start it.

Please go ahead.

Thanks. So, good morning, good

afternoon, uh good evening everyone and

welcome. Uh so, I'm delighted to open

this virtual site event on citizen data

in the leadup to the 15th session of the

UN statistical commission. So, my name

is Yi Min. I'm the acting chief of the

development data and outreach branch at

the UN statistical division. Uh so this

event is organized on behalf of the

collaborative on citizen data uh a

multistakeholder partnership bringing

together

civil society organizations human right

institutions and national statistic

office agencies uh and regional partners

and partners together. So the breadth of

organizations

on this call also reflects exactly the

spirit of collaboration that this

session is designed to advance.

So a little uh about one year ago um at

the 56th session of the UN statistical

commission the member states uh endorsed

the Copenhagen framework on citizen

data. uh this endorsement was a true

milestone. It provide a shared

conceptual and operational foundation

for how citizen data uh that data

produced by people outside the formal

machinery of official statistic can be

systematically

as it could and meaningfully integrated

into national data ecosystems.

So what makes the Copenhagen framework

distinctive is not just that it address

data quality and methodology.

It also addresses accountability, power

dynamics and community ownership

alongside technical standards. In doing

so, it offers a governance centered

approach that enable citizen data to

scale without losing the trust and

consent on which it depends. Uh but

frameworks uh only matters through

implementation

and this is where today's event uh uh

focused. In the past year, the

collaborative

uh has been working on multiple fronts

to translate the framework's principles

into practice and the results are right

tangible. Uh for example, in Malawi uh

citizen data uh has been integrated into

the country's newly adopted national

strategy for the development of

statistics.

Elo citizen data helped to fill critical

data gaps in the 2025 voluntary national

review particularly for SDG3.

In Colombia work supported the

development of a citizen data maturity

model and a data quality assurance

framework in Ghana. it helped initiate

uh the use of a citizen data uh to

measure uh fa female genital mutilation

in northern Ghana. So these are not only

pilot experiments there are signs that

the framework is taking roots in

national systems. So at a global level,

the collaborative has been co-creating a

suite of knowledge products on data

quality, meaningful citizen engagement,

uh building national partnerships,

intersectionality and impact assessment

along with e-learning tools. uh sematic

working group have been established

uh including on gender and citizen data

on citizen science and on the

integration of citizen data um into

official statistics approval concept for

citizen data comments also under way. So

these achievements are are real but so

are the challenges. So our 2025 stock uh

taking exercise uh covering more than

150 uh responses

confirmed strong momentum alongside

persistent uh constraints uh limited

capacity inadequate uh funding and

institutional resistance. So capacity

building emerge as a top priority across

region. Trust and sustain the

stakeholder engagement

remain essential conditions of success.

So the next phase of work must be as

much about supporting institutions and

people as it is about uh producing uh

guidance. So in 2026

the collaborative uh will explore uh

establish regional and subregional

chapters to bring peer learning and

implementation support closer to

national context. So today's event is

part of the efforts.

uh over uh the next uh uh 90 minutes you

will hear from colleagues who are doing

this work directly on understanding

community needs and assets on practical

uh guidance tools on regional approaches

and on country experience. So I

encourage you uh to engage actively

through the slido um interactions and

the open discussion. So before we begin,

I would like to note a few housekeeping

items. So microphones have been disabled

uh to avoid accidental interruptions. To

submit questions to the presenters,

please enter them in the Q&A window. Uh

we will do our best to address as many

as possible. Uh for general comments,

please use the chat. The event is being

recorded and the recording and the

presentation will be available on the

event page following the session. Uh so

uh without further ado I would like

first invite uh how Chen from UN

statistical division uh to give a

overview of the co framework and the UN

statistical commission. Over to you

Howie.

>> Thank you. Thank you Yongi. Uh next

slide please.

Uh next slide.

Yes. So just um very quickly on the

collaborative on sitting data as Yi has

mentioned and we're the collaborative is

um managed I mean steered by a steering

committee that consists of 10

organizations they are listed under on

the slide and this it was established in

2023 and met with the mandate from the

UN statistical commission to develop and

finalize the Copenhagen framework on

sitting data which we have completed

that. I'm also providing a space to

share knowledge, resource, experiences,

fostering collaboration and provide a

platform for advocacy and mobilization

of relevant stakeholders and lastly

identifying

conceptual and methological gaps inform

further development of guidance and

you'll hear a little bit more on that

today. Next slide, please.

So, why did we have the framework? um it

is a share foundation for collaboration

when we started because we wanted to

talk about something among all the

different communities that with this

common understanding so and for as a

foundation also for NSO to play a

central stewardship role here and and it

is also a collaborative collective

commitment to responsible ethical and

professional production and use of

citizen data and it gives gives a common

language that supports collaboration

between NSOs and other data communities

and lastly it bridge

bridges citizens and institutions and

shift the focus from data to data

governance. Next click.

So the question is no longer is no

longer whether citizen data exists

but how NSO a national statistical

system can engage with it systematically

and responsibly. Next slide.

So a very quick overview of what's in

there. Uh there is a QR code for you to

scan and get to the Copenhagen

framework. uh please use that and it has

five elements. The first elements talks

about what citizen data is how important

engagement of citizen throughout the

entire GSBPM throughout the entire data

value chain is and the second is about

the principles of citizen data. If you

think about fundamental principle for

official statistics and this principle

of certain data really is about what's

so important for certain data that we

should be paying attention to and what

is the role of national synthesis

offices we have a section on that um and

and the fourth one element is enable

environment for sustainable production

coordination and use of data. How do we

really nurture that environment? And

lastly, what do we need to do as a

community to implement the coent tagen

framework? Next slide, please.

Yeah, very quickly. Um, a very simple

timeline. We started uh we got a mandate

to work on a conceptual framework in

2023 and the 54th session of the

commission at the 55th session and the

commission welcomed a draft framework.

Then last year uh 56 session 2025 the

commission endorsed the framework.

That's what Y has mentioned and this

year we're here to report back on the

implementation and here also to get

input to get your support to continue

our work and so where are we going at

the 58 session uh in 2027? So please let

us know. Um next

click yes. So the commission as you can

see that it moved away

uh moved this discussion away from not

just away but really moved from uh can

we do it to how do we do it.

I think that's it for my site. Um if you

like to find out more about the

framework and there's a QR code and now

over to you um Heather.

>> Thanks so much. Thanks so much Howie. Um

so uh to follow up uh Howie's uh

presentation of the framework and also

its um uh relationship to the UN

statistical commission, we wanted to

just do a quick interactive poll with uh

participants to get some feedback on the

impact of the framework and ways also

that it could improve our work. So we

have a few slido questions that we'd

like to invite you to join. Um, here's

the QR code for the Slido. Uh, and if

you join online, it's um slido.com and

the number is 2157089.

And this also has the passcode. So, I'll

leave this up for just a

another couple seconds and then we'll go

to our first question. Um, the QR code

and the passcode will also be on the

next slide. So, let me go there now.

