 Good morning everyone. So you've heard that making maps and DHIS2 is easy. You've also gotten to see a lot of the really fantastic features within the Maps app. And you've also seen that there's a lot of really powerful data that's made available to DHIS2 users through a tool like Google Earth Engine. So population data and earth science data, which coupled with the routine information that you have in your DHIS2 instances can make very powerful maps. You also heard though that the Maps app is one of the analytics tools that's the most relatively least used within the DHIS2 platform. So we wanted to learn more about what are the reasons behind the limited usage by gathering insights from the field. So we started a collaboration about a year and a half ago, including UNICEF, Grid 3, the HISP Center, HISP South Africa, and Ministries of Health, and HISPs in five countries in eastern Southern Africa. Kenya, Uganda, Rwanda, Mozambique, and Zambia. And again, the idea was to understand why the app is relatively limited in use and also what are some of the current practices in the field and how can this be supported better within the existing functionality. The results today reflect the inputs of many individuals. We captured in the slide pictures some in the room today and some that are joining remotely. And so we hope you'll be inspired by some of what you see today as a result of what you can do with some capacity strengthening and leveraging some of the functionality within DHIS2. And then you'll be part of the community that we're building here to strengthen map use. A strong motivation behind this collaboration. Bjorn shared some of the data that's made available, for example, through WorldPop, innovative data that's very granular and can be aggregated to different units of analysis. And then we see that there's a strong demand to represent data spatially. And again, we heard from Scott that this does require special skills around how to represent data spatially and how to use and interpret that data. And again, we understand that there's limited use of this information. So we wanted to get insights from the field and identify what are those opportunities to strengthen map usage. So we convened in Nairobi last November, and we brought together Ministry of Health from Kenya and Uganda, including program staff and HMIS staff. We brought together DHIS2 developers, and we brought together population modelers, along with HISPs that support implementation in these countries. And we used a range of different modalities to facilitate dialogue. The dialogue and discussion was really important. Again, to find out what are some of the current practices in the field, what are some opportunities to improve and where users were having some challenges or constraints in using the DHIS2 platform maps up. So what did we learn? As you heard earlier today, we know that facilities in terms of using data and also in districts like to have map printouts. And we found out that the functionality and DHIS2 in terms of downloading and printing maps had opportunities for improvement, specifically around some of the labeling, the download options, and the layout. And so as you heard today, in the latest release of DHIS2, this was one of the features that was prioritized. That was a direct result of some of the consultations that happened, again, having the diverse group of people, the ministries, implementation support teams, and also with the exchange of population modeling team and others. We also found out that the process for signing up for Google Earth Engine was very cumbersome. So again, while many users may have known that these features existed just as you learned today, there were challenges in setting up the access, the sign up for Google Earth Engine and DHIS2 in the national instances. So again, this became apparent from the dialogue that took place. And now the process is simplified and since November there have been 18 countries that have now enabled this feature in the national DHIS2 instances. You also heard earlier today about the need for capacity strengthening around mapmaking, interpretation, and use. We learned from the field that users would like to have more skills development in this area. And also that they were not always clear what are the possibilities of representing data spatially and how this might differ from analytics and charts. We also learned that users wanted to have ongoing capacity strengthening given turnover of staff, and also the need to scale and sustain. This isn't a one off thing. So one of the things that we did working with HIFS South Africa was to develop an online Moodle course that can also be further adapted for national, if you happen to use Moodle in your countries. That provides some principles around GIS and introduction around how to use the maps out. We also developed a level two maps Academy and Sylvia will be sharing more in a little bit around what's possible in terms of with in a short amount of time, some fantastic maps that I hope you all will be inspired by. We also learned that there's a challenge of data. So data availability, particularly population data at the lowest levels of the system. And issues with missing facility coordinates, and also with misplaced coordinates and having updated shape files or administrative boundaries to represent changes over time and for example district formation. So all these things are realities that will come up when, for example, making maps, but one of the important lessons