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.

Citizen data empowers communities to produce information that complements official statistics, fills critical data gaps, and informs more inclusive decision-making. The resources in this section illustrate how citizen data can be collected, integrated into official data systems, and used to influence policy and practice. While citizen data may vary in scale and methodology, this section demonstrates that community-led evidence is a vital component of inclusive data systems, enhancing both the relevance and responsiveness of data-driven decisions. Moreover, it shows how effective partnerships between NSOs and communities can solve data challenges and ensure underrepresented voices are heard.

Integrating citizen data into inclusive data systems requires careful attention to data quality, comparability, ethics, and collaboration between civil society and NSOs. The resources in this section make the case for citizen data, set out the principles, provide guidance, and showcase how different actors have implemented citizen data projects. Users from NSOs to CSOs can learn approaches to ensure citizen data is both credible and actionable.

*Citizen data is an all-encompassing term defined in The Copenhagen Framework on Citizen Data. However, many data actors use terms such as citizen-generated data, community data, and more interchangeably. Here the term “citizen” refers to an individual in a society without any connotations related to citizenship. 

An Unequal Pandemic: Insights and Evidence from Communities and Civil Society Organizations

Author: Civil Society Collaborative on Inclusive COVID-19 Data

Type: Report

Location: Global Partnership website

Overview: This report explores how gaps and biases in official data published and used by government agencies and public bodies in response to the COVID-19 pandemic excluded marginalized groups from national responses. This is done by reporting key findings from citizen data sources and advocating for more inclusive data systems. It demonstrates the value of data generated by communities and CSOs in the hope that it will be more routinely used to complement official, government-collected data.

Key topics:

  • Rationale for routine collection of citizen data

Stages of the data value chain:

  • Influence

Includes case studies/examples: Yes, the report provides a list of the 38 studies used for analysis, but does not include direct links or locations for these sources. Additionally, the report provides direct sources for the 60 resources used in the desk review.

Additional information: Useful for making the case for citizen data and providing learning to NSOs on partnerships with civil society and investments in citizen data. Provides recommendations to national statistics offices and civil society organizations.

The Copenhagen Framework on Citizen Data

Author: United Nations Statistics Division

Type: Standards

Location: UN Stats website

Overview: This framework provides a conceptual structure for understanding and using citizen data in official statistics. It gives an overview of citizen data, principles for responsible production, and its incorporation into the national data ecosystem.

Key topics:

  • Objectives, definition, taxonomy, and characteristics of citizen data
  • Levels of participation, stages in the data value chain where citizens can engage, and types of initiatives for data collection
  • Principles for responsible production, quality, and use of citizen data
  • Enabling environment for coordination, production, and use of citizen data within the national data systems
  • A roadmap for planning and implementing citizen data

Stages of the data value chain:

  • Identify
  • Collect

Includes case studies/examples: No.

Additional information: Useful in the planning, monitoring, and accountability of citizen data within national data systems and can serve as a foundation for internal guidance.

Citizen-Generated Data Strategies, Methods, and Evidence—Suite of Tools

Author: Global Partnership 

Type: Guidance/analytical report

Location: Global Partnership website

Overview: This suite of tools introduces complementary resources on citizen data aimed at helping diverse stakeholders to assess whether citizen data is appropriate, understand the different approaches of citizen data, and decide how to design and proceed with citizen data, particularly in relation to SDG monitoring and implementation. Together they form a “strategy, method, and evidence” set for engaging with citizen data.

Resources:

  • Choosing and Engaging with Citizen-Generated Data: This guidance provides a framework to guide decisions about citizen data design, including defining goals, deciding on an approach, considerations for stakeholder participation and arrangements, practical planning (e.g., resources, tools, and support required), advice on making data public, and risks and ethical considerations (e.g., data protection, dealing with sensitive data).
    • Identify, Collect, Process, Analyze, Connect, Use
  • Advancing Sustainability Together? Citizen-Generated Data and the Sustainable Development Goals: This analytical report looks at examples of citizen data initiatives across sectors and countries, classifying approaches and analyzing how governments engage with citizen data. It helps to illustrate how citizen data can be used to fill data gaps, especially concerning SDG reporting, and provides examples of cutting-edge approaches, such as citizen journalism, crowdsourcing, participatory design, social media listening, and much more.
    • Identify, Collect, Process, Analyze, Connect, Use, Reuse

Includes case studies/examples: Yes, both documents include many diverse examples and/or case studies to illustrate methods. Some examples appear in both resources.