Sorry, I'm

okay. Yes, this is it. Okay, so here we

go. So, awareness and use of the

Copenhagen framework. So, since its

endorsement, how has your organization

engaged with the Copenhagen framework on

citizen data? Are you not aware of the

framework? aware of it but not yet used

the framework, referenced it in

discussions or internal reflections,

used it to guide one or more concrete

activities and decisions

or not aware of the framework. I think I

had it in all of them.

Okay, we'll leave a couple more seconds

to get some more feedback.

>> So, the code again, so if you go to

slido.com

and you should see it here on the left

hand side of the screen, the number is

2157089.

Uh, and the passcode is on the screen.

Okay, so we have about 38% say they are

aware of it but not yet used. Uh 23%

referencing it in discussions or

internal reflections. Um 23% also using

it to guide one or more concrete

activities or decisions. 8% not aware of

it and 7% used to inform institutional

policies or regular uh practices. This

is really great.

Okay. Uh right. So we'll go to the next

question

if I can. Sorry. Okay. So the influence

on practice and decision-m

to what extent has the Copenhagen

framework influenced how your

organization approaches the production

and use of citizen data? Is there no

influence so far or limited influence

helping to frame discussions? Moderate

influence

um informing specific decisions or

pilots.

Transformative influence led to

sustained changes in practice.

Okay,

this is really great to hear um to get

feedback. Uh so we have a bit over 50%

saying there's no influence so far. Uh

24% saying that there's limited

influence but helping to frame

discussions. 24% saying significant

influence shaping methods, partnerships

or governance arrangements.

Okay. So I think this shows we still

have lots of work to do. Okay. I'll move

to the next question. We only have two

more. So perceived value of the

framework. Which of the following best

describes the main value the Copenhagen

framework has provided so far? Has it

provided a shared language and common

principles, helped build internal

external confidence to engage with

citizen data, supported partnerships and

uh coordination with other actor actors

or too early to tell or has not yet

provided clear value?

Too early to Okay.

Okay, so it's primarily helping build

internal or external confidence to

engage with citizen data over 40%. Also

providing a shared language and common

principles and also a bit too early to

tell. Okay, great. All right, last

question. Opportunities to further

enhance impact. So this is really uh

wanting to understand what would most

help enhance the impact of the

Copenhagen framework on citizen data in

your context. More practical country

level examples. Additional technical

guidance or tools for implementation.

Stronger peer learning and exchange

among countries. Greater engagement and

coordination among development partners.

Clear communication and outreach on the

framework. Or it is too early to

identify what would enhance impact.

Okay. So, primarily more practical

country level examples

uh would further enhance impact. Also,

additional technical guidance or tools

for implementation, but generally more

practical country level examples.

Excellent. Thank you all so much for

your participation. really appreciate

this feedback uh to better understand

the impact of the framework and uh how

we can move forward. Uh how I'll send it

back to you.

>> Um Yongi, our moderator.

>> Sorry, back to Yi. Thanks.

>> No, you you can take from here. Um so

next we would like to uh uh listen to a

recording from our one of our committee

members Karen Badge from the global

partnership on sustainable development

data. Uh Karen Batch will give us a

stock taking and exercise on the

implementation of the coher framework.

Hello everyone. This is Karen from the

global partnership and I'll be taking

you through the results of the stock

taking a needs assessment exercise that

we carried out in 2025 as part of the

work of the collaborative. It's almost

exactly one year since we carried out

this um assessment uh with the members

of the uh collaborative on citizen data.

So I'll take us through maybe the next

six or so minutes uh with the findings.

Um

just by way of introduction uh you may

recall that last year um the commission

uh endorsed the work of the

collaborative and therefore we wanted to

start with a point of information or a

point where we were informed and that's

why we carried out this needs assessment

exercise. We wanted to know what

knowledge and tools already exist across

our network and what were the main gaps

and opportunities both at the country

and global level but also just to

understand the priorities and needs uh

of our community and how the

collaborative can can serve the needs of

our uh of our community. And of course

this was going to help us in the work

that we were carrying out uh last year

into this year but also build that um

resource uh that is accessible to uh all

members of the collaborative but also

other institutions that are interested

in and data. The exercise we um you know

we thought it was quite successful in

terms of the response rates and also the

information that we received. It gave us

a really clear picture of what's out

there, what's already available and

where the gaps are. And it also gave

gave us more uh national, global and

regional comparisons and to understand

the priorities. And then we were able to

you know um summarize these findings uh

and help us have discussions with other

partners and potential donors but also

with the countries that we serve.

Um just by way of summary uh the

respondents uh as I mentioned we had a

good response rate 130 uh participants

answered the survey representing 54

countries and uh 111 organizations

spanning both um government

non-government uh NOS's multilaterals um

and the like. So that's um sort of a

summary of the types of organization

that gave us the responses largely

national statical office but also a big

number of civil society both national

and international society. When we

looked at the responses by uh

respondents by country um some countries

like Kenya had the highest response

respondents and you could see a pattern

u in also the other countries as you can

see in the slide.

Um just going now to the next um sort of

findings where we've grouped uh findings

by uh different group uh different

topics. Uh when we looked at the

available knowledge just asking uh the

respondents what sort of knowledge do

they already have and what insights can

we draw from them. We could see that

collaboration was most frequently cited

as an area of expertise that you know

people have the knowledge, people have

the expertise, they've been doing this

for a while and they felt that you know

they have something to share there and

um citizen engagement as well as data

quality was also represented uh and that

sort of sent a message to us that

there's a growing emphasis on uh people

centered data that is trusted.

some topics were less uh mentioned and

this really informed the work that we

did in the working groups uh in terms of

the the product. So intersectionality

was mentioned less frequently and while

you know the community recognizes its

value there still and uh it's

undeveloped or under understood and

therefore you know drove us to to doing

the work that we're currently doing on

intersectionality.

Um we also found that you know the

respondents did not explicitly mention

toolkits or methodologies but it does

play a foundational role especially on a

topic like citizen data. So um you know

it could be that there's just a real gap

or the people who responded of course

not everyone responded just um had not

sort of touched on that point but

several organizations offer capacity

building. Uh there are topics around

gender specific indicators, dashboards

and also going beyond uh technical input

to looking at supporting systemic

change. And then there's also responses

on methodological reflection analyzing

the why. And this is really the true

spirit of citizen data is that it helps

us to understand the why uh and unpack

uh you know insights uh beyond uh the

findings.

Um just to sort of group the expertise

from what we um you know heard from our

respondents there's a huge about 56% who

say that the organizations can offer

something in terms of uh skills uh on

multiple types of expertise. So really

we are starting in a good place that

within the community the citizen data

community there are several people who

have something to share.