that emerged is that by highlighting these issues by using the data. It's created greater demand in terms of improving the geo data and DHS to and also a greater demand for using some of the innovative population and earth science data that we have been sharing. So with that, I'm going to turn over to my colleague Sylvia who's going to be sharing more about the maps Academy. Thanks Maria. And good morning everyone. My name is Sylvia Ren. I'm a GIS consultant with UNICEF and grid three. So if you have any GIS related questions around data or GIS come see me. I'm around. So I just wanted to give you a quick overview of the level to maps Academy that we did in Cape Town, which was maybe a little bit different than some of the other academies that have been held. So first of all, we spent a lot of time trying to make sure we get the right mix of people to attend. And this was not just the technical teams. We really wanted some program staff and decision makers within the programs there as well. And we wanted them to come from the same country. So if a country was present. It would be both the technical and the data use teams that that that were invited and that came to this level to maps Academy. We had some pre-course requirements. And one of them was that they needed to have done a level one Academy and that they took a Moodle, which was an online maps course so that they already had some foundations before they came in to this Academy. We did also make sure that the use cases were based on on use cases that they were using or needing in country within the next few months. So, so the maps that they produce and I'll show some examples in the later slides were some that they would be using back home. We also use the country databases so we didn't use Sierra Leone or Laos, we used all the country teams were able to use their own instances. We had some really fun activities so we also tried out the tracker where we mapped ice cream shops with in Cape Town. And this was mainly because a lot of people they see these these roster layers with population in them and they don't really know what to do with that. So we had people go out and estimate populations around ice cream shops. We also have supported with the online learning so that was the Moodle I mentioned and we will be following up with participants as well. And if you're more interested in this level two maps Academy, and and some of the things we did then Nora will be talking about this in a lot more detail in tomorrow's session. Sorry, everyone, we're having some internet instability and if you're not, you don't have something essential you have to do with your computers are depreciated if you're not doing it's high bandwidth. So I'm going to keep the stream going which is crashing at the moment. So it's appreciated you shut down any high bandwidth activity that would be great. Thank you. Okay, thanks. So I just wanted to show a few maps that were made by the participants. And please keep in mind that while some of them have done the level one maps Academy, these are not GIS experts. There are people that are using mostly that the DHS to maps up with some of their data, and based on discussions that they had with their program staff that were also within this maps Academy. So this is a map of Uganda. And that shows the women of childbearing age, and the ANC for coverage. And here you will see that the black is in the gray is the women of childbearing age per hectare, and maybe just to add to that. This is really powerful because it shows you the location of populations. It's six or 10 women there is it's not that accurate. Especially a lot of this is 2020 data it's it's kind of a top down approach which you can look at more on the world pop website. But for the first time I think some of the DHS to users can actually see where people are in in their catchment or in their districts. They've they've put facility distribution on there as well. And then they can kind of see the ANC coverage. They've also then made a map to look at the number of deliveries, and saw that a lot of while we do have women who are doing ANC visits. There's a good possibility that they're traveling quite far up to the north there to actually have have the babies. So here's an example of the suit to this one actually won the maps competition. And here you can also see some of the level of detail that these maps can give you. We're getting a lot of requests from countries to do geo enabled micro planning. There's a lot of catchment area maps that do have a lot of detail. And here you can see, you can see a lot of detail in in the, in the yellow, the yellow boundaries I think I'm hoping you can see them. Those are the catchment areas that were generated by the cross cut app. And they also showed the home deliveries by, by using the bubble map there so you can see St. Joseph's catchment has a high number of home deliveries, and then they use the new ANC clients data as well to show how many new ANC clients are there actually within that catchment area that's showing a lot of home deliveries. And then they also use the, how many of them are under 20 years of age because there's a high maternal mortality in that district in general. And here's another example of the map where they used the Penta one data together with population, and they used two kilometer buffers to look at where a population that are over 10 kilometers away from our health facility. And again, these are basically map newbies, you know, being able to do this