Citizen contributions to data can help document the realities of those who are often less visible in statistics, close critical data gaps, and are becoming increasingly recognized as a legitimate data source for decision-making. 

Developed by the Collaborative on Citizen Data, the Copenhagen Framework on Citizen Data sets out principles and practical guidance to help countries and organizations use citizen data more effectively to strengthen official statistics and build more inclusive data systems. 

The framework is based around key principles for building data systems that are inclusive, participatory, and centered around the ‘Leave No One Behind’ commitment that underpins the UN’s Sustainable Development Goals (SDGs).

Key principles in the framework:

  • Participatory approaches and collaboration, engaging people across sectors to develop and validate data processes
  • The importance of peer learning, partnership, and sharing what works across different countries and organizations.
  • Inclusion and equity, ensuring underrepresented communities are visible in data and ensuring diversity in data sources.
  • Engaging citizens and facilitating people’s contributions through co-designing tools and approaches, and unearthing new data sources.
  • Ensuring data quality, ethics, and accuracy through disaggregation, robust processes, and governance. 

The Make Inclusive Data the Norm initiative (MIDN) itself embodies the principles of the framework, with its focus on knowledge exchange and shared learning on inclusive, people-powered data systems. The three peer exchange workshops, one in each of the three participating countries, formed the foundation of the initiative and offered an opportunity for exchanging knowledge, lessons, and practices on inclusive and citizen data. 

However, each of the three countries has implemented or adapted the Copenhagen Framework in its own way.

How Colombia has applied the Copenhagen Framework

  • Co-designing new digital tools and approaches to data collection with the communities that are affected by relevant issues and policy areas, including App Diversa, which allows citizens to report discrimination and other issues that are difficult to measure through traditional methods.
  • Colombia’s Citizen-Generated Data Framework and Citizen Data Maturity Model, both developed through MIDN, through participatory processes.
  • Building on DANE's (Colombia’s NSO) strong track record for data innovation to strengthen and solidify inclusive data systems and governance, in line with the principles in the Copenhagen Framework.
  • A focus on peer exchange, partnerships, and shared learning on inclusive data practices.
  • Ensuring under-represented communities are more visible in data.

Colombia’s own Citizen-Generated Data Framework, developed and solidified through MIDN, directly references recognized international standards including the Copenhagen Framework, and aligns with the key principles. 

The development of Colombia’s framework used participatory design approaches, including involvement and validation from civil society, academia, and the government, which in itself is encouraged through the framework. Meanwhile, Colombia’s framework also aims to integrate diverse contributions and perspectives from across the population into statistics and data, ensuring no one is missed out or left behind. 

Tools such as App Diversa, developed through MIDN, are being co-created and designed together with the community, including getting people involved in testing and contributing insights, to share feedback and highlight issues around discrimination, service quality, and access needs, to help ensure the voices of underrepresented communities are heard and everyone’s needs are illuminated. Again, this approach aligns with the Copenhagen Framework, which centers around widening participation in data processes, and encouraging citizen contributions. 

The app, co-created with citizens to capture information on issues that are difficult to measure through traditional methods, including discrimination, went through extensive validation sessions with representatives from LGBTIQ+, Afro-Colombian, indigenous, and youth communities, to co-design the questions and user experience.

Colombia already had a strong track record for data innovation, and engaging civil society through events, workshops, and participatory approaches. Through MIDN, the country has worked to strengthen and formalize its approach to citizen data, and create more inclusive processes. 

Through the course of the initiative, DANE has worked to solidify and institutionalize inclusive data practices, in line with the Copenhagen Framework. For example, DANE’s pre-existing Differential and Intersectional Approach Group focused on ensuring that everyone’s needs are represented in data, with a particular focus on ensuring inclusivity around gender, ethnicity, and disability, and using disaggregated data to better highlight inequality.