Um and then we also asked what would

they like to learn from each other and

we could see you know and this is sort

of the point I was making earlier that

there's an interest in data quality and

methodology and also on community

engagement application and impact all

the way to technology and innovation and

you can see from the ordering of those

um areas of work. It's what has guided

really the work of the collaborative for

2025 2026 in terms of the knowledge

products that we are putting out there

uh to the community and uh we also asked

in terms of uh global guidance besides

global guidance what other support would

be helpful and this was um fairly

balanced uh training communities of

practice online knowledge uh repository

almost you know uh we're getting fairly

good uh scoring from the from the

response.

And then now the second grouping of the

findings is just the existing and

planned collaboration uh that exists

already in our community that we could

tap into and make and and benefit from.

Um there was of course collaborations

between national statical offices and

civil society which is quite common when

it comes to citizen data all the way to

collaborations with international actors

UN agencies and then most of them are

focusing on SDG monitoring policy and

budgeting all the way to data quality

and there are some structures that are

in place which are worth you know

documenting or emulating as good

practice

legal frameworks digital platforms and

then most of of them are long

established. Uh some pre2020s, some are

fairly new and some, you know, continue

to be to be developed.

Um when we're sort of reflecting on the

learnings, uh we're sort of looking at

what are some of the what were some of

the factors that our respondents feel

has led to the success of the

collaborations they have and what remain

the challenges. I think um and you'll

agree with me, those key factors of

success are not quite new. uh they

relate to most of what we all hear and

say you know adaptable methods, trust

and transparency, stakeholder

engagement, capacity building whereas

the challenges uh range from

institutional barriers, sustainability

issues and resource constraints as well

as uh trust and data sharing.

Um the second the third grouping of sort

of uh the fi the findings as as I

mentioned this uh needs assessment was

also helping us to know which countries

uh you know should we prioritize and

what are the priorities when it comes to

the countries that we serve and uh the

key observation and in this uh slide

you'll see that we've sort of clustered

what we had based on country respondents

and we were sort of um

classifying them based on you know where

there's an urgent intervention needed by

the collaborative where there's

significant support required and then

all the way down to minimal uh like

basic support and you can see from this

diagram that you know in a number of

countries there's a critical need and

also a fairly high need. So you can see

the orange and reds are much more than

the greens and the and the grays. What

this um clustering helped us to do is

also identify the countries that the

collaborative could start working with

uh in terms of partnerships uh from last

year onwards and with this we were able

to you know pick the top five countries

that uh we would prioritize as the

collaborative which was Kenya, Nepal,

India, Malawi and Colombia and it's

because there was a strong uh response

rate and also a diverse mix of

respondents so it was a mix of

government grassroots civil society

and other agencies and which sort of

gave us the strength of the evidence

that we were seeing and then of course

there was a high and critical needs in

terms of frameworks, capacity building,

technical support and funding which were

the building blocks that were sort of uh

aiming at uh some countries as well like

Malawi, Nigeria, Nepal, Ethiopia could

sort of start seeing some patterns on um

interventions across multiple areas

especially with you know the topic on

citizen data just beginning to gain

traction in countries. country. Those

are the patterns we see. Whereas in some

countries, you know, the discussion on

citizen data has been there for a while.

So, they've sort of moved to other other

priorities that they are now focusing on

when it comes to uh citizen data. And of

course just uh helpful to mention that

we excluded the US uh from the analysis

uh because most of the respondents were

international organizations uh not

necessarily um you know serving the US

government but just uh based in the US.

Um as I sort of come to the end uh in

terms of just the trends uh across the

regions now going from country up to

regions we could see that from Africa

and Asia there's most need in frameworks

capacity building and then you know the

global north the US and the UK we see

lower needs on operation but more on

sharing the partnerships and sort of

establishing partnerships with them and

then in between of course their

priorities for Latin America and then

two countries Vietnam and Philippines

also stood out as sort of worth uh the

collaborative building more

relationships in country and providing

additional support uh in country.

Um and looking into the concrete support

needs and this is what has really driven

the work of the collaborative uh is that

there are four clusters of developing

frameworks building capacity platform

and data management development as well

as partnership and knowledge exchange

and um there's of course the breakdown

of each of these uh four uh areas of

work which we've now divided into the

support we provide uh to the countries.

So we're supporting some countries on

developing frameworks and guidelines uh

some on capacity building um as well as

you know data management and platform

development as well as partnership and

knowledge exchange and I think the EGM

has always been also a really good space

to foster that learning exchange and

partnerships as well as of course the

inperson uh the virtual exchanges that

we've um consult uh hosted

and I think that brings me to the end of

my presentation. Thank you so much for

your attention and I wish you the very

best in the rest of the session uh

today. If anyone has questions from this

uh presentation that I've made, I'll be

very happy to follow up uh with

responses. Please leave your comments in

the chat or in the Q&A and we'll be very

happy to to follow up. Thank you so much

and goodbye from me.

So I would like to thank you Karen very

much and uh she she's traveling so she

recorded this message uh while she's

traveling and so big thanks Karen. So if

you have a questions, I just want to

remind you uh to uh put your question in

the Q&A um box. And so in the next uh

we'll have three uh different members

from the collaborative will present the

the guidance uh the the the sweet of

guidance that the collaborative uh uh

created in the past years. First uh

maybe I would like to invite uh

Charlotte Johansson uh our consultant uh

gave you an overview of the guidance

products. Um so over to you Charlotte.

>> Thank you so much Yangi. So yeah, so

what we saw from the survey that Karen

just presented is that there is this

need for uh more guidance and we also

saw it from the Slido questionnaire that

um that Heather was taking you through

earlier that there is a need for

guidance. So what we are doing now is

that we are working on uh developing six

different guidances on on different

topics. Um and the idea is really to to

help and support the stakeholders in

responsible and sustainable production

and use of citizen data and to fill this

gap that we see there is uh with filling

yeah with with the knowledge and

practices to support that in the

implementation of the Copenhagen

framework. Um the development of the

guidances is led by the

members of the steering committee. Um

but there's a a lot of other people

involved in this work. We have experts

teams, there are sounding boards. Um

there are pilots and testing. Um we get

feedback from collaborative members and

non-members. And we also uh conduct and

will conduct more webinars specifically

on the the different guidances. So I

will take you through uh the guidance.

So Heather, next slide please.

So the first one um is a guidance on

data quality on citizen data. Um and

this is to to kind of provide guidance

on how to evaluate and improve citizen

data quality and communicate its quality

um to users. Um it builds on uh quality

principles of the international

statistics uh community. Um and we'll

have like a special lens uh from the

from the citizen data point of view. Um

we also have a complimentary guide uh on

gender and citizen data that's actually

about to be published very soon um

specifically on on quality assurance and

it's led by by UN women in the

cooperation of this working group on

gender and citizen data that uh we have

uh under the collaborative umbrella.

Um the next guidance is on meaningful

engagement of citizen in data production

and use. Um first of all what does it

mean to engage citizen in a meaningful

way? Um but then also how do you engage

citizen meaningfully during the design

the implementation and sort of the s

sustainability of that engagement um

during all the yeah the the data

production and and use. Um these two

guidance will be um available only late

summer or early fall in 26. So um so

yeah so you have to wait a little bit

for those two. Uh next slide.

