 evening and enjoyed the city tour yesterday. So this morning we're going to get started with our final round of sessions. I know a lot of you have some plans for later on in the day it's the last day of the conference so we'll try to kind of move through the content and explain everything as we can and allow you to have some time to enjoy the city and the atmosphere here in Sri Lanka. So in today's sessions in the morning we're going to start off with Austin speaking about maps and then after Austin we have Morton from the integration team and he'll speak generally about interoperability principles. After the tea break then we'll have the country presentations once again and then after lunch we'll have some parallel sessions and I'll make sure to explain the makeup of those before lunchtime so you know where to go. All right so I'm going to invite Austin up and he's going to give you a bit of a background on the different features for maps and DHS too. Thank you Shorjit. Good morning everybody. Who was happy that it didn't rain last night or at least not until later. Okay so we're going to talk a little bit about maps today and if you if you didn't think there were enough pretty pictures in my presentation on Wednesday you're in luck because there will be a lot more pretty pictures and even moving pictures today so hopefully you're excited about that. But before we get into this I actually have a QR code here on the screen. I'll show it a few more times through the presentation so you can whenever you have a moment go ahead and open that up. I'll open it separately at the end as well if you don't have a chance to do it now. But basically this is a bentimeter just a pole to see how you're using maps today how you think about maps and we'll we'll talk a little bit more about that. My goal for this presentation is to make you excited about using maps really like interested in finding out what you can do with them and to yeah and also to convince you to come to the session this afternoon to talk more about it with me. But before we get into maps and again I'll show that QR code again so don't worry if you don't see it and I just want to make sure that I have a timer so that I don't thank you. Okay so before we get into the the section on maps I wanted to talk a little bit about continuous release so I mentioned continuous release on Wednesday it's a new way that we release applications and that is separate from the core. So we have the once a year core release that has all of DHS2 we also release applications independently and I just wanted to give a very concrete example of why that is useful and how that is helping us to better serve all of you. So earlier this week I was talking to some of my colleagues from the Hisp MENA team who had an issue in the line listing application with if you had the same codes in two different option sets sometimes the the labels would get mixed up and so I we created a Jira issue I relayed that to the analytics team who then fixed it and released a new version of the line listing application. So now that version of the line listing application was released yesterday it supports 238, 239 and 240 so if you're running any of those versions you can download that new version and you have that fix immediately available. So that was something that we we talked about earlier this week three four days later it's fixed and everyone can download it and use it. So this is available on the app hub and on the app management app within your DHS2 instance it's available to everyone this is just one of the many applications that we do continuous release on. Just wanted to point that out I think it's it's really shows the the power of this this flexibility because we're not even though we have a one-year release cycle we can turn things around in a week and get fixes to everyone and also you can update your application without risk to lots of downtime for your server those types of things. So Mohammed is happy. Okay so now now what you all came to see which is the the moving pictures that we'll get into. I want to first give a lot of credit to Bjorn Sandvik who is has been building a lot of the features that you'll see today also created most of these slides and I'm just the messenger so he is the he is the maps expert and what's about a time I was I was working with him on on building some of these features as well and so really really thanks to him for for a lot of this but as we go through this presentation I'd like you to think about a few things. So think about how do you how would you use these new features in the maps application I'm not going to just talk about ones that are new in version 240 as well we have versions all the way back to 231 new features so just talking about features that are in the maps application that maybe people don't know about maybe people haven't really recognized what the the real power of those features are so we'll talk about a lot of those and I want you to think about how you might use them why maybe you are not using maps as much as you could because I know that it is something that's often underutilized for a number of different reasons so think about why that might be for for your particular country and how are people already using maps in your country and in other countries as well so that's something that we'll try to do this afternoon in the interactive session is actually go around and have everyone talk about how they're using maps or how they're using JS and how they think they might be able to use it in the future as well and and then how can you how can you kind of be inspired and inspire others to use maps and JS in new and innovative ways to better analyze and improve health systems of other systems as well okay so the the main message here is that maps is easy to use it's intimidating sometimes because you you think that there's a lot that you can do with maps but the the main goal of the maps application in DHS2 is not to be not to do everything that you can do with GIS or maps there are many many tools that can do that for you that can are very sophisticated maybe you need even a degree in GIS to use those tools that's not what the maps application in DHS2 is about it's about giving people access to information in a way that is easier to understand easy to use and it gives you an idea of how things are spread out in space in addition to in time so that makes it a little bit easier to to parse and to understand and to present