How Ghana has applied the Copenhagen Framework

  • Participatory approaches to data validation and highlighting data gaps, involving government, civil society organizations (CSOs), academia, and the media.
  • Pioneering inclusive and sensitive data collection and citizen-centered approaches on female genital mutilation (FGM) and other important issues.
  • Developing and piloting tools to enable citizen data to work alongside traditional data sources and close data gaps.
  • Peer learning and South-South cooperation on inclusive data through MIDN to exchange knowledge and strengthen data systems. 

Through MIDN, Ghana is focused on using inclusive data principles to produce better, more timely, and more accurate data on female genital mutilation (FGM) in the country, to help inform more effective policies and interventions. 

A key part of this work included organizing a landmark national validation workshop, which embodied the principles of co-creation and collaboration enshrined in the Copenhagen Framework. The workshop, run by Ghana Statistical Service (GSS) and the Ministry of Gender, Children and Social Protection, together with the Global Partnership, brought together government agencies, civil society, academia, and the media to validate the findings on the data gaps on FGM in the country, and inform next steps. 

Through MIDN, Ghana has also developed a number of innovative digital tools for inclusive data collection, including the prototype for a mobile app for securely sourcing data on FGM. The app is designed to enable safe, anonymous data collection from communities, to shine a light on the scale of FGM, particularly in hard-to-reach and underrepresented areas, and rural communities. This is aligned with the framework's principles around ethical citizen data that reflects people’s lived experiences, while protecting their anonymity. And again, the app design process has been inclusive and participatory, in line with the Copenhagen Framework’s ethos.

Prior to joining Make Inclusive Data the Norm, Ghana was already making strides in piloting and implementing citizen data in policy, through the creation of several citizen-focused mobile apps, including the Boame SGBV App, designed to collect information on sexual and gender-based violence anonymously, and CleanApp Ghana, for addressing waste management and reporting issues.

How Kenya has applied the Copenhagen Framework

  • Incorporating citizen data alongside official statistics and recognizing this as a legitimate data source through quality assurance frameworks.
  • Engaging partners across sectors through workshops and participatory approaches to co-design and validate the best approaches to collecting data from citizens.
  • Ensuring underrepresented groups and communities are visible in data.
  • Peer learning and knowledge exchange to share best practices and strengthen data systems.
  • Institutionalizing citizen data and pioneering quality assurance frameworks by integrating citizen data validation criteria into its national statistical quality framework (KeSQAF), creating an institutional model that balances strict standards with practical utility.
  • Creating a Technical Working Committee on citizen data and cross-sector partnerships to systemize citizen data collection, use it for decision-making, and bridge data gaps for the SDGs.

Kenya’s work through MIDN and beyond embodies several key principles of the Copenhagen Framework, including inviting representatives from across sectors to help validate and design the most effective inclusive data practices. 

During a three-day workshop in Nairobi, government agencies, civil society, and technical experts gathered to exchange knowledge and data skills, working together to explore and develop new inclusive data initiatives, including looking at how to use data visualization to tell better stories and deliver clearer insights to policymakers. 

Collaboration and peer exchange is at the heart of the Copenhagen Framework; during the workshop, participants went on a field trip together with disability rights organizations to collect community-generated data to understand the lived experiences of people with disabilities. 

At the final MIDN learning exchange event in August 2025, Kenya committed to institutionalizing inclusive data practices across sub-national systems through gender statistics guidelines and disability standards, to create a data system that is both inclusive and well-governed.

Its NSO, the Kenya National Bureau of Statistics (KNBS), has already taken steps to embed citizen data into the National Statistical System, in line with the Copenhagen Framework’s principle of introducing wider data sources. This has included the development of the Kenya Statistical Quality Assurance Framework (KeSQAF), a set of data quality standards, which includes criteria for assessing and validating citizen data for use in official reporting, including where there are gaps in the indicators for the UN's Sustainable Development Goals (SDGs).

Kenya has also established a Technical Working Committee on Citizen-Generated Data through KNBS, bringing together stakeholders from across government, civil society, and academia, to develop ways to improve and standardize citizen data collection and implement it into policymaking.