Inclusive data

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The Inclusive Data Playbook signposts practical resources and approaches to help users start, strengthen, and sustain inclusive data practices within their own contexts.

It does not create new content or set out a manual or template for inclusive data. This is because the journey to inclusive data is different for each context. Therefore, the Inclusive Data Playbook presents and describes resources intended to support and improve inclusive data systems. The descriptions are thorough yet succinct, allowing users to skim the Playbook to select the resources that are most relevant. Through this Inclusive Data Playbook, organizations will be able to gain insight on where to start and how to navigate the inclusive data space more efficiently.

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What makes data inclusive and why it matters

Data needs to reflect the realities of all people’s lives with their consent and participation—especially those who are poor, marginalized, vulnerable, or underrepresented. Without inclusive data, decision-makers risk designing policies and programs that overlook or exclude parts of the population. Therefore, inclusive data is critical to achieving the SDGs and ensuring that progress truly benefits everyone.

Data disaggregation, i.e., breaking down datasets based on identities and characteristics— including gender, age, race, ethnicity, religion, disability, and socioeconomic status—helps to better reflect the situation of different population groups. Disaggregation uncovers inequalities, exclusion, and how the poorest and most marginalized are affected by policies and within services. An intersectional approach is the analysis of how these characteristics and identities overlap. It looks at systemic inequalities and their root causes, drivers, and effects and gives a more comprehensive understanding of the complexities of marginalization, inequality, and exclusion.

Citizen data is data produced by and with sufficient engagement of citizens, communities, civil society organizations, and others at the design and/or collection stages of the data process. It aims to inform decision-making and responds to specific needs of a community, supplementing existing data of national statistics systems or filling data gaps. There is increasing recognition of the power and potential of citizen data, especially where data is produced in partnership between citizens and officials or where citizens actively control the entire data process.

Inclusive data goes beyond data disaggregation, intersectional approaches, and citizen data. The case for inclusive data applies to each stage in the data value chain—from collection and analysis through dissemination and use. It requires open, transparent processes designed to share data with people and communities from whom it is collected and must build the capabilities of data users. Data governance, mechanisms, and decision-making must also be inclusive of citizens through participation, ensuring data is ethically used to benefit everyone.

Yet, while momentum around inclusive data is growing, inclusive data remains challenging to implement in practice. Many data actors—particularly within NSOs—may not be aware of existing resources, guidance, and good practices available to support this work. They may also face competing priorities or have limited time to research and apply relevant approaches. In addition, inclusive data often cuts across multiple disciplines and priorities, making it difficult for data actors to keep track of tools and frameworks. While numerous resources exist, they may not be easy for data actors to locate and assess. Addressing this gap is essential to making inclusive data the norm and ensuring no one is left behind.

Refer to the list of abbreviations used throughout the Playbook here.

Who the toolkit is for and how to use it

Responding to this need and building on the progress to advance Leave No One Behind and to strengthen data systems to be more inclusive, the Inclusive Data Playbook is designed to help data actors quickly find, understand, and apply existing resources that support inclusive data practices. It is primarily aimed at supporting technical staff at NSOs but is a useful tool for other data actors, such as line ministries, multilateral organizations, and civil society organizations.

The Inclusive Data Charter served as a core document for defining inclusive data and identifying the potential topics for inclusion, while a desk review of Make Inclusive Data the Norm project materials and stakeholder consultations with project partners and Global Partnership staff helped to define the Playbook’s focus. Read more about the methodology here.

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In sports, playbooks often provide diagrams and brief descriptions of each play. Unlike a manual, they do not prescribe the plays, since the coach decides the strategy and which plays to use, depending on the context. The Inclusive Data Playbook is set up in the same spirit. Inclusive data is multifaceted and has many different approaches or “plays.” It is organized into four topics, focusing on the core approaches.

A glossary and full list of resources are included in the annexes for easy reference.

The four Playbook topics:

Cross-cutting and general resources, such as overarching frameworks, strategies, and plans for inclusive data systems, including case studies and examples;
Data disaggregation, with subsections on gender, children, LGBTQI, race/ethnicity and Indigenous People, and disability, containing technical guidance, checklists, resource repositories, and case studies or examples;
Intersectionality, with guidance and diverse case studies applied to different contexts; and
Citizen data, with standards, reports, guidance, maturity models, and case studies.

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The Inclusive Data Playbook allows users to browse by topic, consider the relevant stages of the data value chain, and quickly identify the most relevant resource for their needs and context. Most resources address more than one challenge, such as definitions, rationale or making the case for inclusive data, identifying strategies or plans, providing technical advice, and demonstrating practice through examples.

