DATA SCIENCE FOR PEACE
Peace Data Standard
A framework for measuring positive engagement across difference boundaries.
Most systems measure conflict and harm more easily than peace. The Peace Data Standard helps organizations identify the behaviors, relationships, and interaction patterns that create trust, reciprocity, inclusion, and mutual benefit.
Why This Matters
Peace is often discussed as an aspiration, but rarely measured as a behavioral outcome.
Organizations collect enormous amounts of interaction data, but most systems are better at recognizing harm, complaints, risk, and conflict than identifying the interactions that produce positive peace.
Without a standard, peace impact remains difficult to compare, fund, design, or audit.
The Peace Data Standard offers a practical way to structure evidence of positive engagement across difference boundaries.
What The Standard Is
The Peace Data Standard helps organizations identify and structure data about positive engagement across difference boundaries.
A simple model for moving from everyday interaction to measurable positive peace.
How Peace Becomes Data
Who Can Use the Peace Data Standard
From Research Concept to Usable Practice
The Field Guide translates the research framework into practical tools for identifying peace-relevant data, designing indicators, mapping difference boundaries, evaluating interaction patterns, and building ethical measurement systems.
GROUNDED IN PUBLISHED RESEARCH
Guadagno, R.E., Nelson, M., & Lee, L. (2018). Peace Data Standard: A Practical and Theoretical Framework for Using Technology to Examine Intergroup Interactions.Frontiers in Psychology, 9:734.
The Peace Data Standard paper presents a theoretical framework for standardizing Peace Data, for identifying, using, collecting and evaluating mutually beneficial outcomes from episodes of engagement and emphasizes ethical considerations and future research directions.
Developed through Peace Innovation Lab research on positive engagement, technology mediated interaction, and peace technology.
Frequently Asked Questions
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The Peace Data Standard is a framework from the Peace Innovation Lab at Stanford for identifying, structuring, and evaluating data about positive engagement across difference boundaries.
It helps organizations measure peace as observable behavior: communication, response, reciprocity, repair, collaboration, trust-building, inclusion, and mutual benefit between people or groups.
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The standard helps identify whether interactions across difference boundaries are producing positive engagement.
It can be used to examine signals such as who initiates contact, who responds, how often interaction repeats, whether engagement becomes reciprocal, whether relationships strengthen over time, and whether the interaction creates mutual benefit.
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The four dimensions are:
Group Identity Information — the groups, roles, communities, or difference boundaries involved in an interaction.
Behavior Data — observable actions such as communication, response, exchange, collaboration, help, repair, or follow-through.
Longitudinal Data — repeated interactions over time that reveal whether relationships are becoming more reciprocal, durable, inclusive, or mutually beneficial.
Metadata & Context — information about timing, frequency, directionality, setting, platform, network position, and other conditions shaping the interaction.
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A difference boundary is a social, cultural, institutional, demographic, geographic, political, professional, or identity-based distinction that shapes interaction between people or groups.
Examples include nationality, religion, gender, race, ethnicity, language, class, political identity, role, organization, team, discipline, or geography.
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Peace becomes data when observable engagement across a difference boundary can be identified, structured, and evaluated over time.
The basic sequence is:
Difference Boundary → Engagement Episode → Interaction → Relationship Over Time → Group Pattern → Peace Impact
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Conflict data usually measures harm, violence, complaints, incidents, risk, polarization, or breakdown.
Peace Data measures constructive interaction: trust, reciprocity, inclusion, collaboration, repair, repeated engagement, and mutual benefit. It helps organizations see where positive peace is being created, not only where harm is occurring.
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Most organizations are better at measuring problems than measuring positive social value. They can count incidents, complaints, churn, violations, and risk, but often lack a way to identify constructive cross-boundary engagement.
The Peace Data Standard helps make positive peace visible, measurable, and designable.
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The standard can be used by researchers, product teams, foundations and funders, governments and civic institutions, peacebuilding organizations, social impact organizations, and technology platforms.
It is especially useful for organizations that already generate interaction data but have not yet interpreted that data through a peace or positive engagement lens.
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Peace Dot / peace.facebook was an early collaboration between the Stanford Persuasive Technology Lab, the Peace Innovation Lab, Facebook, and other technology partners to measure peace on the internet.
The project tracked daily friending activity across geographic, political, and religious difference boundaries. It demonstrated that positive cross-boundary engagement could be counted, visualized, and studied over time.
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Within the broader Peace Innovation Lab architecture, the Peace Data Standard is the measurement layer.
Peace Canvas helps teams design for positive engagement. A Pattern Language for Peace describes recurring design patterns. Peace Engineering frames the field-level practice of designing systems that make positive peace easier to produce, measure, and sustain.
Start identifying the Peace Data your organization already creates.
If your organization creates interactions across difference boundaries you may already be generating Peace Data. The next step is learning how to recognize it, structure it, and use it responsibly.