in the DHS to here we have an example from Zambia, where they're just kind of drilling down to say well northern province actually looks pretty good it's in the green. But when we then look at the districts of that northern province we can see that there is at least one district who was was underperforming in the coverage. Here in Tanzania we have an example of MR one coverage, where we can also see, you know whether where there's increased coverage in the blue, and then low coverage in the areas around where we have increased coverage which which may be an indicator that the the people from those areas are going into, for example, kbt to get there to get their vaccines. So interesting example from South Africa, where they were exploring the population data and in an area which they thought they knew fairly well. And you can see this is a very remote area you don't see a lot, you don't see roads or anything. And they actually did find populations in that area that they said when they went home they're going to need to explore that because they've never actually gone out there. This is an example of the population data in an urban area. Also an example from South Africa, where they were looking at the TB rates and they looked at the population under five years of age, and just kind of looked at that together in the urban area. We've already had a follow up from Zambia. They wrote into the community of practice, I think, which which is great that they have been showing the districts how to use the maps app to understand performance within their districts. So here we can see them in the district office. And one of the people that attended the maps Academy just kind of passing on that knowledge and using the maps app. What's next, come to the session by Nora tomorrow afternoon. And we can discuss this further. Please also join the maps community of practice on the DHS to community. And here you can upload your maps, or if you have questions on making maps, it doesn't just have to be on DHS to it can be in QGIS as well. If it's kind of routine data related. Then please do join that. There is also a maps a really great maps app Moodle course developed by his South Africa, which you can sign up to and do in one or two hours, and it will really show you the features that are available. If you would like to sign up to that, you'll get a certificate. Please contact Nora Nora. I think most people know you but maybe you can wave or stand up really quickly. Please contact Nora and she'll make sure that she can get you signed up. There's more to come so we'll have some more e learning Moodle's videos and jobs aids. And since the health facility locations are so important to a lot of the maps that we see that are being made and requested. There'll also be a health facility coordinate checker. That's coming. That's it for me. Thank you. Okay, so that was the that's all the presentation we had just one thing I wanted to emphasize about the last presentation was a lot of times people ask us how do we come up with the features that we put into DHS to sometimes it's very opaque process. You know, it's not this is not the Willy Wonka chocolate factory where we just kind of dream up our own movie book reference that maybe not everybody gets. But anyways, the point is that I hope you noticed from the presentation how we actually tried to convene a workshop to understand where the barriers were and to then immediately bring those barriers back into new functionality. It's one of what we try to do for all of the apps and everything we develop in DHS we don't know we don't just dream it up. There has to be a real need. There has to be an actual implementation. And we don't actually even have the resources there to do like cool fun things that we think would just be interesting. There has to be a use case there has to be someone specifically asking for it. I need this functionality because I need to use DHS to in this way. So, so if you're hopefully that gives you a little bit of insight, and if you'd like to be more involved engaged in the say the development of the maps up and giving us requirements. We're the folks to talk to we can bring you into the community practice where we have a continuous dialogue about the latest functionality and things that you think need to be there and what other folks are using the maps out for. And so we're very happy to invite anyone and everyone here to join that community. And if you go on to the community practice community dot DHS to org, there is under the implementation thread a link just for the maps community. So please join that and and we'll we'll have we'll keep the conversation going. Now somehow by the grace of God we've ended early. And that think that gives us a very unique opportunity to have questions. So, yeah, sorry, we should have warned you max is max. So we we cover the new functionality, we covered capacity building and we covered some examples. Does anyone have any questions. Raise your hand. Someone's got to break the ice. Yeah. Oh, sorry, Joseph, right here. You're probably going to reference a bug that we haven't fixed it or something. Yeah, thank you, Joseph from La we. Yeah, it's a great new development. Thanks to the GIS. I think the key thing is about the whole data source and how we are going to manage the shape file and all the metadata. So I don't know, do we have some somewhere that like a global repository where we can easily access all sort of like population and even with the climbing weather