this information than it might be on a on a chart sometimes or in a table and with that this is a 15 second video showing how you create a map that's how easy it is so you just click the add layer button you select the indicator that you want to you to add this in this case we're adding a thematic layer and then it's done so that is how you create a and this is actually doing something you don't need to do where you can change the base map so you have some some different base maps that are available you can add new ones as well in the maintenance application but this is how easy it is to create a basic map map obviously there's a lot of other things that you can do as well but that if you have an indicator and you just want to see it in space and you've collected data for that the the data elements that feed into that indicator you can just put it into the maps application and very quickly show it so here are the features we'll talk about today the yeah as you can see it goes all the way back to version 231 so there are some features that we're introducing 231 that maybe people aren't aware of or that we're they're not using as much as they could could be and we have a lot of other new features that have been added since then and and we'll go through each of these and show how they can be used why they're useful and and talk a little bit about them so first we'll start at the start at the end so we're going to start with version 240 and this is a functionality for basically making a very presentable printable map so you can basically lay out the map the legend the overview some descriptive text put value labels so it actually shows the value that you see there not just the name which you could see before it's a very clean thing that you can print on a piece of paper that you can print as a pdf and it really makes it easy to tell a story with your map and to show that to someone who maybe didn't create the map doesn't doesn't use maps every day they can you really want to tell them a story so that they can understand it very easily so this is just an example of what that looks like at the end how you you've designed this in the interface that I just showed and now you want to print it you print it this is something that you can you can tell what's going on here even if you're not a maps expert right so you have some text that describes exactly what you're seeing you have a legend that very clearly says what each of the colors means you have the the different org units laid out on the map and you have the values displayed there also wanted to talk a little bit about different ways to display aggregate data our aggregate analytics in the maps application and we've had chloropleth for a very long time and we now also support since version 235 bubble maps and these are useful in different situations and it's important again when you're telling a story to think about what type of visualization you want to use what type of map layer you might want to use to tell that story best the one on the left here is best used for indicators where you have basically normalized information so if you're dividing if you have an indicator where you have the number of cases of COVID-19 divided by the population then you probably want that to be a chloropleth where you're it's the same basically the it's easy to compare between one and one region and the other if you have just the number of COVID-19 cases for example that's a raw number in wherever your capital city is will probably look very very bad it will look like there is a huge amount of COVID-19 there but per population it might not be that high so there you have the option of using a bubble map which is for raw values so this will just show you relatively how where where the cases are located and you're just looking at raw numbers or data elements in most cases both of these are supported and you can tell the maps application which one you want to use so we talked about maps being very useful for displaying information in space so you're you're actually seeing how different regions in your country are are performing or or the seeing the data spread out over that over that space but it can also display information over time so this is showing the timeline map functionality that we have which lets you see from one month to the next over the course of a whole year what the different values were in these different regions and this one's a little bit hard to hard to read because it's when when you see maybe august it's hard to remember what June or May were were looking like but if you have maybe a single district or something and you want to see the the change over time and see it kind of as a movie or as an animation that can be very valuable but sometimes you want to actually just compare one month to the other month and so there we also have the split view functionality in the maps application which lets you put all of the different periods that you want to compare in basically on the screen at the same time so this is multiple months throughout the year displayed with the the values available so now you can compare your February with your January and this is a much easier way to sort of see see progress over time to see maybe if there's if there's degradation in performance over time and the the downside of course there is that these are these are smaller maps so you can't show as quite as much detailed information as you might in the timeline view for example and both of these the split view and the timeline maps are both available from 233 so every almost everyone here should be on a version that supports these also wanted to talk about styled by data element which is from 231 and this is a really powerful way to display information about events so a lot of times you have events maybe you have a hundred thousand events and you put them on a map and you just see a hundred thousand black dots and that's that's not super useful right or it can be useful if that's what you want to see but maybe you want to see something different like you want to see the the age or the yeah the the status of the the patient that was referred to by this event and so we have the ability to customize the the color of those points and to use values that were collected data values that were collected in that event to change the color of each of those points on the map this means that you can say as you see here on the left you have the mode of discharge as the as the legend and it