Open Forum #21 Leveraging Citizen Data for Inclusive Digital Governance

Summary

This Internet Governance Forum session focused on empowering marginalized communities through citizen-generated data to improve inclusive public services, featuring pioneering experiences from Ghana and Colombia. The discussion was moderated by Alexandra Wilde from UNDP’s Global Policy Center for Governance and included speakers from various UN agencies and national statistical offices.

Sarah Lister from UNDP opened by highlighting the UN Statistical Commission’s endorsement of the Copenhagen Framework on Citizen Data, emphasizing that traditional data systems alone are insufficient for building inclusive institutions. Charlotte Huntson from the UN Statistics Division explained that citizen data refers to information originating from initiatives where citizens are meaningfully engaged throughout the entire data value chain, not merely as data providers but as active participants in collection, analysis, and use.

Omar Seidu from Ghana Statistical Service presented Ghana’s comprehensive experience integrating citizen data into national statistics, beginning with SDG monitoring pilots in 2019. Ghana’s approach included developing mobile applications with multiple accessibility features, such as interactive voice response systems and local language support, ensuring participation from marginalized groups including persons with disabilities. Their citizen satisfaction survey on public services showed remarkable alignment with official census data, demonstrating the representativeness and reliability of citizen-generated information.

Aura Maria Moreno-Gamba from Colombia’s DANE shared their Data in Action Initiative, which focuses on creating a national citizen data framework through co-creation workshops with civil society organizations. Colombia developed a maturity model to help organizations assess their citizen data capabilities and created the “Abdiversa” pilot application to measure sensitive topics like discrimination.

The session concluded with discussions on ethical considerations, the importance of avoiding treating citizens as “free labor,” and the potential integration of citizen data with AI governance frameworks to enhance transparency and accountability in public services.

Keypoints

## Major Discussion Points:

– **Introduction and Framework of Citizen Data**: The session introduced the Copenhagen Framework on Citizen Data, endorsed by the UN Statistical Commission, which defines citizen data as information originating from initiatives where citizens are meaningfully engaged throughout the entire data value chain, not just as data providers but as active participants in collection, analysis, and use.

– **Ghana’s Pioneering Implementation**: Ghana Statistical Service presented their groundbreaking experience integrating citizen data into national statistics for SDG monitoring, particularly SDG indicator 16.6.2 (citizen satisfaction with public services). They demonstrated how mobile applications, interactive voice response systems, and multilingual accessibility enabled inclusive participation, including functionalities for persons with disabilities.

– **Colombia’s Data in Action Initiative**: Colombia’s DANE shared their comprehensive approach to building a national citizen data framework through co-creation workshops with civil society organizations, development of a maturity model for self-assessment, and creation of the “Abdiversa” pilot application to measure sensitive topics like discrimination and gender-based violence.

– **Challenges and Quality Considerations**: Multiple speakers addressed key challenges including ensuring data quality from non-state actors, building trust between national statistical offices and civil society organizations, addressing the digital divide, sustainability of citizen data initiatives over time, and the need for proper methodological frameworks.

– **AI Governance and Ethical Frameworks**: The discussion emphasized the importance of principled approaches to citizen data, including transparency, informed consent, avoiding treating citizens as “free labor,” and the intersection with AI governance to ensure citizen data is used ethically in AI models while mitigating bias and maintaining accountability.

## Overall Purpose:

The discussion aimed to showcase how internet-powered citizen data can transform public service delivery and governance by making it more inclusive and responsive to marginalized communities. The session focused on sharing practical experiences from Ghana and Colombia to demonstrate how citizen-generated data can be integrated with official statistics to improve SDG monitoring and public service assessment, while establishing frameworks and principles for ethical, sustainable implementation.

## Overall Tone:

The discussion maintained a consistently positive, collaborative, and forward-looking tone throughout. Speakers were enthusiastic about the potential of citizen data while being realistic about challenges. The tone was professional yet inspiring, with presenters sharing both successes and lessons learned. There was a strong emphasis on partnership, co-creation, and empowerment rather than top-down approaches. The session concluded on an encouraging note, emphasizing the groundbreaking nature of this work and its potential for global replication.

Speakers

**Speakers from the provided list:**

– **Alexandra Wilde** – Moderator, UNDP’s Global Policy Center for Governance

– **Sarah Lister** – Co-director for UNDP’s Governance, Rule of Law and Peace Building Hub

– **The United Nations Statistics Division** – Represented by Charlotte Huntson (though Charlotte’s name wasn’t in the original list), United Nations Statistics Division, representing the Collaborative on Citizen Data

– **Omar Seidu** – Head of social statistics at the Ghana Statistical Service

– **Departamento Administrativo Nacional de Estadística Colombia** – Represented by Aura Maria Moreno-Gamba (though Aura’s name wasn’t in the original list), National Administrative Department of Statistics in Colombia (DANE)

– **Dilek Fraisl** – Senior Research Scholar with the International Institute for Applied Systems Analysis (IIASA)

– **Maria Nordstrom** – Digital government division of the Ministry of Finance, Sweden, responsible for AI policy

**Additional speakers:**

– **Charlotte Huntson** – United Nations Statistics Division, representing the Collaborative on Citizen Data (participated online from Copenhagen)

– **Aura Maria Moreno-Gamba** – National Administrative Department of Statistics in Colombia (DANE), working on the Data in Action Initiative

# Empowering Marginalised Communities Through Citizen-Generated Data: A Comprehensive Report on Inclusive Public Services

## Executive Summary

This Internet Governance Forum session examined how citizen-generated data can transform public service delivery and governance by making it more inclusive and responsive to marginalised communities. The discussion, moderated by Alexandra Wilde from UNDP’s Global Policy Centre for Governance, brought together representatives from UN agencies, national statistical offices, and research institutions to share pioneering experiences from Ghana and Colombia. The session highlighted the endorsement of the Copenhagen Framework on Citizen Data by the UN Statistical Commission (though there appears to be uncertainty about the exact endorsement date referenced in the transcript) and demonstrated how internet-powered citizen data initiatives can bridge gaps in traditional data systems whilst empowering communities through meaningful participation in the entire data value chain.

## Introduction and Conceptual Framework

Sarah Lister from UNDP’s Governance, Rule of Law and Peace Building Hub opened the discussion by establishing the fundamental premise that traditional data systems alone are insufficient for building inclusive institutions. She provided context that “UNDP supports over 130 countries in building institutions that are inclusive, accountable and responsive” and emphasised that there is growing demand for people to contribute information about themselves in ways that reflect their interests and needs. Crucially, Lister highlighted that inclusion extends beyond merely collecting data from citizens: “But inclusion doesn’t stop at collecting or using that data. It also means returning that information to the people themselves, empowering communities through access, transparency and accountability.”

This foundational concept was further developed by Charlotte Huntson from the United Nations Statistics Division, representing the Collaborative on Citizen Data. Huntson explained that citizen data refers to information originating from initiatives where citizens are meaningfully engaged throughout the entire data value chain, not merely as data providers but as active participants in collection, analysis, and use. This definition represents a significant departure from traditional extractive data collection methods.

The discussion was anchored by the Copenhagen Framework on Citizen Data, which was endorsed by the UN Statistical Commission. This framework provides the conceptual foundation for understanding citizen data and outlines the roles for both citizens and national statistical offices in collaborative data initiatives. The framework’s endorsement represents a significant institutional validation of citizen data approaches within the global statistical community.

## Ghana’s Pioneering Implementation and International Recognition

Omar Seidu from Ghana Statistical Service presented Ghana’s comprehensive experience integrating citizen data into national statistics, which began with SDG monitoring pilots in 2019. Ghana’s approach has been notably systematic, developing multiple applications to address various governance and development challenges, with Ghana becoming “the first country to monitor the SDG indicator 1411B and submit the data to the Global Repository.”

This pioneering work has received significant international recognition, with Seidu noting that the work “received a lot of awards” including the “JUA award” he received in Rome, demonstrating the global acknowledgment of Ghana’s innovative approach.

The “Let’s Talk” application successfully measured four SDG indicators related to gender-based violence, demonstrating the potential for citizen data to address sensitive topics that are often difficult to capture through traditional surveys. Additionally, Ghana developed applications for waste management monitoring, marine data collection, and public service satisfaction assessment, showing the versatility of citizen data approaches across different sectors.

A particularly significant achievement was Ghana’s work on SDG indicator 16.6.2, which measures citizen satisfaction with public services. This indicator is based on actual experiences rather than abstract perceptions, making it well-suited to citizen data collection methods. The results showed remarkable alignment with official census data, with specific validation showing accurate representation in sex disaggregation and persons with disabilities representation, demonstrating the representativeness and reliability of citizen-generated information when properly implemented.