data, and then that we can further use it. And also, like from the country's perspective, like we also generate the local, the local maps and the local data, like the health facility we have our master health facility registry. So how, how we can sort of like creating the synergy and not only within the country, but maybe within the region and also the continent and even worldwide, so that people can benefit out of this. Thank you. It's a tricky question. There are various resources to finding good, good data. Speaker. So, there is a site called garden g a g a d m, which have boundaries. I would also advise you to come to the will be more specific about resources. We will be more specific about resources when we have the meeting tomorrow to finding the shapes file for example. I would also say that this process of getting new boundary data into the issues to has been quite complex. If you have ever dealt with it in 339 is much easier. So we have improved that workflow. So I see some happy, happy faces here. Maybe if I can add to that as well. So there are various global repositories. Geo boundaries is a really good one. It has got them data in it. But here you can compare boundaries from different resources and a different administrative levels. Compare them directly to see which ones match your country best. We have the grid three website which has settlement extends for all countries you have hot OSM for health facilities. What I can do on the maps community of practice I can maybe add some of the global repositories that we would recommend for you to have a look at. Also remember that if they are global repositories they may not match the national data that you might get from your health facility master list or from your ministry of lands in terms of boundaries. So that's just something to keep in mind when using the global data sets, but there is a lot available. Yeah. And one thing is that as part of this collaboration, we have been working with a number of different countries to create what we call bespoke model population data sets. And there are also other layers of interest, for example, like the roads that are not available in Google Earth Engine you may have your local data. So I do think that that is still something that we need to sort out is how we can make available and some kind of repository, some of this data so that you can use the data from that you would prefer from your countries for example if you want different data than the one made globally consistently available through world pop. So again something that we would like to explore in the near future, working with DHS to team and others. And also something we will cover in the session tomorrow. So it's at two o'clock. It's in the technical track don't be afraid that it's too technical. It's basically more how to learn about maps than actually learning to complex yes and tools. So don't be frightened for joining. Thank you. My name is Lawrence Frank Nhambalo from Malawi. I'm from the expanded program immunization. I was interested when I heard about micro planning. And I just want to compliment on what my colleague has actually said again on the same. We are so much interested in access and utilization. So I was also considering to say on the geospatial tracking system where much we are using again geospatial micro planning to say, don't you see that also as a need to say, maybe if you might also bring in a system, the GTS where you'd be able to actually track to look at maybe the vaccinators as they're trying to reach out to them, the children, maybe you've already done your micro planning and then you have to find out to say, who the vaccinator be able to try to reach out so that we really work again on the utilization and of course accessibility. So I don't know on your micro planning geospatial micro planning. How do you plan to get to those levels where you have to also consider the geospatial data. I don't know. Don't you see that as a need in the near future. Thank you. Yeah, it's, it's, it's a good question. Thank you for that. I'm not sure how far the tracker app can be used, like the, the GTS I know the GTS has a has a dashboard that can be used and that shows you how to track. And it uses some of like, I think it uses the settlement extents as well. I know you where you've been in areas you've covered. You can obviously use that data and bring it into QGIS and then take data from from the DHS to and then also add that to QGIS so that is possible now. In terms of linking the GTS with DHS to maybe that's something to ask for. That's good feedback. And, and we have been looked more into aggregate data than to individual based data. So far, I think there is a track entity layer also in Maps app, but it should be really get some more love and focus. So there are possibilities and people are using it and you have the, the, the, the app where you can capture coordinates even multiple coordinates. For the, for some like contact tracing and so on, but it's still limited. So I think often still you depend on, on moving into another system to, to do, to do this analysis. Would you like to add some. Yeah, just to point out that planning and micro planning is one of our. Uh oh. Be careful with your toes. Justin. I think there's quite a few doctors in the room. We needed. Okay. So what I was going to say was that micro planning is a key use case for us. Specifically, we are really analyzing the functionalities that are required to be able to conduct micro planning all the way down