The third guidance is on forming

national partnerships for citizen data.

Um so what does it mean to to create uh

and establish these partnerships um

among um different types of uh

community? So we have those that are

from the official statistics community

and uh the citizen data actors. Um and

so there will be different guidance on

how to identify stakeholders and how to

assess the legal and institutional

conditions that might be in the country,

how do you build trust um etc. Um the

fourth guidance in is on creating a

national toolkit for citizen data. Um so

this is more looking at uh a toolkit in

the country to kind of strengthen

citizen data initiative and use. Uh so

it's about uh yeah having a national

toolkit that can support government and

non-government actors in in promoting

and and working with citizen data. And

these two guidance will also only be

available late late summer early fall in

26. Um but they're on their way. Um so

that's great news. Uh next slide please.

The last two guidances um they're coming

up soon um in the next few months March

April. um it's on intersectionality and

uh one on impact stories. Um so it's

about how do you bring citizen data to

life through the the impact

storytelling. Um and I will hand over to

uh Elizabeth who is the co-lead of the

inter intersectionality guide to explain

a bit more on that and to Heather on the

the impact story toolkit. So over to you

Elizabeth.

>> Thank you so much and hello everybody.

I'm representing the stakeholder group

of persons with disabilities. I'm one of

the co-leads along with open data watch

of the intersectionality guide. We

recognize intersectionality as a concept

looking at people's experiences that are

shaped by multiple intersecting

identities including race, ethnicity,

class, gender, age, disability, migrant

status, sexual orientation, and others.

Intersectionality comes from the

tradition of black feminist legal theory

and the term intersectionality was

originally defined by Kimberly Krenshaw.

But data intersectionality is based on

the concept of intersectionality

uh but going a little further. So, it's

an approach to data and data analysis

that offers a better understanding of

how multiple social identities interact

and influence a person's experiences and

outcomes and highlights disparities that

may otherwise be hidden or obscured when

looking only at one single dimension of

identity. So this guidance document is

an approach to intersectional data uh

which was already just briefly shared

with you by Charlotte and we uh put this

together because we want guidance to

give guidance on the type of data needed

for data practitioners, producers,

users, researchers, civil society and

communities that are interested in an

intersectional approach to data use and

data analysis.

It also offers a practical guide on how

citizen data and other data sources can

be used to informed intersectional data

analysis as a unique data source and

very importantly that it represents the

lived experiences of individuals and can

be integrated with other more

traditional data sources.

We uh started by looking at case studies

that looked at how citizen data can be

used in the data intersectionality

approach and then we built upon this. We

look throughout the whole data value

chain the collection publication uptake

and impact of data and we use the open

data watches intersectional data

framework as our guide. We also look at

intersectional approaches and household

surveys, citizen data for

intersectionality, qualitative data, we

have a very nice section on that and

mixed methods. And then the final part

is highlighting case studies where

intersectional data have been applied

and we have different examples from the

disability community, LGBTQ community

and and so forth. as a very brief

timeline and next steps. We are almost

done with our draft. We had a webinar a

couple weeks ago, February 4th, uh just

open to the public and we're still

gathering feedback from from that and

we'd be happy to share with you if you

want to also provide feedback. We uh

will be finalizing the documents soon.

um at the end of February we'll be done

with all the feedback and then um as

Charlotte said coming very soon will be

the final version and we will share it

on the collaborative website. We plan as

a next step to develop training tools

based on the guidance to present this

and actually to implement the guidance

note as a future step and I will end

here and thank you very much. Let me

know if you have any questions.

Yeah. And next I would like to invite uh

Heather Page uh from the UN statistical

division to present that to impact

story.

>> Thank you so much Yangi. Um so uh UN

statistics division and Danish Institute

for Human Rights uh were the co-leads

for the impact story toolkit uh that

we're developing also with a consultant

and uh in collaboration with

organizations uh and government entities

in the collaborative. Um, and so what

we're trying to do here is develop

evidence-based communication products.

Really looking at developing impact

stories that rather than focus only on

activities or outputs, uh, these impact

stories trace the journey from

information gathering to influence.

Really showing how insights inform

decisions, policies or practices and why

these matter to people's lives. Um we

want the impact story to really sit at

the intersection of the work of the

collaborative uh where we are providing

this these guidance and tools uh to

really show the importance of citizen

data. Um, and the purpose is really to

equip uh, citizen data practitioners

with step-by-step guidance to measure

and assess the impact of their citizen

data and initiatives and then also

translate those findings into compelling

and evidence-based impact stories. Um,

so what's in the toolkit? So, it really

focuses on two different parts. The

first part includes step-by-step

guidance on impact assessment. really

looking at um from eval evaluability to

methods and also strategy embedding um

including guiding questions for choosing

the appropriate impact assessment

method. Um and this also looks at

citizen data and initiatives that are

being undertaken by organizations and

also uh in government. Um really trying

to look at the whole uh um sequence of

events um or the initiative that is

taking place because you can have um

smaller impacts uh along the way that

you can also assess and evaluate um and

also tell the story uh of that impact um

before perhaps getting to the longer

term objectives of the work. Um and so

this really um actually also draws quite

a bit from methodology from citizen

science and impacts and then translates

that to broader citizen data work um and

looking at impact assessment throughout

that that chain. And then the second

part of the toolkit includes impact

storytelling. So really from assembling

that evidence to validating stories and

dissemination including how to for two

different approaches. I would kind of

call it evidence to story or story to

evidence. Um trying to make sure that

the evidence is is included um but also

that the stories um have a human touch

and that they um really really convey

the impact of the work uh in a way

that's accessible to lots of different

audiences. So it includes a lot of

different ways to um disseminate that

information. So we are testing the

toolkit um with organizations and

government entities that are part of the

collaborative. We've been working

together for quite a few months where

we're testing out the toolkit and we

will soon publish their impact stories

uh uh on the website. So this toolkit uh

should be completed in the next two

months. Um and so we uh really also look

forward to uh feedback on the toolkit as

well as your use of the toolkit. Um so

thank you so much.

>> Yeah, thank you very much for Charlotte,

Elizabeth and Heather uh gave us a

overview of the suite of guidance that

the collaborative have collaborate uh

has created um in in the past years and

also the plan for uh how to test and

pilot all this um uh guiding tools. So

if you have questions for uh three of

them, please please leave them uh in the

Q&A and box. And next uh we will uh like

to invite uh Jessa uh incarnation from

women and Jessa will give a presentation

and on the uh work priority sematic area

and engagement. Um

uh yeah go over to you Jessa.

>> Yeah thank you Yongi and as this session

reflects the conversation is now moving

from endorsement of the Copenhagen

framework to actual implementation. So

today on behalf of the working group on

gender and citizen data and its

co-chairs open data watch uh Franchesca

Perucci and UN women I will outline how

the working group is contributing to

that transition. Next slide.