### Digital Inclusion and Accessibility Innovations

Ghana’s approach to digital inclusion proved especially noteworthy. The country developed mobile applications with multiple accessibility features, including interactive voice response (IVR) systems and local language support. Seidu revealed that “56% of the people engage with the IVR process where there’s an interactive voice testing messaging… without that feature for instance it means that more than half of the population wouldn’t have engaged with the process.” This finding provides concrete evidence of the digital divide’s impact and demonstrates how thoughtful inclusive design can dramatically expand participation.

The applications also included functionalities specifically designed for persons with disabilities, ensuring that marginalised groups could participate meaningfully in data collection processes. However, challenges remain, with “40% of the users had to get someone to file a report on their behalf,” highlighting ongoing accessibility needs.

### Concrete Policy Impact and Governance Changes

Ghana’s citizen data initiatives have produced tangible policy changes. After publishing passport satisfaction data, “the Ministry of Foreign Affairs issued a directive to get people who had applied for passports and had taken a long time to get this passport sent out to them” and “currently, we have a situation where the cost of obtaining passports are being reduced.” These examples demonstrate real governance impact beyond data collection.

The healthcare data showed measurable changes over time, with children’s medical treatment needs declining from “97% of children below 18 years had been in need of health medical treatment” in 2019 to “almost 90% of children” in 2024, illustrating the value of longitudinal citizen data monitoring.

### Technical Framework and Institutional Integration

Omar outlined 10 key processes common across all citizen data projects and emphasised the critical importance of “institutional buy-in within the institution” for National Statistics Offices to successfully adopt this approach. This institutional integration has been crucial to Ghana’s success in scaling citizen data initiatives across multiple sectors.

## Colombia’s Systematic Framework Development

Aura Maria Moreno-Gamba from Colombia’s National Administrative Department of Statistics (DANE) shared their Data in Action Initiative, which takes a more systematic approach to building a national citizen data framework. Colombia’s strategy focuses on creating comprehensive institutional foundations before scaling implementation.

The initiative includes extensive co-creation workshops with civil society organisations across different territories, recognising that Colombia’s diverse geography and social contexts require tailored approaches. Through these workshops, DANE has identified that 150 civil society organisations in Colombia work at different stages of the data value chain, with environment and gender being the most common topics of focus.

### Maturity Model for Capacity Development

Colombia developed a comprehensive maturity model designed to help civil society organisations “do a self-assessment in terms of identifying which step, in which process they are in terms of the construction of citizens’ data.” This tool enables DANE to provide appropriate support and tools based on each organisation’s current capabilities and development needs, creating a structured pathway for capacity building across the citizen data ecosystem.

### Pilot Implementation and Sensitive Topics

The “Abdiversa” pilot application represents Colombia’s approach to measuring sensitive topics like discrimination and gender-based violence. This application is designed to capture data on issues that are often underreported in traditional surveys, demonstrating how citizen data can illuminate hidden aspects of social experience. The application is scheduled for launch in October, with plans to expand to additional modules covering gender-based violence and public service access.

Colombia’s approach emphasises the importance of building trust and partnerships with civil society organisations before implementing large-scale data collection. This methodical approach reflects lessons learned about the importance of institutional relationships in successful citizen data initiatives.

## Challenges and Quality Considerations

Throughout the discussion, speakers acknowledged several key challenges that must be addressed for successful citizen data implementation. Charlotte Huntson from the UN Statistics Division identified three primary challenges: lack of trust between state institutions and non-state actors, concerns about data quality from non-state actors, and limited statistical capacity among citizen data collectors.

The trust issue is particularly significant because it requires National Statistics Offices to work with different types of non-state actors with whom they have not traditionally collaborated. This represents a fundamental shift in institutional relationships and requires new approaches to partnership building.

Data quality concerns reflect the statistical community’s need to maintain rigorous standards whilst embracing more participatory approaches. Traditional statistical offices have established methodologies for ensuring data quality, and integrating citizen-generated data requires developing new validation and quality assurance frameworks.

The sustainability challenge is crucial for official statistics, which require time series data to measure progress over time. Citizen data initiatives may not be consistently reproduced year after year, creating potential gaps in long-term monitoring efforts.

Dilek Fraisl from the International Institute for Applied Systems Analysis emphasised additional considerations around digital inclusion and ethical frameworks. She noted that “digital divide and inconsistencies in access to smartphones and technologies must be carefully addressed to ensure inclusion.” This challenge requires ongoing attention to ensure that citizen data initiatives do not inadvertently exclude the very populations they aim to serve.

## Ethical Frameworks and Avoiding Exploitation

The discussion placed significant emphasis on ethical considerations in citizen data implementation. Dilek Fraisl raised a critical concern about avoiding exploitative approaches: “We really need to avoid that or seeing citizens as free labour… but instead create value that is shared with participants.” This observation addresses fundamental questions about power dynamics and mutual benefit in data relationships.

The ethical framework extends beyond avoiding exploitation to actively empowering communities. Alexandra Wilde emphasised that citizen data “empowers communities by returning information to people themselves, enabling transparency and accountability rather than just collecting data from them.” This reciprocal approach transforms citizens from data subjects to co-creators of governance solutions.

The empowerment aspect is particularly important for marginalised communities, who have often been subjects of data extraction without receiving benefits from the insights generated. Citizen data approaches aim to reverse this dynamic by ensuring that communities have access to and control over data about their own experiences.

## AI Governance and Emerging Technologies Integration

Maria Nordstrom from the digital government division of the Ministry of Finance, Sweden, brought an important perspective on the intersection between citizen data and AI governance. She noted that “data is essential for AI systems, and citizen data can enhance AI actionability while requiring proper governance frameworks for transparency and accountability.”

However, Nordstrom also introduced important nuance about potential risks: “Citizen data can, of course, be used to mitigate biases when used in AI, but it can also have biases in itself. So you need to be aware of potential biases when the data is then processed by AI.” This observation highlights the need for careful governance frameworks that address both the potential and the pitfalls of integrating citizen data into AI systems.

Nordstrom outlined a comprehensive framework including seven key principles for AI governance, emphasising the importance of documentation, metadata management, risk-based approaches, and traceability in AI systems. The AI governance discussion emphasised the importance of participatory design, where citizens are involved in determining how their data is used in algorithmic systems, requiring clear principles on data ownership, consent, and usage rights when citizen data is incorporated into government AI systems and public services.

## Institutional Collaboration and Partnership Models

A consistent theme throughout the discussion was the critical importance of multi-stakeholder partnerships. Dilek Fraisl noted that the Ghana-UNDP collaboration “represents the first time a national statistical office and UN custodian agency collaborated to launch citizen data projects for monitoring governance indicators.” This pioneering partnership model demonstrates the institutional innovation required for successful citizen data implementation.

The collaboration involves not only National Statistics Offices and UN agencies but also civil society organisations, academic institutions, and community groups. These partnerships require new approaches to relationship building, capacity development, and shared governance of data initiatives.

Both Ghana and Colombia emphasised the importance of working closely with civil society organisations that have existing relationships with marginalised communities. These organisations often have the trust and local knowledge necessary for successful citizen data collection, whilst National Statistics Offices bring technical expertise and institutional legitimacy.

## Future Directions and Global Scaling

The Collaborative on Citizen Data is developing comprehensive guidance documents on data quality, citizen engagement, partnerships, and qualitative data handling, to be completed by mid-2026. These resources will provide practical frameworks for other countries seeking to implement citizen data initiatives.

Beyond Colombia, the Collaborative is supporting additional countries including Kyrgyzstan, Nepal, and Malawi in implementing citizen data initiatives. This expansion demonstrates growing international interest in citizen data approaches and the potential for global scaling.

The next annual expert group meeting is scheduled for October 2025, with a focus shifting from framework development to practical implementation. This evolution reflects the maturation of the citizen data field from conceptual development to operational deployment.

## Available Resources and Documentation

For those interested in learning more about these initiatives, Omar Seidu noted that detailed documentation of Ghana’s experience is available “in the Wiley Sustainable Development Journal.” Colombia’s Abdiversa application can be accessed through QR codes that Aura referenced during her presentation, providing concrete resources for practitioners and researchers interested in citizen data implementation.