will automatically take each of these points and it will adapt it so that it has the color of the mode of discharge of that particular event we also have the ability since 235 to show this information in a table within the map itself and you can then filter this table as well but you can see the the the value you can see much more detail about these individual events there's also this is also supported for the other layers it was only added for events in 235 but other layers were added before that but this allows you to to quickly kind of drill down and identify individual cases to identify something that you want to highlight on your map and then to get more information about that if you have a lot of events then the colors might not make a lot of sense it'll look kind of like a rainbow with a with a lot of little little speckles all over the place so we have the ability to do clustering which will dynamically group the events together and you can still see the colors for those that style by data element in this example so you can see the uh yeah green yellow and blue for example and it'll say that there are two events one of them is is orange and one of them is blue it'll show that in in what's called a donut cluster uh so this is also available if you have large number of events to be able to to at a glance visualize how many in this part of the country how many were discharged in this way and in this part of the country how many were discharged in a different way this one is really exciting and we actually uh I heard from someone uh Bangladesh I believe was was interested in this functionality um this is actually available from 238 it's something that maybe some people aren't completely aware of but it's it's a really powerful feature where for an org unit in your system you can have not only the the geometry or the the point or the the the boundaries of a district but you can have additional geometries as well that are associated with that point so the the common this is called associated geometry is the the name of the generic feature but a very common way to use that is to define catchment areas for facilities so in addition to a point which tells you exactly where that facility is located you can actually assign a a region or an area as doesn't have to be just a square or a circle um it it can be a a dynamic region around that facility and then you can use that to say all right these are the people that are served by this health facility for example um and the this allows you to associate that geometry with that org unit and then you can do a lot of things with that uh newly associated geometry or those catchment areas and I'll talk a little bit more about that as well uh there's also an application from an organization called crosscut so this is developed by someone that is uh it's on the app hub it's not developed by uio but it's available to everyone um and that allows you to automatically generate these catchment areas which is a very powerful feature as well it's it's a quite a complex task to be able to generate catchment areas based on driving time or or travel travel time and also based on uh geography so things like rivers and mountains that might be in the way of someone getting to a facility so this will allow you to dynamically split up your district based on where you have the points of your facilities so that you have coverage of that entire district split up between the different facilities in that district and you can actually have multiple org unit associated geometries and so there's a lot more powerful things that you can do here I wanted to talk also about uh yeah so this is still catchment area support but a little bit about what you can do with that first of all this is a um a thematic map so you can do any anything that you would normally see a point for a facility you can then apply that to the catchment area for that facility so instead of seeing just a bunch of dots for the the values at each facility here you're you're applying it to the catchment area the associated geometry for that facility which lets it makes it a little bit easier to read that's a that's a very simple advantage there and there's also an example on the right here where you can zoom in and turn on aerial imagery which is like planes flying over basically and you can see very detailed information about the the houses or the the buildings the roads that are in a particular area and you can actually evaluate the the catchment borders and then go back and edit them if they're not exactly right so you can use this this tool as well to kind of validate the catchment areas that were maybe generated by the cross cut application and we'll talk a little bit about uh that that functionality is called ground true thing so basically you you're doing something in the in the sky and you're trying to figure out if it actually matches what's on the ground to make sure that it actually lines up with with the reality and we'll talk a little bit about also calculating population so being able to define those those dynamic catchment areas around a facility and be able to calculate how many how many population how many people is this facility serving we'll talk about that in a minute and to get to that we'll talk about google earth engine so if you were in the climate and health presentation or a breakout session yesterday uh john kind of gave this presentation already but uh hopefully well it's it's still interesting to those of you who weren't there um and this is a a layer type that's been around since 236 for dhs2 and it's really really powerful google earth engine can do a lot of different things and we'll talk about what exactly it can do and also what we're going to continue to uh enhance dhs2 to support additional layer types from google earth engine but this can uh basically let you show things like population like building footprints like precipitation or rain land cover is really important as well um it can you can do all of these things and you can for free go and add these layers and and show your information in your dhs2 instance along with this very sophisticated detailed information coming from google earth um and it used to be a little bit complicated to sign up for this so you had to actually go and talk to google directly uh and then you would get access to to the google earth engine api at some point we've made it much much simpler you just go you can go to this url you can send an email