So the Copenhagen framework as you have

heard is has established shared

principles but principles alone do not

implement themselves. So implementation

requires translation from norms into

usable guidance from commitments into

practical tools and the working groups

function as the institutional bridge

between those principles and real world

applications. They provide structured

thematic spaces where principles are

translated into tools, methodological

questions are clarified and lessons from

countries are cit synthesized. Next

slide. So creation of working groups

began with gender not because other

dimensions are less important but

because gender is universal and

crosscutting.

Citizen data initiatives are advancing

rapidly across sectors and regions. As

you have heard the task now is to ensure

that gender is systematically integrated

across the citizen data value chain. So

we also often speak of persistent gender

data gaps. But maybe what we call a data

gap may in fact be a systems gap. When

citizen data repeatedly emerges on

issues such as violence, unpaid care,

environmental harm, indigenous peoples,

or access to services, it is often

described as filling a data gap. Yet, if

certain realities consistently surface

outside official statistics, that raises

the questions about coverage,

prioritization, or lack thereof,

instrument design, or responsiveness

within the system itself. So, citizen

data is rarely attempting to replace

official statistics. More often it is

responding to areas where measurement

remains complex, evolving or incomplete,

particularly in capturing gendered

experiences.

And you see these patterns are not

accidental. They cluster in areas where

methodological complexity intersects

with power,

violence and paid care and environmental

burdens. And these are not marginal

topics. They are measurement stress

points. So starting with gender allows

us to to test how the framework works in

areas where inequality is most visible

and most complex. Next slide.

So this working group was established in

July last year at the high level

political forum. It is co-chared by UN

women and open data watch bringing

together 19 organizations and 23

individual experts spanning civil

society, official statistics, academia

and UN entities. Importantly, the

working group is complemented by a

broader gender and citizen data network

which allows us to expand consultations

and engagement beyond the core members.

So while the working group is the

operational core, the network broadens

its reach and diversity of input. So

since 2025, we have focused on three

areas. First, the gender responsive data

quality assurance, translating

principles into practical standards so

citizen data is credible and usable.

Second, measurement of gender-based

violence and sexual harassment.

strengthening approaches to capture

harms that are often under reportported.

And third, the gender environment nexus,

particularly within indigenous peoples,

ensuring citizen data reflects

intersectional and lived realities. So

across all three, our aim is simple to

make um gender responsive method uh

methodologies

across the board. Next slide.

In less than a year, the working group

has moved from dialogue to concrete

outputs. So first uh through

commissioned work with Mon Monica

Protesy in collaboration with the

working group so to develop a gender

responsive citizen data quality

assurance framework which will be

released in the coming weeks. Second,

another commissioned work with Anita Raj

in consultation again with the working

group which produced guidance on

measuring sexual harassment using

citizen data. It clarified definitions,

provided ethical safeguards, and how

citizen data can complement official

statistics. And then third, a background

document on indigenous peoples, gender,

and the environment is underway, mapping

systemic information gaps and proposing

methodological pathways grounded in data

sovereignty, one of the principles of

the framework. So some of this work is

still evolving but together this output

showed that working groups are not

discussion spaces alone that they

generate technical substance.

So next slide. What makes a working

group effective? In our experience three

things matter. First focus. We did not

debate gender in general terms. We

focused on specific methodological

questions related to data quality and

measurement. Second, disciplined. We

committed to defined outputs within a

timeline, a gender responsive data

quality assurance framework and the

guidance on sexual harassment. And

third, coherence. The work was not

isolated. Our work was embedded in the

collaborative architecture and informed

the broader citizen data quality

framework. And so when these three

elements are present, working groups

move from discussion to delivery. And if

I may say aside from the gender and

citizen data working group, there are

two working groups upcoming. First is

the working group on citizen science and

second would be this a working group on

integration into official statistics.

Next slide.

Another thing to to stress in the in the

work of this working groups this is not

a one-way relationship. The

collaborative for example shaped the

working group on gender by anchoring it

firmly in the Copenhagen framework

principles. At the same time the working

group on gender inform the broader

design of the citizen data quality

framework and strengthening how gender

is reflected across teams and and this

is a two-way process. It is how

institutional learning happens. It shows

that thematic groups are not isolated

and we it helps shapes the collaborative

direction in both ways. Next slide.

So we began by suggesting that we often

call

uh persistent gender data gaps but may

in fact be signal areas where

measurement systems can be strengthened.

So for national statistical offices, the

question is not whether citizen data

replaces official statistics. It is how

statistical systems remain responsive as

new forms of data emerge. Working groups

offer a structured space to translate

emerging signals into methodological

clarity and shared standards. Engagement

in this process continues through the

collaborative and the thematic working

groups. Ultimately,

they support strengthening the

responsiveness and resilience of the

statistical systems which is at the core

of the of this commission's mandate.

Thank you.

>> Thank you so much. Ha gave us such a

compressive overview of the uh working

group on gender and the citizen data. um

the uh so if you would like to join so

just uh uh send us uh uh the information

and there's a QR code you can use. Um so

u next I would like to invite uh our

colleague from ESCAP Audi Marshall uh to

present the regional coordination and

subreional uh collaboration work on

citizen data. Um over to you IO.

>> Hi everyone. Um I'm A IO Dele Marshall,

associate statistician at ETSCAP and

we're set to become the regional chapter

for the implementation for the

Copenhagen framework. Thanks for the

opportunity to share regional um

perspective from ESGAP. Following the

endorsement of the Copenhagen framework,

the focus has shifted toward a key

question. And how can we translate the

principles into practice for the diverse

national context that exists in this

region? The region includes highly

advanced statistical systems along with

smaller more re resource constrained

statistical systems. So the diversity

makes structured adaptable

implementation especially important.

Asians. The Pacific is home to immense

diversity geographically,

institutionally, socially. Many

countries face common challenges. The

need for more granular and timely data.

Um, reaching vulnerable or marginalized

populations as have been mentioned here

on this call. Um, ensuring disability

and gender inclusion in data systems.

Much like what my colleague just said um

as the focus for the working group um on

gender and citizen data,

citizen generated data it already plays

a role in several contexts here in the

region often through community based

monitoring um civil society initiatives

or party pac party sorry participatory

data collection. Um in many cases the

data is already informing development

planning um including common country

assessments

and and voluntary national reviews here.

Um next slide please.

The region has several strong assets.

First, there are active civic tech

communities, academia, and civil society

organizations that are not only

advocating for transparency, but they're

actively building tools, generating

analysis, and supporting inclusive data

ecosystems.

Secondly, there's a lot of expanding

data infrastructure and digital

infrastructure from digital ID systems

to administrative platforms and improved

connectivity and this creates the

backbone for more integrated and timely

statistics.

Thirdly, there is growing experience

with data innovation including G

geospatial data, satellite imagery,

mobile data and advanced analytics. And

many countries are now hoping to move

from pilots to actually

institutionalizing

these projects and this using this um

alternative sources of data in CRBS. Of

course, civil society plays an essential

role in reaching marginalized

populations and improving registration

coverage. And importantly, NSOs here are

increasingly embracing structured

engagement, shifting from being sole

producers of data to coordinators within

a broader national data ecosystem.