## Session Limitations and Future Engagement

Due to time constraints, with Alexandra Wilde noting “There, unfortunately, isn’t much time, or any time, actually, for questions and discussion,” the session concluded without audience Q&A. This limitation highlights the need for continued dialogue and engagement opportunities as the citizen data field continues to evolve and expand globally.

## Conclusion

This Internet Governance Forum session demonstrated the significant potential of citizen-generated data to transform public service delivery and governance by making it more inclusive and responsive to marginalised communities. The pioneering experiences from Ghana and Colombia provide concrete evidence that citizen data can produce representative, reliable results whilst empowering communities and improving accountability.

The endorsement of the Copenhagen Framework on Citizen Data by the UN Statistical Commission represents a significant institutional validation of these approaches within the global statistical community. The framework provides a solid foundation for scaling citizen data initiatives whilst maintaining quality and ethical standards.

The discussion revealed strong consensus on fundamental principles whilst demonstrating the flexibility of citizen data approaches to accommodate different contexts and implementation strategies. The emphasis on meaningful participation, digital inclusion, ethical frameworks, and multi-stakeholder partnerships provides a robust foundation for continued development of this field.

Ghana’s international recognition and concrete policy impacts, combined with Colombia’s systematic framework development, offer complementary models for other countries seeking to implement citizen data initiatives. The integration of citizen data with emerging technologies like AI presents both opportunities and challenges that will require ongoing attention and governance innovation.

As citizen data initiatives continue to expand globally, the experiences and insights shared in this session provide valuable guidance for practitioners, policymakers, and researchers. The transformation from traditional extractive data collection to participatory citizen data represents a fundamental shift towards more democratic and accountable governance, with tangible evidence that this transformation can produce measurable improvements in public services and community empowerment.

Alexandra Wilde: Good morning everyone, distinguished guests, welcome to this session of the IGF entitled Empowering Marginalized Communities, Harnessing Internet-Powered Citizen Data for Inclusive Public Services. My name is Alexandra Wild, I’m with UNDP’s Global Policy Center for Governance and it is my pleasure to moderate this very exciting panel and session this morning. Today we will be really focusing on the pioneering experiences of Ghana and Colombia, exploring the potential of citizen-generated data in improving the engagement of citizens in the measurement and assessment of public service delivery. We have many colleagues here with us in the room and colleagues online who have also tuned in to this session. Some of those online include also some of the people speaking in the session today. First we will have some opening remarks by Sarah Lister, the co-director for UNDP’s Governance, Rule of Law and Peace Building Hub. We will hear today an introduction to citizen data and the contribution of the Collaborative on Citizen Data that will be shared with us by Charlotte Hunson of the United Nations Statistics Division, also a co-host of this session today. And we will hear, as I said earlier, the experience of Ghana from my colleague Omar Seidu, the head of social statistics at the Ghana Statistical Service. and also the experience of Colombia with citizen data from my colleague, Ora Gamba, who is with DANE, the Department of Statistics in Colombia. Then we will hear from two discussants that will sort of share their perspectives on some of the very exciting advancements we will hear today. The session is only an hour. We have a very hard cutoff time. So without further ado, I’m going to hand over to Sarah Lister to open the session. Over to you, Sarah.

Sarah Lister: Thank you very much. Good morning, good afternoon, good evening. Excellencies, distinguished colleagues, friends and partners, those in the room and those online, welcome to this session on empowering marginalized communities, harnessing internet-powered citizen data for inclusive public services. It’s a real pleasure to open this timely discussion on how digital tools and citizen engagement can transform how we understand and deliver public services, especially for those who are most often left behind. As many of you know, the United Nations Statistical Commission, the highest decision-making body in the global statistical system, took a landmark step earlier this year by endorsing the Copenhagen Framework on Citizen Data, which we will hear more about in this session. This marks a critical recognition that traditional data systems alone are not enough and that there is a demand for people to be able to contribute to generating information about themselves in a manner that reflects and serves their interests. To build truly inclusive institutions, we need data that reflects people’s lived experiences, especially those of marginalized and underserved groups. But inclusion doesn’t stop at collecting or using that data. It also means returning that information to the people themselves, empowering communities through access, transparency and accountability. This is why the expansion of citizen data as an approach is so important for UNDP. At UNDP we support over 130 countries in building institutions that are inclusive, accountable and responsive. Strengthening public service delivery, particularly for those furthest from power, is central to this mission. But governments can’t improve what they don’t understand. And they can’t understand without taking into consideration different viewpoints, including from the people they directly serve. That’s where citizen data, powered by the internet, can be a game-changer. By putting digital tools in the hands of people, we can help communities not only access services, but shape how those services are designed, delivered and evaluated. This helps answer the most fundamental governance questions. What do people need? Are services working? Who is being left behind? And why? Today we’re fortunate to hear from two countries at the forefront of this approach, Ghana and Colombia. Both have been exploring how citizen-generated data, enabled by internet access and digital innovation, can improve the inclusivity and responsiveness of public services. Their work offers practical lessons on how to connect official data systems with community-level realities, ensuring that services are not just available, but equitable and effective. This discussion is especially relevant in the context of the Internet Governance Forum, because the IDF is about ensuring that digital transformation serves people, rights and democracy. When people share data online to improve their communities, it shows that digital tools can strengthen the connection between people and their governments. Citizen data powered by the Internet helps build trust, promote accountability, and make public services more responsive. It allows for a form of digital participation that is grounded in everyday realities and promotes accountability from the bottom up. UNDP is the UN entity responsible for the global monitoring of SDG indicator 16.6.2, which measures people’s satisfaction with public services such as healthcare, education, and general government services. The indicator focuses not on abstract perceptions, but on actual experiences, access, quality, and affordability. By combining official data sources with citizen input, we can create a richer, more accurate picture of service effectiveness and drive more informed decisions. Ultimately, this is about bringing governance closer to people. It’s about ensuring that digital transformation doesn’t widen gaps, it closes them. It’s about showing that when communities are empowered to contribute their voices and experiences, they become co-creators of better public services and stronger institutions. Thank you very much for joining us and I really look forward to the rich insights from today’s presentation and discussion. Thank you very much. Alex, back to you.

Alexandra Wilde: Good. Thank you, Sarah. That’s a very helpful framing for the session. I just want to pick up on one particular issue, which is this fundamental idea that it’s not just about collecting data from people, but also returning that data back to communities. To empower them to be able to engage in governance. For that reason, it’s very much my pleasure to introduce Charlotte Huntson from the United Nations Statistics Division. who is representing the Collaborative on Citizen Data, who will take us through what is Citizen Data and how that whole very idea is so central to this understanding of Citizen Data, and also share with us sort of the work on the Collaborative and the Copenhagen Framework on Citizen Data. Now, Charlotte’s online and I’m hoping that we will have a smooth handover to Charlotte. Over to you.

