health emergencies. It came about to support
the response to the 10th Ebola outbreak in the eastern part of the
Democratic Republic of the Congo.
HOW IT IS PROPORTIONAL: The CAI team only collects data
when they can be sure it will be relevant and used. The team
involves the data users from the outset so that it is not
overburdening communities and ensure their work has use. The
team does not collect information beyond the specific scope of
operational research or data if it can find another study providing
“good enough” or similar work to avoid excessive collection.

24. CHALLENGES:
● Referrals for ethically challenging cases: Teams sometimes face
difficult ethical situations that require referral or dedicated procedures
to address. The local teams are not always knowledgeable on what
procedures to follow, particularly when weighing multiple interests.
ENABLERS:
● Consider data’s relevance and value over its lifespan: Identifying the
length of information’s lifespan requires users to look at applicable laws
and organizational or professional policies.
● Ensure legitimacy of re-use: Many applications of data for children are
the result of secondary use, the use of data for something other than its
initial purpose. It is important to identify these uses and ensure they are
considered appropriate in the communities they operate.
● Destroy Outdated or Superfluous Data: Data users should have a
clear process for identifying when and why data about children should
be retained, when it should be archived, and when it should be
destroyed to avoid accumulating risk for minimal value and/or using
data that is anachronistic and no longer relevant or applicable.
Challenges & Enablers
PROPORTIONAL

26. WHAT IT IS: 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.
HOW IT IS PROTECTIVE OF CHILDREN’S RIGHTS: Only approved
staff members have the necessary digital credentials for accessing,
changing, or printing certain case records. The system also creates an
audit trail when a user edits, deletes, or prints a client record—but not
when a user only accesses the record. The system also ensures staff
can only access sensitive client records while physically present at
the Childline premises and connected to its network, helping to avoid
unauthorized remote access.
Example: Childline Kenya
PROTECTIVE OF CHILDREN’S RIGHTS

27. CHALLENGES:
● Inappropriate External Use: The approach of keeping data “as open as
possible and as closed as necessary” can be a useful frame. Information
made accessible to stakeholders and partners can lead to less control
over secondary use and their respect for children’s rights.
ENABLERS:
● Data as Extension of the Child: A child’s data — including especially
immutable personal information — can be considered as an
extension of their physical person to help inform data handling
activities that support their rights.
● Risk and sensitivity tagging: Different types of data have different
risks and sensitivities. Biometric and health data, data about children
in conflict areas create unique and amplified risks to children’s
privacy and security. Datasets with known or unknown inaccuracies,
biases, and other quality issues can negatively influence analysis and
use. Processes for assessing and tagging these information streams
can ensure responsible handling downstream.
Challenges & Enablers
PROTECTIVE OF CHILDREN’S RIGHTS

29. WHAT IT IS: InForm is 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. It supported Cyclone Idai and Kenneth response.
HOW IT IS PURPOSE-DRIVEN: InForm was developed with a
“user-centric design approach” to ensure that the tool would be
useful for compiling and visualizing data. This fact is evident not only
from the platform’s origins, which sought to respond to a clear,
pressing need to compile data, but to the way UNICEF sought to
respond to that need. Personnel launched a small, inter-agency pilot
in Somalia with multi-stakeholder workshops to determine how to
best operate the tool. . InForm received revisions in response to
feedback, adding new ways to visualize data.
Example: InForm
PURPOSE-DRIVEN

30. CHALLENGES:
● Different Partner Priorities: Different partner priorities can sometimes
hamper the purpose-driven nature of a data program. This requires
parties to have a common understanding of their roles and
expectations, of which data is most important for the immediate context
and how to integrate it into the system.
ENABLERS:
● Articulate intended actions: Establish a legitimate purpose for
information collection prior to collection. Understand what data is
required for the project, why, and for how long.
● Define objectives and establish metrics: Clearly define project
goals and only collect data directly relevant to meeting those goals.
● Avoid missed uses of data: Missed use of data is when useful data
exists (or could exist) but is not used. Missed use can be avoided by
reviewing all available datasets and using them to solve problems
when such use (or re-use) is appropriate and legitimate.
Challenges & Enablers
PURPOSE-DRIVEN

31. Tool: Data Ecosystem Mapping
Tool
PURPOSE-DRIVEN
● Helps users to identify the systems generating data
about children and the key components of those
systems;
● This tool lets actors determine whether the data
system aligns with the RD4C Principles by
providing a framework to capture:
○ WHY the system exists (Purpose-Driven;
People-Centric; and Proportional)
○ WHO is involved (Professionally Accountable and
Participatory)
○ WHAT data is held (Protective of Children’s Rights;
and Prevention of Harms Across the Data Lifecycle)
https://bit.ly/RD4CEcoMap

32. Discussion
Questions
● What are some of the responsible data
for children practices in your
organisation that you are most proud
of?
● What are some of the challenges
you’ve encountered when it comes to
protecting data for and about children?

33. Discussion Session
Debrief