to health facility community level in countries and making sure that DHS to has all of the necessary functionality. It's a process. And there's different ways that there are different types of micro planning. So you have different plans for like immunization may also have different kinds of micro planning approaches for other types of outreach services like, like, insecticide net distribution or maternal follow up, etc. So we are part of a global community that's analyzing digital tools for micro planning. And, and if your country is going to do any micro planning and considering to using DHS to for it. Please keep, please talk to us. Tell us what you need, what you have what you don't have, and then we can kind of go through the process together. So what is the use case that we're, we're aiming to cover. I do want to mention two examples that we have presented earlier. This one's from Uganda. And if you remember, and Uganda is actually able to use this map to inform micro planning. They have micro planning coming up and they have used DHS to for micro planning in the past I think some of the Ugandan's in the room to probably prosper certainly could elaborate more on that. The point is that with these maps you're able to see where people live. Right. And you can see that quite quickly, this is quite zoomed out but if you can zoom in, and you can see where the actual structures and buildings are where people live. And obviously that's a critically important part, you can also see where the health facilities are. And so you can very easily just like they did and which one is Ethiopia here. You can see all of those populations that are quite far away from health facilities, you know 10 kilometers. And we know that that is a barrier to access that distance. And with these maps, I mean it makes it as obvious as you can possibly get it. Certainly. The other one here that was from this too. It's also extremely interesting because you can see the health facilities those are the big dots, right. And you can see the catchments, and you can see that some of these catchments are gigantic. And when when they were presenting it, they told us we didn't even know people lived here. You know, it's so rural, it's so remote. And now we know we have to go do campaign planning or we have to do outreach to those those places because there's clearly people there. And it wasn't something that they had an insight into until they built those layers on top of each other started with the base layer, added the building footprints at the population, and then it's clear that the that it's there. Yeah, maybe we can. Okay, so now we've we've managed to fill the time but you know, we live here so come find us. And we have a session tomorrow as well. Okay, so the break. I think the brakes at 10. Well, sorry. No, we still you still have to sit here. Well, we can answer some questions off as area. Sorry, breaks at 10. This communication there's a question here in the middle. Okay. Well, maybe, and then we can come back to Malawi. Yeah, sorry. Here's the room come back to you. Oh, sorry. So I find interesting. Otherwise, I just want to compliment our little on what I actually said. So I was looking at a problem at hand here. Because you'd see if you get into the choice to generally in terms of coverage is generally it's a problem because each time maybe like I would cite our scenario that maybe we want to come up with in campaign. So the times we want to get the data. That's when we're coming up with the micro planning. We have to get data from the districts. In this case we want to get them. We want them to provide us with the national statistical figures and the head counts right now with the special micro planning in my thinking I was thinking that if they just to be to provide us with this approach, it means issues to do with coverage is not their problem because in this case will not have all these headaches that come in when we are trying to reconcile the figures. There are times people would say no, maybe we want to use the NSO figures the national statistical figures and the head count figures so these don't do not actually reconcile. And then you will see that we want to calculate the coverage is now that even us as we are working with the coverage is actually tough because at times we need to sit down and say okay, can we work on the proportions and then come up with these coverages and you'd see that some districts do not even manage to reach out to those coverages because they just don't use on doesn't provide coverages we have to calculate separately we're going to preparation. The proportions and then people give feedback source of the concern of the missed opportunity for vaccination in comes to children. Most of the children are actually missed. It's either we underpopulate or we overpopulate and then these proportions are not always realistic. The week on assumptions would say okay, if we are to assign to district by district, how do we ensure that we are really giving real figures. I was thinking that maybe if we, we may adopt the geospatial micro planning is going to be easy will not have issues to do with coverage is because be able to actually track the children that are really supposed to be tracked according to the populations that were able to actually generate. So I was thinking that if we might come in with the idea of geospatial analysis in this case is going to be easy because it will be direct. It will not be these two way where the office has to ask for