The United Nations Statistics Division: Thank you so much and hello everyone from Copenhagen. So I will give you a very brief introduction to Citizen Data and the Copenhagen Framework on Citizen Data and how it’s being implemented by the Collaborative on Citizen Data. So next slide, please. Next slide. Can you hear me? Yeah. So first, what is Citizen Data? In the Copenhagen Framework, it has been defined and it basically refers to data originating from different initiatives of which citizens are engaged at various stages of the data value chain. And this is whether or not this data is integrated into official statistics or not. Is there a problem with the audio? It’s a bit unclear to me, sorry. I can hear you fine, Laura. I’m not sure about others here. Okay, that’s fine. We can all hear you, thanks. Okay. And the key aspects is really that there is sufficient and meaningful participation of citizens and that the citizens are engaged throughout the entire value chain or the data value chain. So next slide, please. So there are many different types of Citizen Data. For those of you who might not be so familiar with Citizen Data, I have here a few examples. It can be a civil society organization that gather data on marginalized population, usually the people that they represent. It can be communities, whether they are geographical communities or thematic communities that gather data on topics that’s relevant to them. Or another example is crowdsourced data, for example, from digital platforms that gather real-time information on various topics. It can be pollution monitoring, for example, waste on the beach, or a different type of public infrastructure that people are using, and that can give information to authorities of how well their services are working. Next slide, please. Sarah was already mentioning some of these different types of contributions that citizens can have to data and what that data does. Just something to highlight here is, of course, it’s a way to empower communities and improve their dialogue with public authorities. It’s also about having marginalized voices heard and having those voices respected, and then also expanding the production of power to citizens. Next slide, please. Since citizen data is a fairly new area, particularly in official statistics, there are different challenges with this data for the time being. A key thing is lack of trust or engagement between partners that have usually not worked together. These are state institutions, particularly the National Statistics Office, working with different types of non-state actors. We have concerns about the data quality collected by non-state actors, because this is something that often has been done by the National Statistics Office, and now we have a new type of data. This also links to the third bullet here, which is about the limited knowledge about data and maybe the lack of statistical capacity among these actors. So there’s a bit of concern around data quality as being a big area. There’s also issue with the sustainability of these different types of citizen data efforts, because we like to, at least in the official statistics world, we like to measure time series and see how things are developed over time. But can we be sure that if we use these data sources, they are reproduced year after year or over a certain period of time to make sure that we can measure progress. So these are some of the challenges. Next slide, please. And because of these challenges and the need to address them, but also to really give power of citizen to contribute to data, the Copenhagen framework has been established. It was endorsed in March 2025 by the US Statistical Commission. And it kind of, in its basic form, conceptualize and define citizen data. But it also kind of outlines the many different roles as citizens and national statistical offices can play in the different stages of data production. And it has also some quite specific active points on how to have a sustainable production and the use of citizen data. Next slide, please. So the collaborative is a network of a lot of organizations, communities, civil society organization, NSOs, human rights institutions, academia, different types of regional and international organizations. And it was established in 2023 and has been mandated by the US Statistical Commission to develop and finalize the Copenhagen framework on citizen data. And so that’s now in place and now it’s being implemented. But this network is also a space to share knowledge and foster collaboration and basically learn about citizen data because it’s such a new area. And the collaborative is also very much engaged, particularly at the moment, to develop different type of and guidances on how to handle the methodological gaps and some of all these challenges that I mentioned before. Next slide. So the actual work at the moment of the collaborative is, as I just said, really focused on developing this different type of knowledge projects to help facilitate the work and the more extensive use of citizen data. And we have a whole set of guidances that we expect to be completed by mid-2026, focusing on data quality, how do you handle data quality of citizen data, how do you engage citizens in a meaningful and participatory way, how do you form partnerships among these different type of actors in countries, how do you work with intersectionality and qualitative data. We see that citizen data have more qualitative data than, for example, national statistical offices are used to work with, so that’s also a new area, particularly for national statistical offices. We will also have a toolkit for how to develop national toolkits that kind of look at the national context, but take in experiences from around the world and some of these more generic recommendations on how to work with citizen data. We’re also supporting countries. We have worked with Colombia, Kyrgyzstan, Nepal and Malawi, but we have others to come that’s going to feed into the work of the next two years, both to support countries, but also to learn from the countries. And this will also provide input to the development of the guidance that we are working on. We have an annual expert group meeting. The next one takes place in October 2025. The previous ones have focused a lot on setting the stage and figuring out what citizen data is and developing the Copenhagen framework, but now we’re moving on to more sort of in the implementation mode. Next slide. So, yeah, everyone is welcome to join the collaborative. As organizations or contributions in any form, we have a website. You can find a lot of information there. It’s being updated at the moment. And if you can’t find what you’re looking for, you’re welcome to email us at citizen.data.un.org. Thank you very much.

Alexandra Wilde: Great. Excellent. Thank you, Charlotte. And for everyone, please do check out the information online. It’s a very inclusive collaborative. And as you’ve heard, you have access to a lot of the practice and the insights and the guidance that’s being developed within that very energized movement. Charlotte also highlighted some of the challenges in sort of integrating citizen data with official statistics. We’re going to hear a little bit about that now, but also some of the opportunities. So I’m going to ask my colleague, Omar Seidu, again, the head of social statistics at the Ghana Statistical Service, to share with us the experience of Ghana in integrating citizen data into national statistics. And to sort of elaborate on, yeah, some of those, some of those challenges and utilizing, you know, really timely, accurate, and reliable statistics to promote trust in government institutions and their decision-making. Over to you, Omar.

Omar Seidu: Thank you very much, Alexander. As already indicated, citizens’ data, data that are originating from initiatives which involve citizens’ engagement throughout the various stages of the data value chain. And these are guided by the principles of inclusiveness, responsiveness, professionalism. and the ethical production and use of the statistics. Now, in Ghana, our motivation had been in 2017, we did a data roadmap assessment to understand our capability of monitoring the SDGs, and it came out clearly that if we do not do something different from what we are used to, we might not be able to measure all the SDGs. And so, our motivation stems from the fact that we wanted to know how citizens’ data can provide timely, disaggregated, and actionable data for monitoring the SDGs, what technology-based tools are appropriate for representative data collection, and what pathways exist for addressing quality issues and building trust in this data. Now, we have had a long history of engagement with citizens’ data. In fact, we started in 2019, just before COVID, piloting the use of citizens’ data for monitoring five SDGs indicators, four on the gender-based violence, and so we deployed an application called Let’s Talk, where we tried to measure those four SDGs indicators. We developed another application the same year called Clean Up Ghana, which kind of engages citizens and waste management companies to try to measure another SDG indicator. While the first one was a success in measuring those indicators, the second one, Clean Up Ghana, was not successful in measuring the SDGs indicator, but it was successful in engaging and providing a tool for the local government to engage with the citizens and build trust in solid waste management. Then our third one was the Marine Data, which we did in 2021. In fact, Ghana was the first country to monitor the SDG indicator 1411B and submit the data to the Global Repository, and this piece of work has received a lot of awards, and last month, I was in Rome to receive the JUA award based on this work. Then in 2023, We tried another one, basically on leave no one behind. There is a policy in Ghana, it’s a law actually, to ensure that 3% of the local government resources are allocated to provide services to persons with disabilities. So we wanted to assess the effectiveness of that, and we used citizens data approach. And for the first time, because of the level of engagement, we were able to develop functionalities for persons with disabilities to engage with the applications. And based on that, then we work with the UNDP on the most recent one, which 2024, citizens satisfaction with public services, and that has been, that will be the focus of this discussion today. It’s been a very good project, because it shows how much citizens can contribute to providing feedback on services that they are expected to receive. Now, in all these citizens data projects, 10 key processes are common across all of them. And what is important to note here is that in all the processes, the citizens are engaged right from the planning stage, the data compilation stage, even the development of the application, and the data use. And I will mention a few instances where citizens have used this data to demand some service improvement in their areas. I will not attempt to go through all the processes, but it is important to note that coming from a national statistical office where we are used to well-established methodologies, you need to have institutional buy-in within the institution to get everybody to accept that this is a good way to invest time and resources in. And then you need to ensure that the key stakeholders are mapped and you identify the different interest groups and bring them on board. situational analysis to ensure that and that is very important the enablers and barriers of the use of this because if you’re in a country where a lot of people do not have mobile phones or even when they have mobile phones they do not have Android phones that have internet then you need to develop functionalities for them to be able to engage with the application and so these are very important features of this project. Importantly is your public education and sensitization effort because that is what will get as many citizens to know about this and engage in the process and that is an important tool to ensure that people who ordinarily wouldn’t be left behind in data collection in our service and all that are part of this process. Now let’s look at some interesting results. Now when we deployed this piece of work you can see that most people engage who do not have 56% of the people engage with the IVR process where there’s an interactive voice testing messaging and and and so without that feature for instance it means that more than half of the population wouldn’t have engaged with the process. Then with the application that is downloaded from Play Store or Apple Store we there is voice interaction within it and test options so for people who are literate a lot of them would prefer to use the test but for people who may not be literate they engage in their local languages through the application and so you see a 24% of them and we also provided functionalities for people to report on behalf of others with their consent and and that also showed that 40% of the users had to get someone to file a report on their behalf and the different local languages recording all this in the different local languages and also with the functionality for persons with disability also ensure that we have wide coverage in this. Now, when we’re done with this, after going through the data quality and doing all that, then we wanted to understand whether this really represent the situation on the ground. So here you can see on my left side, the pie charts shows that we compare the sex disaggregations of the two districts where we piloted this with the census, because Ghana had conducted a population and housing census in 2021. And so we compare the sex disaggregation from the census and the citizens’ data. And you can see that it’s almost the same for both districts. Then the bar charts on my right, the persons with disabilities in those two districts. The first one looking at what we have from the census, and the second one is looking at what the persons with disabilities who have engaged with the app. And you can see also that there are quite some good representation of the different population subgroups. Now, beyond the census, in 2019, Ghana had actually implemented a nationally representative sample survey on this same SDG 16.6.2, with the support of the UNDP. And you can see that at a time in 2019, 97% of children below 18 years had been in need of health medical treatment within the previous four weeks. And in 2024, using this same citizens’ data, on the same, we see that almost 90% of children have been in need of health. So which means that, yeah, there’s some level of representation in this data. Then the rightmost charts is showing the level of satisfaction the citizens have indicated with the healthcare delivery from the public health services. And we can see, of course, 2019, 2024, but you can see that for those of us who live in Ghana, this reflected the sentiments within the country, within the period. And you can clearly see some similarities there too. Then on education, and this is very important. In the 2019 national representative sample, we see that 55% of households had children 5 to 18 years in those households. In 2024, using the internet-based citizens data, you can still have 56% of households have children between 5 to 18 years, which means that there’s some level of representation and the rightmost chart is giving the public satisfaction with public education delivery in both the sample survey and the citizens data. Next, on the third one, which has to do with people needing a national ID system, and either to obtain it or to renew it, in 2019, we see that a third of the population had indicated that they had been in need of a national ID system. And in 2024, this has increased to 70%. And in fact, in a recent survey we have done in 2025, we realized that the fourth most important public entity that citizens in Ghana visit is embassies of other countries. And this really reflects the findings from this citizens data, that 70% had been in need of a national ID. And in the report, you see that whilst in 2019, the most important sought-after national ID was a Ghana card, in 2024, it was a Ghanaian passport. And people were frustrated also if you look at the satisfaction level in terms of the timeliness of the service and all that. And interestingly, when we published this, not long after that, the Ministry of Foreign Affairs issued a directive to get people who had applied for passports and had taken a long time to get this passport sent out to them. And also, currently, we have a situation where the cost of obtaining passports are being reduced. Now, it is important to know that for a successful rollout and how to overcome the common challenges is the inclusive… nature of developing the application with both the local people and the national stakeholders. And then establishment of a regular and consistent internal feedback mechanism. And understanding the key stakeholders’ interest for engagement. That is very important because once you engage, in fact, in developing this, there are 12 different domains of persons with disabilities in Ghana. And we make sure we engage with all these different domains. And that helps us to develop the functionalities for persons who are partially blind, for persons who have hearing impairment and all that, to engage with the application. And one other important thing is minimizing the user costs through optimization of the application. These have been some of the key challenges that we have, over the period, been able to mitigate to ensure that there is wide participation in this project. Yeah, so we have, because this is a learning process, we have documented even the processes that we started with from the beginning, not just the technical report. The processes also have been documented to provide information to other countries and other people who would want to replicate this. And of course, we also did another report comparing this survey data with the citizens’ data report. Thank you very much.