to maps at dhs2.org uh and we'll sign up for you basically it's free of charge for any country government to to set up uh this uh system and it adds a ton of power to the maps application dhs2 there's also other things that you can do with it that are very cool so you'll we'll share these um slides as well so you can follow that link and it'll give you instructions for how to sign up for google earth engine to get access to this incredibly rich uh set of data that's available so what exactly happens when we're talking about google earth engine um and so if you if we look uh we'll yeah we'll see we'll see an example of this in a minute um but if you add for example the population layer for um google earth engine um and you might be uh elevation layer there's a lot of different um layers that you might be able to use what actually happens in that case so you have some district boundaries in your system that are defined in dhs2 google doesn't know about those right google knows maybe about some political boundaries maybe about the national border but not not necessarily about anything else below that but you want to actually calculate the the population within a catchment area for a facility or the population within a district so you can uh what what this will do automatically so as soon as you add that layer it can send the the organization unit boundaries to google and then use google's processing so google earth engine is not just a repository for data it's also free processing capability in the cloud to be able to do a lot of very sophisticated modeling and very sophisticated uh processing of your data um so this is in this case you're not actually sending any data or anything uh too sensitive to google earth engine you're just sending the borders of the district or the catchment areas for example and then it will calculate in detail using the um the the information that comes from another organization called world pop that will talk about what what how that how that is world population is calculated um but that has very fine grained granular uh population data at each point in the world and it will then add up all of those points within the org unit boundary and give you an estimate for the population for that particular uh organization unit um and then it can also be brought back into the maps application you can also import it if you want to use it for calculations if you'd like to supplement maybe the population data that you already have in your system um it uses a lot of um data sources for google earth engine this is just an example for um the uh yeah for population um world pop is uh you can also use uh lots of data coming in from nasa from satellite information uh from information about climate and we'll talk more about the layers that are available there as well so this is an example with elevation so you can actually um aggregate the elevation within an organization unit and say what is the what is the maximum the minimum and the average uh popular elevation um and you can define exactly what uh values you want to want to know um that are within this particular district um you can also zoom in and click on the map and see the the elevation at a at a specific point so this is displaying the elevation in uh yellow to red um scale uh so you zoom in on the right side there you can click on that red point and you can actually see all right this is this is the elevation of this this high point in this particular district and so that can be quite useful for a number of reasons both to just visualize kind of where are the where are the mountains in my country and there are very many mountains in Sierra Leone um but you know in a lot of other countries there there are bigger mountains than that um but it can also be very useful for for example um malaria risk mapping so malaria is um typically only found below a certain elevation um so if you want to know where where is there risk of malaria in my country um you can actually use this to to estimate that so you can define the uh the the values that you want to see where you want to how you want to sort of split up the elevations within the the country uh in this case again it's Sierra Leone which is not a very high country so there's no malaria risk but you could set the the minimum and the maximum uh and then the steps so you can see where exactly you're above uh 1,700 meters for example and there and there there should be no malaria risk um from uh I think we have some colleagues from from Bhutan here um in a workshop in 2019 Bjorn and myself were in Delhi in India and presented a a maps academy to training on on maps and using a use of GIS um and Bjorn created this this map which is actually using QGIS I'll talk more about that which is a um can do even more sophisticated and advanced processing within DHS2 or then then you can do within DHS2 but this is showing in the country of of Bhutan um where the uh elevation is above and below 1,700 meters so where you where you should estimate that there is a risk of malaria um and you can see in this case that there are something like four or five uh districts where there there probably is is is no risk because it's it's so high so there that's somewhere where you don't need to target your malaria and interventions for example another layer that's available from Google Earth Engine is land cover which can be quite useful also for for malaria but for a lot a lot of other things as well especially when we're talking about climate impacts on human health um so this is showing you what what is the land used for is it urban is it agriculture is it forest uh what what type of land is is is in each of these places and then you can again similar to elevation you can dive in and and click on a specific point and figure out more about that that particular uh area the population data that we're seeing here in in the Google Earth Engine comes from uh an organization called WorldPop uh and we'll talk there's there's a number of resources online where you can find out more about how they calculate population um so we'll talk but we'll talk briefly about that as well so this this is an example of the population the granularity of the population that you can uh access through Google Earth Engine with which comes data comes from WorldPop and what it's actually doing under the hood is it's taking a ton of different information from satellites from building footprints from census data um and it's creating a basically