data. That's the cow. I mean the population figures. These two, the national statistical figures and at the same time, the head count figures. So to populate these maybe to reconcile is always an issue. So I was thinking that maybe if we can have that system in the ice to it's going to be easy and the gts thing. We hope us to actually reach out to the gap that we still feel it's always there over time because we don't have those realistic figures we make on assumptions over time and we really don't speak what happens really on the ground over so I thought maybe we can still talk a little on the same. Thank you. The sad reality is that I've never worked in a country that wasn't struggling with their population. Most countries are struggling with this. And I think the important thing to appreciate is with the maps you can see where people live. Now this world pop data is a projection. This is not a head, it's not a head count. Right. It's a model. So it's not necessarily exactly what you see it's also from 2020 and as you pointed out they are updating it and even providing some new projections, but it is not your national statistics necessarily. But it is a really good place to start and we and it makes it very easy now to use it in the maps out. But we haven't we have actually done a series of webinars on different approaches and methodologies to available. We've done it on our YouTube channel but I'm happy to show you some links but there are and it's certainly some of the WHO colleagues here have a lot of experience in this as well. So, if you're struggling with coverage indicators just know that everybody else in the room probably is to, and then there are different methodologies to to use to calculate them. And then of course the maps app can be a, you know, when you put on the building footprints layer, it's kind of hard to argue with it. Because it's just, you see where all the buildings are. It's very, very clear. So it makes it quite easy. Yeah, maybe also just to add on, I think one of the things that we're seeing a lot of is how important the actual boundary of the catchment area is when you're trying to reach people. Sometimes the facilities have hand drawn maps. So, and when we asked them to digitize that we see a lot of gaps and overlaps and what the facility perceives is their catchment area. So when they say this is my facility headcount or my catchment area, they may be under over estimating what is in their their catchment boundary, just because it's never been properly mapped. So you're starting with just properly mapping the catchment area, and you can use a tool like cross cut to get kind of a first iteration of that and then sit with the facilities to make sure they are happy with that. That can go a long way. And then you can use your census population to see, maybe it does actually add up. It's just that the boundary was wrong. However, you can, you can sit with your facility and then go through that again use settlement extends that you can write populations to and then look at that. Look at the population again, but the actual boundaries around your catchment area are really, really important to make sure you get the right population. So that's an issue that we've seen, maybe just to add, in some countries, we've done extensive micro planet maps, where we've put three different populations. We've put the one from the statistics office, a bottom up model which uses a more detailed data, like from a census cartography, and the facility headcount data and then the facilities could choose what they felt was the most accurate. So countries are requesting that as well. Hi, my name is Lily signs I work on the PMI vector link project. And on our project we collect quite a lot of entomology data. And there's a lot of interest in being able to map our entomology indicators like vector density and vector composition, along with climate data. And mostly, that is, you know, looking at monthly changes to climate data at the district level with our entomology indicators. So far we've noticed that the climate layers, we're seeing a lot of data at the weekly level, and their differences in what that time period is based on the source of the climate data that's coming through. So we're just wondering if there's any possible or expected functionality of kind of aggregating climate data at different time periods or flexibility in in those time periods that are available within maps. So, um, sorry, I need to, I need help on this one. The answer is, yes, it's something that we're taking we're looking very much into having more granular climate data but maybe, Kristen. So, we have, we have an own session on climate health tomorrow. Actually, so so please join that one. We have several initiatives around in the countries, and there is a growing demand for combining climate data with health data to be able to predict prevent understand the impact of climate on health issues. We are in the process. I mean, we could say that I think it's not a secret. We are in the process of we actually just handed in and proposal for welcome trust on a big project eight years project with the 12 PhD students involving many countries on the climate health. So we hope we will start a big initiative, but we don't know yet it will be decided during summer so across all the fingers, but we really believe anyway, even though we're not getting those funds, we believe that that's a growing demand and it's very important to address issues and weather data, climate