Alexandra Wilde: Thank you so much, Omar. And please, colleagues, do look into this documentation. It’s very rich, not only the findings, but also the processes of engaging citizens, the utilization of digital, including the app. And I might add to that too, there is further documentation in the Wiley Sustainable Development Journal. So there’s a lot of resources that are really capturing this important experience for SDG monitoring and particularly of. the indicator on satisfaction with public services. So without further ado, I’m going to invite Aura Maria Moreno-Gamba, who is with the National Administrative Department of Statistics in Colombia, DANE, to share with us also Colombia’s journey with citizen data, and in particular the Data in Action Initiative. Over to you, Aura.

Departamento Administrativo Nacional de Estadística Colombia: Thank you. Hi everyone. Today I’m going to show you how the experience has been working, or has DANE working on, especially with the citizens’ data. In this case, it’s important to show you that we are in the same line that the Copenhagen framework, in terms of identifying that citizens’ data is all the initiatives in which the citizens participate, but not only as a regular way in terms of collecting data or giving information or data to an institution, for example. In this way, it’s so important the participation of the citizens in the different stages of the data value chain. And we consider that this participation has to be sufficient and meaningful in all the processes or in all the stages. According to that, we have developed or have identified the importance to create a citizens’ data framework in Colombia. This is an initiative or is a document that we want to build, thanks to the support for the Global Partnership for Substantial Development Data and the United Nations Citizens’ Data Collaborative, and obviously taking into account the participation of civil society organizations, academia and all entities that belong to the national statistical system. In this way, or in order to develop the initiative, we have established different stages or different actions in terms of developing the framework. One of them is to create different workshops in which we can interact with different civil society organisations and citizens as well, in order to identify which aspects they consider so relevant in terms of considering the build of this framework. We have been working in different workshops, we are going to see later, and it’s a strategy in which we identify if we are going to create a document for the citizens, obviously we need to establish the collaboration or, how we call, co-creation with the citizens. On the other hand, we have been considering including the maturity model in the framework, because we consider that it’s important to establish different dimensions, level, criterias of evaluation, in order to let the civil society organisation and the citizens in general be able to do a self-assessment in terms of identifying which step, in which process they are in terms of the construction of citizens’ data. And in that way, we can, as an institution, give all the support, all the help that the institutions need, in terms of which tools they can apply, which standards they can apply in the generation of citizens’ data. And we have developed a form in which, or the idea of this form is to identify how many civil social organisations are in Colombia, and how many of those interact with citizens and produce citizens’ data. And one of the strategies that we have been working on as well is the creation of a pilot application, it’s called Abdiversa. And the idea is to be or have the possibility to measure some sensitive topics as discrimination, for example, in order to let or have the possibility to identify how or these topics, how it works and have the possibility as well to measure some SDGs indicators. So the initiative of the data in action followed a different normativity, for example, in Colombia we have the statistical law in which this document or this law established the importance of the inclusion of different characteristics of the population and the idea is that all of those characteristics are included, are visible, so that’s why we work in the same line for the law. And we have in Colombia the national statistical plan in which the goal 35 specifically they mentioned the importance to create a document that is our citizens data framework in order to give some recommendations, good practices, some advice in terms of how interact with the citizens, civil social organization in the processing, validating and use of statistical data. And obviously the importance of a statistical culture that is so important to identify that citizens acts not only as a person that gives information continuously to institution, in this case it’s important to identify the citizens or their important role in the ecosystem data. And obviously if we interact with or we create citizens data we can identify the possibility that citizens has in terms of being part of the government agenda or show the different situations that… civil society can face. In terms of the workshops, the idea to create these workshops is that we can identify or establish a different way in which we can co-create with the civil social organisation. We have been working together in terms of identifying what dimensions, what criteria they use in terms of producing citizens’ data and obviously we try to not focus in the capital city, Bogotá. We try to develop these workshops in different areas in order to identify the different situations that people face in the territory and not only in the capital, so that’s important. We have been creating workshops in Cali, in Medellín and other places that is so useful for us to identify the topics and the things that we have been identifying in terms of the quality of these workshops is that we can establish a necessary in which we create a network in which different civil social organisations can identify in which topics they can work together or support each other, so it’s so helpful and obviously we have been the main actors in our workshops, we have the participations of civil social organisations, the academia that has identified the potential that citizens’ data has in terms to identify different or sensitive topics. That’s why we consider a maturity model because we identify the importance in which the self-assessment can help to the civil social organisations in terms to identify in which states they are in terms of the production of citizens’ data. And as I mentioned before, the idea is that as an institution that can provide different tools, guidelines in terms of how they can improve the level or the statement in the different aspects of the production of citizens’ data. So in that case, the idea is work together or co-create as well this maturity model. We have developed a workshop directly to identify how civil social organisations identify what dimensions are so important, what criteria of evaluation are so important in terms of this maturity model, and determine specific aspects they can use, and in that case, interact with different areas or different areas in that in terms of which methods, which tools they can use. As I mentioned before, we developed a form in order to identify how many civil social organisations are in Colombia, and we identified that 150 civil social organisations work in the different stages of the data value change, and we identified the most common stages in which citizens participate in the data collection and the analysis and dissemination of the data. From these 150, we identified that 95 civil social organisations work directly with citizens, and the main topic is the environment topic, it’s one of the most relevant or common topics that the civil social organisations work with. and the gender topic as well. So we can identify in which aspects they work, and obviously, the idea is to increase the amount of civil social organization that we will able to identify and work with in the same or in the other scenarios as the workshops and other spaces that we create. Finally, in terms of the app, the app diversity that is a new strategy that we have been working on in terms of identify this sensitive topic. We have developed a pilot application with the support of the global partnership and the Appesee Colombia. The idea, as I mentioned before, is to identify or measure these sensible topics as discrimination. Now, we have discrimination as the main topic and we have developed this module and the idea is to keep working in other modules as the gender-based violence and the access for the public services in order to have or identify some data related with these topics. Obviously, let us measure the SDGs, for example, in terms of discrimination, the 16B1. Here, we identify that this app can help us in a multi-collaborative scenario because in the test that we have been doing with the citizens, we collaborate or we co-create as well in terms to identify the aspects, the questions, if are correct, if they are clear in order to develop the app, and we identify the importance that the app helps not only interact in one way, the idea is to interact in different ways, not in a regular obtained or. capture data for the citizens. In this case, the citizens have the opportunity to interact constantly with us in terms of the building of this app, and the importance that this app can have in terms of go to the territory, because in a regular way, it’s a census or surveys is so difficult to go directly with those territories that could be difficult to access in a normal way or in a normal survey. In this case, we consider that this app could help in terms of identify aspects relevant that maybe is not so usual to ask in a normal way. Here, you can ask or you can access to the QR code in which we develop, or the app is in production. The idea is to be launched in October, so we are keep working on it. The idea is that if you want to search a little bit, the discrimination module, you can access. Obviously, the structure is in Spanish, but if you like to take a look, go ahead. Thank you.