a grid 100 meters by 100 meters for the entire world uh particularly for for for the country that you're you're you're interested in and it's saying all right in this 100 meter by 100 meter square it's approximately 60 people 68 people yeah 60 people um that are living in that 100 meter by 100 meter square um and and maybe there's zero people in another 100 meter by 100 meter square and maybe there's 125 in one that's particularly populated um this is not exactly it's not going to be exactly accurate for that one point that 100 meter by 100 meter square but if you add all of those up for a district it can be quite accurate and there's uh there's actually a lot of documentation of of how accurate that that really is in practice and importantly this also uh um the sum of all of these points will add up to your census data so it adds up to the the official value that you that you um uh your country is is publishing for the the census data for the for the entire country um and that helps to basically like get more granular than it is easy to do with census data which is at the high level uh but be able to do micro planning and and very detailed um health uh intervention targeting at the lower level um so in this example you're you're adding up all of these squares of 100 meters by 100 meters that are within the catchment area for a facility and then you can get the estimate for the each of these facility catchment areas just by adding up that information so that's what google is doing for you because there's a lot of 100 meter by 100 meter squares in each of these catchment areas and a lot of complexity in how you calculate it but it will do a lot of that processing for you do all of that processing for you and give you just the the estimated total for a catchment area or a district or a region important to note that there there is some additional dimensionality to this information that you can use so you we have uh both sex and age age group for that population data in particular which can be quite useful if you're looking at elderly populations or population under five for example for for different programs and additionally it's currently based on population data from 2020 um which is uh yeah which which is useful but maybe you want something that's a little bit more current or maybe you want projections into the future uh and then the good news is that world pop is working on that so we should have estimates for from 2020 all the way to 2030 in the near future okay um so I talked a little bit about this already but this is basically applying that population layer to a particular district and then adding up all of the values within that district to give you the the estimate for the the total population which is in this case 24 000 in this this particular district here and similarly you can do that with uh the area around a facility I talked about catchment areas which are a little you have to do a little bit of work to to figure out what is the catchment area for each of my facilities because you have to think about driving time splitting up the district in a certain way but maybe at at a very basic you just want to say give me the the population within a five kilometer circle circle around this facility and so that's something that's very easy to do you have your facility data you just add a a population layer and say give me the the five kilometer radius around each of my facilities and add up what the population is there okay this is another very cool feature that um I think has been widely requested and maybe is is a little bit underutilized and and that is organization unit profiles so we have a lot of facilities out there and they they do different things right they have different services that they offer they have opening times they have uh you maybe you want to to have some some information about that facility um you can add that within dhs2 uh and you can then visualize it in the maps application um so this is something that can uh basically you click on a a facility or an org unit um and then you open up a profile that shows a bunch of information that's quite relevant to to to you and this is all defined by you in your system um and you can uh even have some dynamic uh data elements or indicators coming from the data values that are entered in your system as well this one I talked about on Wednesday uh but as we talked about the value of population data coming from Google Earth Engine for example we showed how you can see that on a map in the with the Google Earth Engine layer you can also import it into your dhs2 system as a data element so this means that you can have it in parallel with maybe maybe some other population data that you have but this will allow you to calculate or use the calculated data for the the catchment area population as a denominator and an indicator for example uh which can then be used on charts it can be used on maps obviously uh and many other things so this allows you to actually import um so this is the earth engine import that I'm talking about here this allows you to actually import data directly from Google Earth Engine and maybe you want to have a data element that shows the population disaggregated by age estimated in the catchment area around all of the facilities in your country it will do that for you uh we also have improved support for importing Oregon organization unit geometries we're moving to supporting Geo JSON uh and other uh improvements there as well GML which is uh an XML format is quite complex and there was a lot of manual editing that needed to be done uh so we're moving to Geo JSON which is a more modern format for being able to import and uh um uh define your organization unit geometries this is just the tip of the iceberg because as I mentioned DHS2 is is designed to be uh easy to use and for people that are not GIS experts but there are a lot of tools out there that and a lot of cool things that you can do with GIS if you are an expert or if you or if you are someone who wants to go a little bit further than what the maps app can do for you uh so you can export the data from the maps application and then import it into an application like QGIS which is a free and open source tool for doing advanced GIS um uh analysis as well as building of maps generating of new layers lots of things like that uh we saw an example from Bhutan of how you can use that to in in great detail calculate the um the elevation profile of a country