Um, next slide, please.

So where engagement is emerging as we as

we've identified several countries where

enabling conditions are strong. I won't

go through each of them just in the

interest of time. Um but they're listed

here on the slides for various reasons.

Um the countries are being highlighted

because they demonstrate

clear demand for more inclusive and

disagregated data, commitment to

disability inclusive development, active

collaboration with our UN resident

coordinated offices here and established

engagement in VNR processes and other

activities.

In many of these countries, citizen

generated data and evidence already

exists, particularly in areas I keep

mentioning disability and gender

equality and community service

monitoring. I'll just flip through the

other slides cuz the other slides um

show other countries as well. Um but in

the interest of time, I'll just

summarize quickly. Um these countries

they have also requested support to

integrate citizen data with traditional

data sources to improve disability

statistics. Um we're launching a project

development account project soon on

citizen data um to improve disability

statistics and to inform inclusive

policym

and the project is responding by

developing practical integration methods

building partnerships among NSOs

organizations for persons with

disabilities and relevant line ministry

is strengthening these organizations's

capacity

to lead citizen data initiatives and

supporting use of results in policym and

this goes beyond disability statistics

and for other statistics or for other

information that is pertinent to

national experience.

Um next slide please. I'll just touch

briefly on the challenges.

Um next slide.

Thank you. So yes, by shared challenges

and lessons learned across the sub

regions here, there are similar

challenges. Ensuring data quality and

representation,

um safeguarding privacy and informed

consent, clarifying institutional roles

and mandates and building sustainable

technical capacity and a consistent

lesson is that trust is foundational.

Building trust among the data holders

and building trust in the public sphere

as well.

Citizen data we think can strengthen

statistical systems when governance

frameworks, transparency and ethical

safeguards are clear. And this has been

a common message throughout this entire

presentation.

And we think the Copenhagen framework

provides a shared language for

addressing these issues and not just a

shared language um but practical tools

and regional dialogue as it remains

essential.

So next slide we think our way forward

our escap role is going to be

multi-layered.

First we need to convene safe spaces for

peer learning and exchange among NSOs

and all the data players all the

partners in this space translating and

helping to adapt the global principles

and all the guidances that have been

mentioned here um on this call to

regional realities particularly for the

small island developing state and for

capacity lower capacity systems and

lower capacity statistical and data

systems

work is already being done by the dash

teams um on hol of society approach to

building agile statistical systems. I'll

just go back and give some background on

as to what the dash teams are. They're

the data and statistics horizon teams

which report to the committee of

statistics here and very similar to the

working group that was described by

Jessica um on citizen data and gender.

It's less formal. It's meant to be time

bound and activity and delivery bound.

So we see these teams, these dash teams

as being essential to doing the work um

that countries are calling for that are

high in demand um in this region. And

this particular dash team, the one on

the whole of society approach was

established to explore

how um all of the data players and all

of the citizen data and the data being

held by different data holders can be

integrated into various aspects of work

that the NSOs are looking to do across

the whole data value chain and exploring

how NSOs can engage a wide range of

stakeholders to ensure that official

statistics reflect the needs and

perspectives of all all sectors of

society. And it acknowledges the roles

that citizens and NSOs play in data

processes formulating action points for

the sustainable production and use of

citizen data.

And this whole of society approach

entails deliberate and proactive

engagement and collaboration with many

players in society. And then ESCAP's

role extends also to aligning with

RCOS's, resident coordinator offices and

other development partners to ensure

coherence and sustainability.

So moving forward we see priority areas

in demand driven pilot initiatives

dash teams and those have already been

established and will be established

based on need and demand practical

guidance that is adapted and tailored

for a regional perspective and sustained

collaboration beyond the initial pilots

that are happening in the region.

We're thinking implementation must be

incremental, but it must also be

countryled and grounded in national

statistical mandates for it to be

sustained.

I will stop here. Um, we look forward to

continuing this work with the member

states and partners across the region.

And thank you and I'll hand back over to

Yangi.

>> Thank you so much uh Aayod. And it's

really great to see uh the work uh in

escap and other countries and escap

support uh on citizen datas. Um also I

just want to mention that our work the

citizen data work actually started in in

Bangkok in ESA ESCA building that's

where the first meeting uh took place.

So we went back again last year and had

our first meeting. So this is a a region

that has greatest support and

interesting and in the unsafe data. Uh

so next I would like to invite a country

representative uh to uh to pres present

their country exper experience. So I'd

like to invite uh uh basani

from Ghana uh statistical service to

present the how Ghana use state and data

uh for for national policies and uh uh

SDG monitorings over to you um Basil

thank you very much for the opportunity

so my name is Basil Tongan and I'm

making this presentation from Ghana so

um next slide please.

So um for Ghana u why did we choose to

adopt citizen data? So in 2017 an

assessment was done on our data needs um

that could help us in form monitoring

the sustainable development goals and um

this uh we realized that 33% of the the

indicators on the sustainable

development goals are based on data from

the census and service and this was not

enough for us to um use when it comes to

the monitoring of the SDGs. So hence we

had to um explore different other data

options that could help us um be able to

address the SDG data gaps. So hence the

adoption of the citizen data approach in

Ghana and this was mainly so because um

citizen data also helps to amplify

citizen voices. It enables citizens to

voice out their concerns and also target

specific needs within the society that

can um actually influence change. So

through the adoption of citizen data um

we able to strengthen accountability and

we also were able to have an in um an

everyone involvement when it comes to

the data collection exercise where uh we

able to reach out to persons um with

disabilities among several other

vulnerable populations and this aligned

well with a human rights based approach

because um the data um it respect the

rights of the individuals also enables

people um to feel more comfortable

contributing um to the development of

the country and this has hence helped us

in monitoring the sustainable

development goals and also with our

voluntary national reporting. So um

Ghana has so far undertaken five of this

um projects using citizen data. Um the

first was the gender based violence

which um helped us to be able to um

measure the proportion of women um and

girls age 15 years and older who were

subjected to sexual violence by persons

other than an intimate partner. And um

this proved to be very effective cuz we

used um a um the application called

let's talk which made it easier cuz we

had embedded in this application um

different other approaches that allowed

persons um to be able to report either

they were using smartphones or even if

for persons who were not having access

to smartphones and for um the vulnerable

population the persons with disabilities

and all of that we're able to um report

concerns regarding gender based violence

and um we able to monitor on the

indicator 5.2.2

and then we also adopted citizen data

approach to measure waste management um

using the clean up Ghana um approach

where we developed the app and citizens

um we're able to report on waste which

help us to also measure the sustainable

indicator 11.6.1 6.1 which is on the

proportion of the municipal solid waste

that was collected and managed in

control facilities out of the municipal

waste generated by um cities. So this

again also proved successful. The third

um project which we used citizen data

was the marine data and um this was yet

another success and u we also adopted it

to influence um decision making. For

instance the um DACF that is the

district assembly common fund support

app which enable persons with

disabilities um to effectively voice out

concerns regarding the allocation of

funds that were meant for them as part

of the um district common fund

allocation. And then the quite recent

one that uh we adopted was on the um

sustainable development goal 16.6.2

which is on citizen satisfaction with um

public services which also allowed us to

be able to measure the proportion of the

population that were satisfied with

their last experience of public services

in Ghana. And we um limited this to uh

public services such as education,

healthcare and government issued

identity services which had to do with

um passport um collection the passport

the collection of passport the um

application for um birth certificates

and application for um Ghana card. How

did citizens um what were their

experiences with this services? Next

slide please.