Alexandra Wilde: Great. Thank you so much, Aura. We’re running very short of time, and I’ve been transitioning very quickly, but I’d like us to take a moment now to give a round of applause both to Omar and to Aura, for this really excellent sharing of very frontier and really inspiring experience. So please do follow up with them both during the IGF and look at the resources made available online. I’m going to turn now to one of the co-organisers of this session, and a really important partner in the broader work on citizen data and integration with official statistics. And that is to invite Dilek Fraisl, who is joining us online. She’s the Senior Research Scholar with the International Institute for Applied Systems Analysis, IIASA. She’s just going to kick off a little bit of the discussion and hoping we have a couple of minutes for questions and for those here to share their views. But she’s gonna just sort of highlight a couple of points coming from this experience to kind of share with us and allow us to sort of further reflect on. So over to you, Dilek.

Dilek Fraisl: Thank you so much, Alexandra, and thank you everyone for attending this important event. I’m really sad that I couldn’t be there with you today, but I would like to talk about a few points that is related to this project and in general to citizen data projects related to citizen data projects. So I really find the conversation we’re having today is extremely important and very timely, as we could see also the UNSD and Partners Let’s Citizen Data Collaborative is also understanding and supporting the importance and timeliness of this work. And as a person who is heavily involved in citizen data, both as a scientist looking at the topic from a theoretical perspective, but also as a practitioner using citizen data approaches for scientific research and production of knowledge, I’m very excited to be here and to be part of this important conversation and session. And I would like to mention a few points regarding the project that was presented by Omar and led by the UNDP Global Policy Center for Governance and the Ghana Statistical Service so greatly. And I’ve been privileged to be closely involved in this groundbreaking project since the start. And I’m saying groundbreaking because the project was innovative in many fronts, but I’ll mention one. This is the first time a national statistical office together with the UN agency, a custodian agency for a particular SDG indicator came together to launch a citizen data project and to monitor a governance indicator. And there has been conversations in the past a lot about integrating already existing data gathered through the citizen data initiatives to SDG monitoring. and reporting processes towards address large data gaps in the SDGs, but this particular initiative actually paves the way for a more active leading role of national statistical offices in a groundbreaking way and to help maybe to create a path forward for all the NSOs worldwide to see the benefits, to show the benefits of citizen data approaches and adapt it to their own context. And as mentioned, there are very detailed documentations of works through the reports that are published by the Ghana Statistical Service and the scientific paper mentioned by Alexandra. All the information is really out there and it talks about all the details, including limitations, including opportunities. And I think there are great resources. What I would like to say a few things about the citizen data initiatives in general, and this came up a lot in this conversation today. We really need to, especially as NSOs, because this approach is really new to NSOs and data monitoring and gathering for global frameworks, it’s really important to carefully consider strategies and citizen data initiatives that ensure data collection is really participatory and inclusive. And particularly in terms of engaging underrepresented and hard to reach communities, as mentioned in the Ghana work, there has been a lot of measures taken to be able to reach out to these communities. And for instance, using sign languages and translating the application to several different languages. And the goal really should be to avoid that or seeing citizens as free labor. This has been tackled and discussed a lot in the citizen data community where I come from, academic community, but instead create value that is shared with participants. And also what I hear from Ghana and also Columbia experience. People who are really at the forefront of these initiatives are very well aware of this, and this is very promising. And speaking of inclusion, we need to be really careful of potential digital divide and inconsistencies with regards to access to smartphones and technologies. And that’s why it was really important in the Ghana project that it wasn’t only smartphones that were used, but also voice recording was included and many other aspects. So people didn’t have to have smartphones to participate. And trusting data-driven initiatives depends on strong ethical foundations that prioritize transparency, inform consent from participants and really fairness. And there are a lot of important frameworks and principles to guide citizen data initiatives. And it looks like the National Statistical Offices and the UNDP as well as UNSC are very well aware of that. There is, for instance, from the academic community where I come from, we have the ten principles of citizen science. But Copenhagen Framework is building actually on these existing principles and has its own 13 principles for citizen data in the Copenhagen Framework. And there are other principles as well, like human rights-based approach to data or peer and care data, which highlights the findability, accessibility, interoperability and reusability of data. But also care principles about collective benefit, authority to control, responsibility and ethics in data initiatives and citizen data initiatives. So I will just close or finish by saying empowering communities to take part, not just in data collection, but also in decision-making processes is really important. And it helps ensure governance structures are accountable and aligned with public needs. And this has been the motivation of the UNDP colleagues as well as the National Statistical Office of Ghana to really implement this project. And this approach through citizen data also supports the Leave No One Behind principle of the SDG agenda that is subject to this conversation today. and help strengthen democratic data governance. Thank you all so much. And I’m happy to stay around if there’s any questions. Thank you.

Alexandra Wilde: Thanks so much, Dilek. And also for the important reminder of a principled approach and particularly inclusion, this real shift from looking at citizens as free labor and data production to being really driven by inclusion and to be very conscious of the digital divide. We have just one last, last but not least, an important panelist who is Maria Nordstrom, who is within the digital government division of the Ministry of Finance, Sweden, responsible for AI policy, who will give a little take on what you’ve heard, whether you’re new or not to the citizen data community. I think you’ll bring a very interesting perspective. So you just have a couple of minutes to share that with us. Thank you, Maria.

Maria Nordstrom: Thank you so much. And thank you for having me. This is such an interesting and inspiring session. So I work mostly on AI. And as you all know, data is essential for AI. Similarly, AI can be used to enhance the actionability of citizen data. But we need AI governance. We need policies and practices to ensure that AI systems are transparent and accountable. And that starts with the data. In Sweden, we have developed national principles for making information available. And those principles are developed by our agency for digital government. And the principles provide a framework for organizations to publish and share data in ways that promote transparency, innovation, and societal values. So originally, these principles were developed for public organizations, but I think they are very relevant in the context of citizen data as well. And they relate to a lot of that has been said here today. There are seven principles in total. And one of the principles. is on the documentation and metadata of the data that’s being collected. So this is important to ensure transparency. This is on how the data is collected by whom and in what conditions, similarly to what is done in Ghana. I think it shows that this is really important because in turn, AI governance can then encourage the transparency of how citizen data is used in AI models. Another principle is related to a risk-based approach. So even if the data isn’t personal data, it must be assessed for risks. So a data set could reveal vulnerabilities or be misused. There are government frameworks that can help assess and mitigate risks related to bias to misuse or unintended consequences when the data is then processed by AI. So citizen data can, of course, be used to mitigate biases when used in AI, but it can also have biases in itself. So you need to be aware of potential biases when the data is then processed by AI. Traceability in this context is very important. Finally, AI governance promotes participatory design. So when citizens are involved in how their data is used, and we’ve heard this before. So today, I think citizen data and the process of collecting citizen data provides a basis for dialogue and it’s crucial in establishing trust. Authorities can engage with citizen data and validate, enrich, and integrate the data into public services as we’ve been told today. But this requires principles, clarity on ownership and consent. So data must be shared under open terms and under clear agreements to ensure respect for the original contributors, not to undermine trust. So I think it was mentioned that citizen data and the process of collecting citizen data can contribute to building trust in data. Similarly, I think citizen data can be utilized to building trust in AI, with the help of proper AI governance. Thank you so much for having me.

Alexandra Wilde: That’s great. Thank you so much, Maria, and really important points raised around the governance of AI, and the integration of citizen data into models, and these issues around bias, and how to utilize citizen data to mitigate that, but also to be very aware of it. So thankfully, we’ve kept time. There, unfortunately, isn’t much time, or any time, actually, for questions and discussion. But again, please follow up with any of us, with UNDP, with OMA, with AURA, and we’ll be very happy to share more information on these experiences. And with that, thank you, OMA and AURA. Thank you for being part of this session. Also to you, Maria, and to Dilek and Charlotte online, and to Sarah, of course, who is over here to be able to look at the PowerPoint. Thank you to all colleagues joining online, and for those that have come here this morning for this session. Have a wonderful rest of day. Thank you.