Additional information: Available in English and Spanish. Useful for planning or piloting citizen data projects, highlighting possibilities, trade-offs, and partnership dynamics.

Citizen-Generated Data in Kenya: A Practical Guide

Author: Global Partnership 

Type: Guidance/case study

Location: Global Partnership website

Overview: This guide presents methods, standards, and reflections aimed at improving the quality and usability of citizen data in Kenya. It is targeted at civil society organizations, governments, and NSOs and addresses how to make citizen data more rigorous, credible, and integrated with official data systems, ensuring that citizen data can influence policy, close data gaps, and be trusted by decision-makers. 

Key topics:

  • Rationale and definition of citizen data and its link to official statistics
  • Data quality assurance practices and insight on the data value chain, i.e., data processes
  • Identifying the purpose for which data will be produced
  • Developing data collection plans, methods, and instruments, including sample design and methods
  • Data collection preparation, such as training personnel, testing processes, consent, and supervision
  • Data processing, analysis, and dissemination, including cleaning, classification, and metadata
  • Privacy, confidentiality, anonymization, and data protection
  • References validation of citizen data under the Kenya Statistical Quality Assurance Framework, tying citizen data to official data systems

Stages in the data value chain:

  • Identify
  • Collect
  • Process
  • Analyze
  • Release
  • Disseminate
  • Connect
  • Use

Includes case studies/examples: Yes, this guide draws on examples from Kenyan civil society, e.g., how local CSOs collected and processed data, the challenges they encountered, and lessons learned. Most of the examples are at the subnational/project level.

Methodological Guidelines on the Collection and Use of Citizen-Generated Data for Reporting SDG 5 and Gender-Specific Indicators in Other SDGs

Author: UN Women

Type: Methodological guidance 

Location: UN Women website

Overview: This resource presents a framework to help CSOs, NSOs, and others systematically collect, compile, and use citizen data to support gender equality monitoring, especially pertaining to SDG5 on gender equality and other gender-relevant indicators. It explores how citizen data can complement official sources, addresses methodological challenges, and provides advice on aligning citizen data production with statistical principles and institutional processes. 

Key topics:

  • Rationale for and limitations of integrating citizen data into national gender data systems
  • The Frameworks for Gender Equality and Women’s Empowerment
  • Advantages and disadvantages of commonly used citizen data methodologies
  • Methodological principles and the data value chain
  • Stakeholder mapping, coordination structures, and mechanisms for citizen data
  • Capacity-building approaches
  • Assessment, design, and implementation of data collection of citizen data
  • Quality assurance, publication, and dissemination of citizen data
  • Uptake, use, and impact of citizen data

Stages of the data value chain:

  • Identify
  • Collect
  • Process
  • Analyze
  • Release
  • Disseminate
  • Connect
  • Use

Includes case studies/examples: Yes, there are examples of citizen data approaches, including surveys and grassroots data collection projects to demonstrate key points, as well as examples of NSO-CSO partnerships. 

Additional information: Approaches and learning can be applied to areas beyond gender. Technical guidance is light and may need to be supplemented with additional resources. Useful for influencing the integration of citizen data into official systems.

Reusing Citizen-Generated Data for Official Reporting: A Quality Framework for National Statistical Office-Civil Society Engagement

Author: Paris 21

Type: Guidance/discussion paper

Location: Paris 21 website

Overview: This resource explores how citizen data can be reused for official reporting, rather than being viewed as purely supplementary. It outlines conceptual framing, criteria for assessing reuse potential, and institutional, methodological, and governance considerations for bridging citizen data with official data. The aim is to help NSOs, government ministries, and data users to understand when and how citizen data might be credibly incorporated into national reporting. 

Key topics:

  • Current debates, definitions, and processes for citizen data
  • Rationale for NSOs to use citizen data and ways for NSOs to identify citizen data
  • NSO guidance on developing a quality assurance assessment framework for citizen data
  • Developing the scoring matrix for quality assurance
  • Establishing minimum quality levels for citizen data
  • Recommendations for NSOs to integrate citizen data into national systems

Stages in the data value chain:

  • Identify
  • Process
  • Analyze
  • Connect
  • Use
  • Reuse

Includes case studies/examples: Yes, there are examples of citizen data reuse by NSOs in SDG reporting and sample tools used by NSOs, e.g., Uruguay, Germany, and the Philippines.

Notes: While aimed at NSOs dealing with citizen data quality control issues, CSOs may find it useful in understanding NSO perspectives.