data, meteorological data for the first impact on and we know already we have done it on malaria, dengue and nutrition. We know already there, there's evidence, but we will encourage people in countries to take contact with climate communities at the universities at meteorological stations to start the discussion to see how can we combine data from various sectors in order to to solve or to at least dress social challenges such as climate health. So this is a kind of a call for action, and we will have some examples in the primary on Thursday when we are talking about cross sector monitoring. So there will be examples and we actually have a session at three o'clock today, monitoring progress progress across sectors in auditorium one where we actually look at the histories to see how we can combine data analytics across sectors, and many of these indicators are climate relevant indicators. So yes, this is a very much an up and coming topic for for us. Maybe I could just add one thing about that specific question. I worked fairly extensively on a proposal on climate health and the issue of granularity and matching geographical scale comes up in every climate health use case. And the way to address that is by creating customized climate services for use case which we're planning to work with a few new partners in the climate sciences demand to do. There will probably be a combination of local climate data were available globally modeled climate data, but designed to match a given health use case where we have discussed that with a few different climate partners that we're hoping to join us the welcome project, and once those become available to the extent of those can be made generic and made available for different countries in different contexts that's obviously the goal as many DHS to product product. As suggested, I definitely recommend getting in touch with us, because the first step of that if we do receive the approval for project proposal will be selecting countries and use cases to work with and trying to move forward and develop some viable systems. And if there are any knowledge about where ministries are sharing data, we are very interested to kind of leverage upon that to see what can we do in order to show. Or, as I usually say create hope, show examples where we actually can do see the benefit from from matching data from local weather data with climb local health data, because for in on satellites that has been available for quite a while. It's the same as with maps. The more the lower you go in your, you know, in the locality the more relevant they are. So, so we need to think about that in when it comes to climate as well. I would also advise you to have a look at the Google Earth engine just Google it and see the data repository it's a vast, vast resource and that's climate changes a big issue for them as well. And they are constantly adding new data layers. So, but it's if someone you could have a look if you're working within the field and see if there are more data sets that we could also add to the DHS to instance to the maps up. So please have a look and and give us feedback. I think we have time for one more question before the break. This side of the room seems to be a bit more tired than this side of the room. Are there any questions over here. Yeah, of course George always. Thank you very much. So I have one comment and one question. So the organic profile is really spectacular. I've come across it recently. It's impressed me what from beyond said is that I realized that you could have like the data table at the bottom of the map. But you were just clicking around with the filters and I realized that you could actually use it for real time analysis. That's really interesting because now I realized that instead of having to create 567 different maps like, you know, all the zeros or the ones you can actually just have one map and give an explanation to dynamically use it like on the fly. Yes, that's great. And the stupid question is, how do I edit the work unit profile. Currently, because this is a one time job, we have not prioritized to make this into a nice unit. And an API, you need to set it's fairly well described, sending a request to this API and it's done as a one time job and it will keep and it will be there. So this one basically selects which sort of elements and data attributes or you need groups, what kind of indicators and data elements you want to see. But I see we will, I will take a second round of getting a user interface for this as well. Yeah, yeah. Yeah, we pointing out an API link is Okay, we're still we're still just a few more minutes away from T. Any other questions last question. No, silence is acceptance. Okay. One thing I just want because this was this been a great process this last half year. Having a workshop in Nairobi and then leading up to the Academy at the same time working on the maps up trying to improve features. So I just want to specially thank Sylvia and Maria from UNICEF and also Nora from his South Africa for organizing the Academy which was a lot of work. It's super useful also for us as developers and also people sitting in Oslo, come out in the field, learn about the use cases, see how this is used. We were 2014, this weren't his group represented on this, and it is super useful. And sometimes someone from the outside needs to come and bring us together. So I'm very thankful that you did this job. I hope this, we will continue this great cooperation for the future as well. Thank you.