Agreement points

Citizen data requires meaningful participation throughout the entire data value chain

Speakers

– The United Nations Statistics Division
– Departamento Administrativo Nacional de Estadística Colombia
– Alexandra Wilde

Arguments

Citizen data refers to data originating from initiatives where citizens are engaged at various stages of the data value chain with sufficient and meaningful participation

Colombia is developing a national citizen data framework with support from civil society organizations, academia, and the national statistical system

Citizen data empowers communities by returning information to people themselves, enabling transparency and accountability rather than just collecting data from them

Summary

All speakers agree that citizen data is fundamentally about meaningful citizen participation throughout the entire data process, not just data collection, emphasizing co-creation and empowerment rather than extraction

Topics

Data governance | Human rights principles

Digital inclusion and accessibility are critical for successful citizen data initiatives

Speakers

– Omar Seidu
– Dilek Fraisl
– Departamento Administrativo Nacional de Estadística Colombia

Arguments

Ghana’s citizen data showed strong representation compared to census data, with 56% of users engaging through voice interaction due to literacy considerations

Digital divide and inconsistencies in access to smartphones and technologies must be carefully addressed to ensure inclusion

The initiative includes workshops across different territories, a maturity model for self-assessment, and the ‘Abdiversa’ pilot application focusing on discrimination measurement

Summary

Speakers consistently emphasize the need to address digital divides through multiple access methods, local language support, and territorial approaches to ensure no one is left behind

Topics

Digital access | Rights of persons with disabilities | Development

Institutional collaboration between NSOs, UN agencies, and civil society is essential

Speakers

– Omar Seidu
– Departamento Administrativo Nacional de Estadística Colombia
– Dilek Fraisl

Arguments

Ghana has implemented citizen data projects since 2019, including applications for monitoring SDG indicators on gender-based violence, waste management, marine data, and public service satisfaction

Colombia is developing a national citizen data framework with support from civil society organizations, academia, and the national statistical system

This represents the first time a national statistical office and UN custodian agency collaborated to launch citizen data projects for monitoring governance indicators

Summary

All speakers highlight the importance of multi-stakeholder partnerships involving NSOs, UN agencies, civil society, and academia for successful citizen data implementation

Topics

Data governance | Capacity development

Similar viewpoints

These speakers share a strong emphasis on citizen empowerment and moving beyond traditional extractive data collection methods toward participatory approaches that benefit communities

Speakers

– Sarah Lister
– Alexandra Wilde
– Dilek Fraisl

Arguments

Traditional data systems alone are insufficient and there is demand for people to contribute information about themselves in ways that reflect their interests

Citizen data empowers communities by returning information to people themselves, enabling transparency and accountability rather than just collecting data from them

Citizens should be viewed as co-creators rather than free labor, with value shared among participants throughout the data collection process

Topics

Data governance | Human rights principles

These speakers acknowledge the practical challenges of implementing citizen data while demonstrating concrete examples of successful implementation and existing capacity

Speakers

– The United Nations Statistics Division
– Omar Seidu
– Departamento Administrativo Nacional de Estadística Colombia

Arguments

Key challenges include lack of trust between state institutions and non-state actors, concerns about data quality from non-state actors, and limited statistical capacity among citizen data collectors

The ‘Let’s Talk’ application successfully measured four SDG indicators on gender-based violence, while other projects provided tools for local government engagement

150 civil society organizations in Colombia work in different stages of the data value chain, with environment and gender being the most common topics

Topics

Data governance | Development | Capacity development

Both speakers emphasize the importance of ethical frameworks and participatory approaches that respect citizen rights and ensure fair value distribution

Speakers

– Dilek Fraisl
– Maria Nordstrom

Arguments

Citizens should be viewed as co-creators rather than free labor, with value shared among participants throughout the data collection process

AI governance promotes participatory design where citizens are involved in how their data is used, requiring clear principles on ownership and consent

Topics

Data governance | Human rights principles | Privacy and data protection

Unexpected consensus

Integration of citizen data with official statistics and AI systems

Speakers

– Omar Seidu
– Maria Nordstrom
– Dilek Fraisl

Arguments

Ghana’s citizen data showed strong representation compared to census data, with 56% of users engaging through voice interaction due to literacy considerations

Data is essential for AI systems, and citizen data can enhance AI actionability while requiring proper governance frameworks for transparency and accountability

This represents the first time a national statistical office and UN custodian agency collaborated to launch citizen data projects for monitoring governance indicators

Explanation

There is unexpected consensus on the technical feasibility and institutional readiness for integrating citizen data with both traditional statistical systems and emerging AI applications, despite the novelty of these approaches

Topics

Data governance | Legal and regulatory | Development

Quality and representativeness of citizen data can match traditional methods

Speakers

– Omar Seidu
– The United Nations Statistics Division
– Dilek Fraisl

Arguments

Ghana’s citizen data showed strong representation compared to census data, with 56% of users engaging through voice interaction due to literacy considerations

Key challenges include lack of trust between state institutions and non-state actors, concerns about data quality from non-state actors, and limited statistical capacity among citizen data collectors

This represents the first time a national statistical office and UN custodian agency collaborated to launch citizen data projects for monitoring governance indicators

Explanation

Despite acknowledging quality concerns, there is consensus that citizen data can achieve representativeness comparable to traditional methods when properly implemented, which is significant given initial skepticism from statistical institutions

Topics

Data governance | Development

Overall assessment

Summary

There is strong consensus among speakers on the fundamental principles of citizen data (meaningful participation, empowerment, inclusion), the importance of multi-stakeholder collaboration, and the need for ethical frameworks. Speakers also agree on practical implementation strategies including digital inclusion measures and institutional partnerships.

Consensus level

High level of consensus with significant implications for legitimizing citizen data as a viable approach for official statistics and governance. The agreement spans theoretical foundations, practical implementation, and future integration with emerging technologies like AI, suggesting strong momentum for scaling these approaches globally.

Different viewpoints

Unexpected differences

Overall assessment

Summary

The discussion showed remarkable consensus among all speakers on the fundamental value and importance of citizen data initiatives. No significant disagreements were identified in the transcript.

Disagreement level

Very low disagreement level. The session was characterized by collaborative sharing of experiences and mutual reinforcement of key principles. All speakers supported the same core objectives of empowering communities, improving data quality, and enhancing governance through citizen participation. The only variations were in implementation approaches and emphasis on different aspects of citizen data work, which reflects complementary rather than conflicting perspectives. This high level of agreement suggests strong momentum and shared vision in the citizen data community, which bodes well for continued collaboration and development of this field.

Partial agreements

Similar viewpoints

These speakers share a strong emphasis on citizen empowerment and moving beyond traditional extractive data collection methods toward participatory approaches that benefit communities

Speakers

– Sarah Lister
– Alexandra Wilde
– Dilek Fraisl

Arguments

Traditional data systems alone are insufficient and there is demand for people to contribute information about themselves in ways that reflect their interests

Citizen data empowers communities by returning information to people themselves, enabling transparency and accountability rather than just collecting data from them

Citizens should be viewed as co-creators rather than free labor, with value shared among participants throughout the data collection process

Topics

Data governance | Human rights principles

These speakers acknowledge the practical challenges of implementing citizen data while demonstrating concrete examples of successful implementation and existing capacity

Speakers

– The United Nations Statistics Division
– Omar Seidu
– Departamento Administrativo Nacional de Estadística Colombia

Arguments

Key challenges include lack of trust between state institutions and non-state actors, concerns about data quality from non-state actors, and limited statistical capacity among citizen data collectors

The ‘Let’s Talk’ application successfully measured four SDG indicators on gender-based violence, while other projects provided tools for local government engagement

150 civil society organizations in Colombia work in different stages of the data value chain, with environment and gender being the most common topics

Topics

Data governance | Development | Capacity development

Both speakers emphasize the importance of ethical frameworks and participatory approaches that respect citizen rights and ensure fair value distribution

Speakers

– Dilek Fraisl
– Maria Nordstrom

Arguments

Citizens should be viewed as co-creators rather than free labor, with value shared among participants throughout the data collection process

AI governance promotes participatory design where citizens are involved in how their data is used, requiring clear principles on ownership and consent