The Playbook is particularly helpful in finding a starting point for identifying the right tools to support inclusive data work.

Each resource is presented using a consistent format, including title, author, type, location or hyperlink, overview, and topics covered, plus:

Stages in the data value chain, each resource is mapped to the relevant stage of the data process, guiding users on when the resource may be applied. For ease of reference, Open Data Watch and Data 2X’s 12-step framework is the first entry in the Inclusive Data Playbook
Case studies/examples, noting whether the resource is or contains case studies or examples of practice
Additional information, providing details unique to each resource, such as information about translated versions, suggested use, limitations, or other considerations

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Explore the resources

The Inclusive Data Playbook is not intended to be read cover-to-cover, nor is it intended to be prescriptive, as each context for inclusive data is different. Instead, it allows users to browse by topic, consider the relevant stages of the data value chain, and quickly identify the most relevant resource (or ‘play’) for their needs and context. Most resources address more than one challenge, such as definitions, rationale, or making the case for inclusive data, identifying strategies or plans, providing technical advice, and demonstrating practice through examples. The Playbook is particularly helpful in finding a starting point for identifying the right tools to support inclusive data work.

Explore the tools and resources below.

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Cross-Cutting and General Resources

Effective inclusive data work relies on strong foundations, including principles, frameworks, strategies, and structures. This section provides overarching resources to define and make the case for inclusive data, the norms and standards to guide the work, and examples of practical tools for a whole systems approach, such as governance models, strategies, and advisory bodies.

https://www.data4sdgs.org/cross-cutting-and-general-resources

Books and papers with coloured tabs. Kelsy Gagnebin / Unsplash

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Data Disaggregation

Data disaggregation is the process of breaking down aggregated or compiled data into smaller, more detailed subgroups based on specific characteristics, such as gender, age, disability, and ethnicity. Disaggregating data allows for deeper analysis to reveal who is being left behind and is is foundational for inclusive policymaking.

/data-disaggregation

Coloured stipes. John Schaidler / Unsplash

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Intersectionality

An intersectional approach to data recognizes that people’s experiences are shaped by multiple, overlapping characteristics and identities, including gender, age, ethnicity, disability, and income. Inequality cannot be fully understood by looking at any single dimension in isolation. Integrating intersectionality into data systems enables more accurate and nuanced insights into who is being left behind and why.

/intersectionality

Diversity in paper cutouts. Katie Rainbow / Pexels

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Citizen Data

Citizen data refers to data originating from initiatives where people, communities or civil society organizations either initiate or are sufficiently engaged in the design and/or collection stages of the data value chain. It aims to inform decision-making, responding to the specific needs of a community, and can include community surveys, participatory mapping, social audits, crowd-sourced reporting, and more. When designed and managed responsibly, citizen data can supplement official data, filling critical gaps, particularly for marginalized groups who are often left out.

https://www.data4sdgs.org/citizen-data

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Conclusion

Inclusive data is more than a technical aspiration. It is a collective commitment to ensuring that everyone counts and that people’s experiences are visible in the evidence that drives decisions. Across NSOs, ministries, multilateral organizations, and civil society, progress toward inclusive data requires continuous effort to strengthen data systems, challenge biases, improve methods, and build partnerships that value diversity.

This Inclusive Data Playbook describes the tools, frameworks, and case studies that can support this journey. Rather than prescribing a single pathway to inclusive data, it offers a menu of proven approaches that users can adapt to their own contexts or use as inspiration. From improving data disaggregation and embedding intersectional approaches to partnering with communities and using citizen data, the Inclusive Data Playbook provides insight so that users can identify that crucial starting point.

Inclusive data work is ongoing. As data systems evolve, the resources and practices will also evolve. Since 2018, the Global Partnership has facilitated the Inclusive Data Charter initiative, mobilizing political commitments, collaboration, and knowledge-sharing to advance the use of inclusive and disaggregated data so that governments and other organizations better understand, address, and monitor the needs of marginalized groups and ensure that no one is left behind. Representatives from national statistics offices, ministries, civil society, multilateral organizations, academia, and other sectors may join the Inclusive Data Charter and learn from its Champions. Contact details and further information can be found on the Global Partnership’s webpage on the Inclusive Data Charter.

By putting inclusion at the center of data systems, we can ensure that no one is invisible, no decision is made without evidence that reflects lived experience, and no one is left behind.

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