So um what we can see currently is the

different applications that we developed

for the various u projects that we

undertook using citizen data. So to the

top left corner is the gender based

violence uh where we developed the

lessto app and um the middle side was

the solid waste management and then the

um to my right is the PSSS app that's

the public service satisfaction survey

app which allow persons to um report on

their experiences of public services. So

in we use different um apps we develop

different apps to enable um people to

contribute and then we able to collect

the data and analyze the data and

provided feedback um to persons. Next

slide please.

So um this we did not do alone. We did

it in collaboration with several other

um agencies. For instance, the UNDP,

Oslo Governor Center, um the United

Nation Environment Program, um GIS,

local authorities. Um for instance, in

Ghana, we have um 261

um mun metropolitan municipal district

assemblies. So we engaged them um given

that the project was being undertaken in

those specific districts and we also

involved civil society organization as

well as the academic institutions. This

were all his stakeholders that we

brought on board to enable us um to

undertake this project. Next slide

please.

So um for the um next few minutes I um

would be explaining Ghana's experience

using the um key pillars of the

Copenhagen framework. Um so the first

has to do with the collaboration. So

through collaboration what we did was to

build a strong partnership with our

stakeholders, all interest groups, all

institutions um that were relevant in

helping us to be able to undertake the

projects were involved. And we also

engage civil society, academia and as

well as the local authorities to bring

them on board to share experiences and

also learn from one another. And this

actually proved to be very successful

because um we able to engage them at

different levels and also s their views

to be able to undertake this project.

For instance, the technical coordination

um we undertook it at the national level

where we involved the ministries

departments and agencies and at the

regional level we also interacted more

with the regional co coordinating

council um that was able to um help us

reach out to the 16 administrative

regions in Ghana and again at the

district level we also involved the

metropolitan municipal district

assemblies 261 district assemblies. So

depending on where um this particular

project was being piloted, we involve

the specific districts that were um

involved in this particular project and

by so doing we able to um share a lot of

learning and methodological adaptations

that um helped a lot in um helping us

achieve the aim of the project. So the

result in a nutshell through the

collaboration we're able to embed as

part of the national statistical system

data. So it has come to stay and um is

now part of the national statistical

system in Ghana. Next slide please.

So the um second key pillar which is on

the participation and inclusion um we

realize that citizens are actually um

part of the data value chain and to in

order to be able to successfully

undertake um citizen data. It's

important to always involve citizens as

part of uh this data value chain and to

um get citizen involvement in this data

value chain. the um applications were

developed in a way that um created that

enabling environment easy to use and

also um made it accessible to citizens

to be able to use and report on certain

um projects that we undertook. So for

instance the um gender based violence

was we we had developed it in a way that

could enable people to even report using

the proxy. So if instances um where the

victim does not maybe feel very

comfortable using the application, they

able to um contact someone that they

trust and they able to report through

that person as well. So we made it very

interactive and accessible for all

persons and um we able to then notice

that um this citizen data approach um

when developed in a way that is

inclusive is able to solicit the needed

feedback. For instance, in the U public

services satisfaction survey which was

the PSS, we noticed that um the we had

significant number of persons with

disability who were reporting of their

experiences with public services. So um

ordinarily maybe a survey would not have

really been able to reach out to um this

group of person but because we had

embedded um interactive um systems to

enable all persons report using the app

we able to get feedback from diverse

group and this actually um strengthened

the voice and then also created that

ownership. So for instance the district

assembly common fund which had to do

with persons with disability uh it

created that ownership and gave them um

that failing of being part of the data

value system. So they were willing to to

contribute their um feedback and helping

us report on issues that were very

relevant. And this actually has result

in a shift from what we term as citizens

now shifted from being data subjects to

active data partners. So they were being

part of the process and then uh were

also willing to always voice out their

concerns which helped us um a lot when

it came to the reporting as well. Next

slide please.

So for the ethics and trust uh which is

one other key um pillar of the

Copenhagen framework through this ethic

and ethics and trust we notice that it's

important that uh we need to always

safeguard the rights and um independence

and credibility of every um data system.

So through so we um Ghana statistical

service was the institutional was

providing the institutional leadership

that's um and then um the data

confidentiality we also ensured that um

citizens data was um some of this

citizen data approaches for instance the

gender based violence um deals with

sensitive data. So um we needed to

establish that trust that there is that

confidentiality in handling such

sensitive data to make people more

willing to participate and more willing

to um provide us with the sensitive

information that is needed in helping us

measure some of this progress. So um we

did so by also making it um very

inclusive in a way that respected the

individual identification and allow

persons to report um as who they see

themselves to be. So and their constants

were also sought. So we had the consent

form which um was first shown to them

and respondents who were um feeling

comfortable to continue with the with

the application then move forward. Those

who were not had the chance to decline

and this process was so transparent and

we also made sure to document it. And at

the end of it all most importantly uh

the data that was collected after

analyzed we reached back to the society

um to um let them have an experience or

feel of what the results were like and

this actually led to several other

initiatives going forward. I'll be

mentioning some and this enabled that

trust building and also made it easier

for us for places that we conducted this

pilot. It was easier when we needed to

scale it up because we had already

established that trust and um believe in

the fact that the data that citizens

were provided was being protect

protected and um being um the

credibility of the data was assured.

Next slide please.

So for sustainability

um we have institutionalized citizen

data for long-term impact and um this we

have been able to do based on the first

pilot project and from the pilot project

we able to continuously refine our our

tools for data collection based on our

experiences and um this has so far

demonstrated the needed impact. For

instance, the district assembly common

farm um project that we use um citizen

data for uh sometime in on the 24th of

October 2025

um the president of Ghana had actually

announced that the um district

allocation for persons with disability

to be increased from 3% to 5%. And this

announcement was made as a result of the

project that we undertook using citizen

data reaching out to persons with

disability trying to find out whether

they were first of all aware of the

district assembly common fund allocation

meant for them and also for those who

were aware uh were they receiving this

support. So through this initiative we

were able to um publish the results and

this led to a very significant um policy

impact where the president increased um

and the policy the the funds allocation

for persons with with disability from 3%

to 5%. which was indeed as part of the

recommendations that we made from the

project that we undertook on this and so

far this has um is going to continue

because it's aligned with the

sustainable development goals and it

also um is part of the Ghana statistical

service and the national development

planning commission of Ghana's mandate

to always report on the sustainable

development goals. So going forward uh

we will continue to enhance this

reporting and ensure that we use citizen

data to complement our traditional data

sources and help us to be able to meet

um and address data gaps that were

existing. So this gradual integration

with um would continue and we hope that

it will become a part of the

administrative system where we can um

routinely get data on citizen data to be

able to measure Ghana's progress on the

sustainable development goals. So based

on that the result has positioned

citizen data as a complimentary data

source and it has also led to the system

strengthening innovation where we are

others stakeholders who are part of the

national statistical system are now also

trying to adopt the citizen data

approach to be able to undertake the

approaches. Next slide please.