Topics

Data governance | Human rights principles | Privacy and data protection

Key takeaways

Citizen data represents a paradigm shift from traditional data collection, engaging citizens meaningfully throughout the entire data value chain rather than treating them as passive data sources

The Copenhagen Framework on Citizen Data, endorsed by the UN Statistical Commission in March 2025, provides the foundational structure for integrating citizen-generated data with official statistics

Both Ghana and Colombia have successfully demonstrated that citizen data can produce representative results comparable to traditional census and survey data while reaching marginalized communities more effectively

Digital inclusion strategies are essential – Ghana’s success with 56% of users engaging through voice interaction highlights the importance of accommodating different literacy levels and technology access

Citizen data initiatives can drive real policy changes, as evidenced by Ghana’s passport processing improvements following citizen feedback and Colombia’s focus on sensitive topics like discrimination

The approach transforms citizens from data subjects to co-creators of governance solutions, enabling bottom-up accountability and more responsive public services

Integration of citizen data with AI systems requires careful governance frameworks to address bias, ensure transparency, and maintain citizen trust through participatory design

Resolutions and action items

The Collaborative on Citizen Data will develop comprehensive guidance documents on data quality, citizen engagement, partnerships, and qualitative data handling to be completed by mid-2026

Colombia will launch the ‘Abdiversa’ application in October to measure discrimination and other sensitive topics, with plans to expand to gender-based violence and public service access modules

The Collaborative will hold its next annual expert group meeting in October 2025, focusing on implementation rather than framework development

Ghana Statistical Service and UNDP will continue documenting their processes and methodologies to provide replication guidance for other countries

The Collaborative will continue supporting additional countries beyond Colombia, Kyrgyzstan, Nepal, and Malawi in implementing citizen data initiatives

Unresolved issues

Long-term sustainability of citizen data initiatives remains a challenge, particularly ensuring consistent data collection over time for meaningful trend analysis

Data quality concerns persist regarding citizen-generated data compared to traditional statistical office methodologies, requiring ongoing validation approaches

Trust-building between national statistical offices and non-state actors continues to need attention as these partnerships are relatively new

Digital divide issues require ongoing solutions to ensure truly inclusive participation across all population segments

Standardization of methodologies across different countries and contexts while maintaining local relevance remains an open challenge

Ethical frameworks for citizen data use in AI systems need further development to prevent misuse and maintain citizen trust

Suggested compromises

Hybrid approaches combining traditional statistical methods with citizen data to address quality concerns while maintaining inclusivity

Multi-modal data collection strategies (voice, text, app-based, IVR) to accommodate different technology access levels and user preferences

Gradual integration of citizen data into official statistics through pilot projects and validation studies before full-scale implementation

Co-creation approaches involving citizens in application development and methodology design to balance statistical rigor with community needs

Risk-based assessment frameworks for citizen data use in AI systems that balance innovation potential with bias mitigation requirements

But inclusion doesn’t stop at collecting or using that data. It also means returning that information to the people themselves, empowering communities through access, transparency and accountability.

Speaker

Sarah Lister

Reason

This comment reframes citizen data from a traditional extractive model to a reciprocal empowerment model. It challenges the conventional approach where data flows one-way from citizens to institutions, introducing the critical concept that data should flow back to communities to enable their participation in governance.

Impact

This comment established the foundational framework for the entire discussion, shifting focus from technical data collection methods to the transformative potential of citizen data for democratic participation. Alexandra Wilde immediately picked up on this theme, emphasizing it as ‘fundamental’ and ‘central’ to citizen data understanding.

A key thing is lack of trust or engagement between partners that have usually not worked together. These are state institutions, particularly the National Statistics Office, working with different types of non-state actors.

Speaker

Charlotte Hunson (UN Statistics Division)

Reason

This comment identifies a fundamental institutional challenge that goes beyond technical issues to address the human and organizational dynamics that can make or break citizen data initiatives. It acknowledges that successful citizen data requires bridging traditional institutional silos.

Impact

This observation set up the practical country experiences that followed, with both Ghana and Colombia demonstrating how they addressed these trust and partnership challenges through inclusive design processes and stakeholder engagement strategies.

56% of the people engage with the IVR process where there’s an interactive voice testing messaging… without that feature for instance it means that more than half of the population wouldn’t have engaged with the process.

Speaker

Omar Seidu

Reason

This finding provides concrete evidence of the digital divide’s impact and demonstrates how thoughtful inclusive design can dramatically expand participation. It challenges assumptions about digital-first approaches and shows the critical importance of multi-modal access.

Impact

This data point became a powerful validation of the inclusion principles discussed earlier, providing empirical evidence for why inclusive design isn’t just ethically important but practically essential for representative data collection.

We really need to avoid that or seeing citizens as free labor… but instead create value that is shared with participants.

Speaker

Dilek Fraisl

Reason

This comment addresses a critical ethical concern in citizen data initiatives, challenging exploitative approaches and advocating for genuine partnership models. It introduces important considerations about power dynamics and mutual benefit in data relationships.

Impact

This observation elevated the discussion from technical implementation to ethical foundations, reinforcing the principled approach needed for sustainable citizen data initiatives and connecting to broader conversations about data justice and community empowerment.

Citizen data can, of course, be used to mitigate biases when used in AI, but it can also have biases in itself. So you need to be aware of potential biases when the data is then processed by AI.

Speaker

Maria Nordstrom

Reason

This comment introduces important nuance about the relationship between citizen data and AI systems, acknowledging both the potential and the pitfalls. It challenges any assumption that citizen data is inherently unbiased and highlights the need for careful governance frameworks.

Impact

This comment expanded the discussion beyond traditional statistics to emerging AI applications, introducing new considerations about how citizen data might be used in algorithmic systems and the governance frameworks needed to ensure responsible use.

Overall assessment

These key comments collectively transformed the discussion from a technical presentation about data collection methods into a comprehensive exploration of democratic data governance. The progression moved from establishing philosophical foundations (data as empowerment tool), through practical implementation challenges (institutional trust, digital inclusion), to ethical considerations (avoiding exploitation) and future applications (AI governance). Each comment built upon previous insights, creating a layered understanding that citizen data success requires not just technical innovation but fundamental shifts in how institutions relate to communities, how inclusion is operationalized, and how emerging technologies are governed. The comments demonstrated that citizen data represents a paradigm shift toward more participatory, accountable, and equitable approaches to both governance and knowledge production.

How can we ensure that digital transformation doesn’t widen gaps but closes them in marginalized communities?

Speaker

Sarah Lister

Explanation

This addresses a fundamental concern about whether digital citizen data initiatives might inadvertently exclude those they aim to help, requiring strategies to bridge rather than expand digital divides.

How do you handle data quality of citizen data when it comes from non-state actors?

Speaker

Charlotte Huntson (UNSD)

Explanation

This is identified as a key challenge since National Statistics Offices are concerned about maintaining data quality standards when working with citizen-generated data that may not follow traditional statistical methodologies.

How do you ensure sustainability of citizen data efforts over time for measuring progress?

Speaker

Charlotte Huntson (UNSD)

Explanation

Official statistics require time series data to measure progress, but citizen data initiatives may not be consistently reproduced year after year, creating challenges for long-term monitoring.

How do you work with intersectionality and qualitative data in citizen data initiatives?

Speaker

Charlotte Huntson (UNSD)

Explanation

Citizen data often contains more qualitative information than National Statistics Offices typically handle, requiring new approaches to process and integrate this type of data.

What technology-based tools are most appropriate for representative data collection in different contexts?

Speaker

Omar Seidu

Explanation

Understanding which digital tools work best in specific contexts is crucial for ensuring broad participation and representative data collection across diverse populations.

What pathways exist for addressing quality issues and building trust in citizen data?

Speaker

Omar Seidu

Explanation

Building trust between traditional statistical institutions and citizen data initiatives requires clear pathways for quality assurance and validation.

How can we avoid seeing citizens as free labor in data collection initiatives?

Speaker

Dilek Fraisl

Explanation

This addresses ethical concerns about exploitation in citizen data projects and the need to create shared value for participants rather than extracting data without reciprocal benefits.

How can citizen data be utilized to build trust in AI while being aware of potential biases?

Speaker

Maria Nordstrom

Explanation

As citizen data is integrated into AI systems, understanding how to leverage it for building trust while managing inherent biases becomes crucial for responsible AI governance.

How do we ensure clarity on ownership and consent when citizen data is integrated into public services?

Speaker

Maria Nordstrom

Explanation

Legal and ethical frameworks need development to address data ownership, consent, and usage rights when citizen data is incorporated into government AI systems and public services.