um and there are many other things you can do with driving time calculations things like that as well um so just is just to say ArcGIS is another um uh commercial software that costs a little bit of money but it's very very powerful um that you can use as well you can export the data from DHS2 to Geo JSON directly from the maps application so there's a download data um capability when you have a layer on your map and then you can uh work with it in another program that you might be using for your advanced GIS calculations okay uh I have a little bit less than 10 minutes left I think if I if I add up the the time that before we started the clock so I I have this QR code again if you didn't get a chance to to follow it please uh do that now and then I'm going to talk about about kind of what's what's next what are some other things that we have coming for the maps application that you can look forward to I see some people taking pictures so I will stall for a moment show of hands who likes maps thank you oh I got two hands in the back nice okay so uh more earth engine layers so this is something uh as as we mentioned there's population land cover uh temperature rainfall lots of lots of layers currently supported for from google earth engine but there's a lot more there there's a ton of data that's available through this this platform that you can get access to uh that we want to make available and make it easily available to people just as we've done for the the layers that we have now so we'll be looking at adding the ability to uh define the uh the maps that you want available in your system so you're not you also don't want to overload the the end user maybe with too much information but be able to define all right these are the layers that I think are quite relevant and useful um they're they're available on on google earth engine let's just enable them uh so there'll be a an interface for doing that and then we're adding a bunch of new layers layer types from google earth engine um additional types of temperature and precipitation layers um the ability to have uh Copernicus land cover layers that's from a different type of satellite lots of different uh types of information that can be um very useful um in a lot of these programs we're also looking and this is this is all kind of uh demonstration of potential so it's not necessarily something that is done or that will look like this when when it gets released but this is really interesting information about climate that can be very relevant to health programs that you can get access to we're we're working on ways to get uh give access to it directly within the maps application in dhis too so in this case we're seeing the history and and we had the forecast as well of temperature and and weather at a particular point uh within uh dhs too um you can see the the history of precipitation um you can see the daily precipitation which can be quite useful for for dengue or malaria or a lot of other uh diseases that are dependent on that uh you can see the the the change in climate over time for example so there's a lot of things that we can start to do to bring in additional information to make it a a richer experience for the user of the maps application uh well without overwhelming them with too much uh data as well and just a brief um talking about kind of what what that involves to to bring that information in um this is again just an example but you're bringing in information from local weather stations from global data sets like um satellite data uh using processing and data sets from for example google earth engine but others as well um a lot of other organizations that are helping to kind of do the modeling and the processing of this data um and to bring that into dhs too to make it available to people okay um this i'm just going to go through this very quickly because we can we can dive into it more this afternoon if we want and i don't have a ton of time um but i just as some inspiration for kind of what you can do with maps um so you can think about what you can do in your countries maybe you can share this afternoon what you already are doing in your countries or what you think would be useful um but here are some examples of uh from an academy that we held in South Africa for um the yeah the use of maps in dhs too um showing an example of uh different maps built by the teams that were uh attending there i'm not going to go into too much detail because actually the exercise for this this afternoon um first we're going to ask everyone to share and talk about kind of what what they're doing with maps in their countries what they think could be could be useful uh use of the the tools there but then we're going to look at these maps and see can you without without me telling you can you understand what this what story this is telling and and what uh what is what it actually is is saying with the data there so there's a number of different examples from different countries this is the sutu for example of data displayed on maps and how that can be used for for action in a health program for example again i'm just going to go through these uh quickly so you can see some of the maps that were created um you can obviously print these and and use them for for planning you can use them to identify unreached populations for example you can use them to identify places that are at high risk of emergent diseases lots of those types of things and with that i think that is it for my presentation today i'm not sure how much time i have left nope almost perfect two minutes left so if anybody has any burning questions you can ask them now um we also have a maps community uh the qr code is there again if you haven't had a chance to fill that out yet i'll open that up in just a moment and we have a a map section on the community of practice community the dhs2.org we'll share this um these slides so you can follow that link but community.dhs2.org is where you'll find that and there'll be a lot of more um content and and uh trainings and and academies and things like that coming soon as well for the use of maps with that i will open up just quickly this mentimeter so we had uh people um describing what uh what maps support in dhs2 means to them um enough to support needs that's good data visualization yeah lots of lots of good things here please continue to fill these out because it's it's useful information for us um we also have which versions of dhs2 are