So um this wasn't without challenges. uh

we encountered some challenges. So um

for instance resource constraints um and

um there were issues um with

methodological concerns as well as the

initial skepticism from some citizens um

who were not too sure how this works and

also um issues of data quality which

came up in the um by by the previous um

presenter as well. So to some extent we

try to address some of these challenges.

So for resource constraints uh we

started by undertaking pilots. So for

places we are not able to upscale it to

the entire country. We we would um

undertake it using a pilot approach

where we would select few districts and

then we try to see how this turns out.

So based on that then we are able to

upscale it as and when we are able to

get some resources and uh for issues of

me methodological concerns um there's

still this continuous review uh of our

methods and going forward how best we

can ensure that this become very

comprehensive enough to um target all

methodological concerns and for the

skepticism uh we have demonstrated to

the success stories from other um

projects that we've so far undertaken.

So based on that people have come to the

realization that citizen data is

actually a gamecher and when abducted

can influence the necessary change that

we need and for the data quality

refinement issues um GSS has establish

itself the leadership of the national

statistical system and so doing we've

been able to u lead when it comes to

issues of data quality where we've adopt

and ensure that data quality is aligned

with our um data quality management

strategies to ensure that the data of

pallet. So please next slide.

So in conclusion, citizen data in Ghana

has actually demonstrated that indeed it

can help us address our data gaps. It

can also um influence in strengthening

the accountability of institutions and

as well as empowering communities and

making people feel that they are part of

the data value change. And this has so

far um demonstrated the relevance and

leadership of the national statistical

system in helping meet the actual needs

of the of the citizens and ensuring that

the needed change is being met and

addressed. Um so on this note I'll say

thank you very much and if there are

questions and concerns um we will take

them um on the chat. Thank you very

much.

Thank you so much. Um so uh it's a big

congratulations on on Ghana statistical

service uh have been it's it's a

champion in using citizen datas in so

many and diverse areas and also I know

like uh you this is progress has made

pretty fast in in the past only five

years five four or five years you have

made so much progress in in using

citaden data to monitor many of the SDGs

And uh so this is a great uh

congratulations. I think we have a few

minutes maybe for questions and Q&A. So

I will maybe open the floor. Um so but

uh before I open the floor I would like

to remind you u to uh have a two minutes

intervention maximum and maybe allow

three uh questions for the presenters.

Um yeah. So now let me open the floor to

see if anyone have a a questions. Um

let me also try to open to

enable so you can unmute yourself and

also

turn on your camera. So if you can raise

your hands now

anyone from the

participant and uh before that I can

read from the chat.

Okay let's see one one person has a hand

to raise. Let me find out just please go

ahead. Yeah Sarah Sarah

Hi everyone. Can you hear me?

>> Yes.

>> Hi. Um, yeah, apologies for the

background noise. I'm biking through a

very icy Copenhagen and listening to

this very exciting conversation. Uh, it

was so exciting to hear all the

developments in Ghana and Ghana has

really been uh an ally and a pioneer and

visionary as well in this type of work.

Um very briefly I just wanted to ask um

if you can point out very concretely

what has changed in the way that you

work with citizen data since this whole

movement of the collaborative data has

started. Uh has it inspired uh different

ways of engaging citizens in the

projects in citizen data projects that

you have um or to support citizen data

initiatives from society organizations.

um if you could yeah point just a little

bit to this to the shift of um uh how

this work has inspired in a statistics

office like yourselves uh in in this

type of work. Thank you.

>> Thank you Sarah. And maybe I would like

to invite Basil and Omar. Omar is also

on the call. Omar the deputy and DG and

Ghana service uh can address these

questions.

Okay. Yeah. Thank you very much um for

the question. So um for Ghana

statistical service as the national um

statistical organization um this has

really been a gamecher. Um so for

instance um prior to this approach of

citizen data um we as the national

statistical system were mandated to

report on the sustainable development

goals. Um but from our assessment that

we did we noticed that just 33% of the

indicators on the sustainable

development goals can be addressed using

our census and survey data and um

meaning that there were a lot of um

other gaps that needed to be filled. So

um for an approach such as citizen data

it has come in handy and it has come um

at the appropriate time because we are

able to utilize this um tool to be able

to complement the existing data gaps. So

it has been um a game changer I think.

>> Yeah thanks um BO

I also saw has a um yeah

>> go ahead. Yeah, thank you very much. Uh

just to add that as part of the work we

have done, um Ghana is one of the few

countries that has developed a

disability data framework to guide

international statistical system on how

to incorporate a disability data in all

our data collection processes including

um non-traditional data I mean citizens

data among others and this somehow was

influenced by the work we have been

doing around citizens data. Thank you.

Thank you so much, Omar. I know you're

you're really a champion and pioneer in

this area and really u pushing uh so

much um and and gave us a lot a good

example that we would like to invite you

probably share with more countries to

use all the experience you have gained

in in using citizen data. Um so um maybe

I'll invite one or two more questions if

you have any.

Yeah, feel free to to raise your hand.

Okay.

I don't see any more hands up. Um,

uh, I think also we're we're really

Yeah, it's Omar. Uh, Ali. Yeah, go

ahead, Omar.

Can you hear me?

>> Yes, I can hear you.

Thank you very much for all these great

presentations and I I it's really

inspiring and it gives a lot of ideas

for countries who want to do it and the

the e-learning course on citizen data

was really fantastic on the on the

Copenhagen framework was great with

great examples and there was one an uh

case I mean one one uh topic that I was

interested in addition to what was

presented by Statistics Ghana um is uh

what advice or or or recommendations or

ideas would you uh share on the use of

citizen data when it comes to population

on on the move or forcibly displaced or

even stateless people as you you

probably as you know I mean it's very

sensitive and in in many places and I

was wondering if uh you you you could

share some some thoughts on that

Thanks. Thanks Omar. Um I I don't know

if any of the the presenters and or

member of the collaborative have any

answer on this and please come in

or count know the the any of the

experience city data for people on the

move.

>> Yeah. How

this Omar from Ghana?

>> Yeah. Yeah. Go ahead. Uh Omar.

>> So populations on the move. I think

citizens data will be one great way of

reaching out to them especially if many

of them use uh phones or some other

medium of communication where you can