you running so that's very useful as we saw the the different versions of dhs2 and the the features that were supported there um interesting to see that so you have a number of 240s and 338s um no questions yet on what would you like to know about the mapping dhs2 mapping functionality so feel free to add this and we'll talk about it in the parallel session later today some good features that you didn't know were supported but maybe you learned about today so some people knew about all of these that's great um how to download a time series map oh that's something that somebody wants to know um that's a good question we can talk about that in the in the um parallel session later yep great input here and then this is this is quite interesting as well as where what are the um kind of the strength of different aspects of gis or maps in your countries um so very interesting input there i know one of the challenges oftentimes is you just don't have a good uh sense or not census but um data about the the the org unit boundaries or the facility locations or things like that because that can be quite a challenge when you're actually trying to do things in the real world and you don't have the uh the digital information to back that up that's something that's it's quite important to to strengthen as well great i think with that um wrap it up any any burning questions for austin yeah thank you uh regarding population displacement yes especially in conflict areas how can that be it's a challenge it's a big challenge especially in uh for example in my country uh displaced population are not located in uh camps yeah they usually are hosted by relatives or neighbors or yeah so you cannot predict exactly where they are or follow up where they are also uh what if you your your digital data that you base your maps on is old like for example in my country again the last census uh made was in 2004 so uh it's been a long time right now since we have uh got an accurate uh calculation of the population so yeah how can very good questions thank you so did you have it did you have another one as well no um so the the first question is a very difficult one to answer um and it's it's not going to be dhs2 maps that solves that problem for you specifically you can obviously if you if you have access to that information somehow and there are different ways to collect it you can display it on the map and you can use it for micro planning um i don't i'm not an expert on this but i know that there are some uh mechanisms or ways that you might or people have explored using for example uh cell tower data to estimate populations in a particular region as as populations move so you can actually without knowing the details of exactly who's connecting to towers but you know how many people are connecting to a particular cell tower they can see some some estimates of populations moving uh yeah whether whether that works in in different contexts it's it's up to um yeah it's not not entirely clear um but yeah there there are that's a that's a challenge that i think is is quite uh if if you solve it let us know but also but also i think uh there's there's more and more research on how to do that and and ways to go forward and i think maybe others um have some experience with that as well the second point is um is a very good one so actually the the google earth engine uh population layer supports uh it it can do that the estimation of the uh of the population um without uh mapping it back to census data if you don't want it to um so there's actually another option to be able to just it uses building footprints and land cover and a lot of other uh a lot of other information to provide a what has been proven to be a pretty realistic estimate of population even even if the census hasn't been conducted for 10 or 15 years so that can be quite a powerful tool as well on the last thing you said probably it will be good estimates for organized countries like you know western world or but in countries like uh you know underdeveloped countries like my country becomes very difficult to calculate based on uh yeah satellite images are extremely difficult so a big challenge here it is a big challenge but that's we there's actually a whole presentation on youtube that i can send to you that the the founder of world pop give a presentation on how they actually do this it's very complicated but they do it specifically targeting actually uh low and middle income countries and a lot of countries that have uh more informal settlements and things like that as well so it is it is something that you can get uh it's not going to be a hundred percent perfect but you get a good estimate of the population even without any other data than than what's available from satellite so yeah we can share more information about that as well thanks so just one last question from ahamed i know there's other questions probably but we have a session with us and has a dedicated thank you thank you very much austin for nice presentation just a reflection about the the good and the smart question from uh uh najib uh from yaman so we can in his question we can uncover one of the details to feature let me say or power uh by um presenting a program indicator about the assigned population for certain facility uh where we have the owner organization unit and the referral organization unit so if we adopted the concept of family practice for example and assigned population for certain area and knows the owner organization versus referral organization so the gis in this case is the vehicle so the issue how to put the good passenger uh to put them inside that vehicle in a proper way so in the design phase this is the public health uh work while we are working on designing this program indicator in this way at least we can maybe show uh some indicators might help the decision maker to see the displaced people uh crowdness um and um let me say the overwhelmed health facility as a result of displaced people so there is a work around solution for that uh uh could be uh utilized by the vehicle the gis thank you it's complicated it's a challenge it's a challenging yeah it's a challenging one there's there's some proxy indicators that you can use as well to kind of get some estimates but really depends what data you have available yeah all right so a big thank you to austin thank you all okay and i'll invite my colleague morten um to come up to give us a bit of a discussion on interoperability