 What we will not cover is, what we don't plan to cover is that there are some tasks for using maps in DHS2 that are not used by that. We are now, for this one, we are targeting more the end user who would like to create maps more than the system administrators. So there are some tasks, like for example, upgrading DHS2, which is like lots of considerations. So we recommend, especially for the workshop, that you are on version 230 or above, higher than better for us. And then of course, if you don't have this version, you can also try our demo instances. And then it is quite important that you have an organization unit hierarchy with coordinates, with poly, yeah, with coordinates. So you can actually have something to aggregate your data to and add to your map. And this is described in the docs here. And also if you would like to use the Google Earth Engine layers that we provide, we would recommend you to sign up for a Google service account. You don't need to do that as an end user. This is something like the system administrator do for their DHS2 instance or organization. So I recommend to have a look at these two and then before and have this in place before the workshop on 29th of April. And if you have any problems with achieving this, just reach out to us in this community channel and we will try to help out. But we won't cover this altogether because it's just relevant for a few of you. So why do we make maps? Maps are really great to of seeing how things varies across a region. So, and very often they can reveal patterns that we can't really, or it's really hard to see in a graph or in a table. So in a previous GIS Academy, we created this malaria map of Bhutan. I'm not saying that this is an accurate map. This might just add for demonstration, but here we have highlighted an area where there is malaria risk. And this is made out of elevation data. So I think the, yeah, so you can see the malaria risk zone is below 1,700 meters. And trying to sort of describe where these areas are in the chart or in the table or in words are quite difficult, but even you can see the maps, you will easily see where these areas are. And it's, they can contain a lot of information that this is a quite small map, but at the same time it contains, really contains a lot of information. And also something special with maps is that you can add these different layers of information. So here, for example, we have like a base map. So you can see malaria risk zone might be very connected to the altitude. So you can see the mountain ranges and the valleys. And here we also add the district boundaries on top that help users to orient themselves and also the district names. So what we often talk about when we talk about maps, when we create them ourselves are map layers. So map layers are often have one topic. And then we add these different topics on top of each other to create a full map. So, and so, and because often we don't want, of course we make abstractions all the time or we try to simplify things because there's some things we want to emphasis. And then we simplify the real world. You can see depicted at the end here. And then we create all these kind of different layers and then add them on top of each other to create a map. And also the maps app and the previous GIS app is built around this layer metaphor. So what makes a good map? It's very important to think about the audience all the time who's going, if you're only making maps for yourself, it might be okay, but most often you will present the map to someone or share it. And then it's very important to think about the audience and what is the story? What is the purpose of the map? Quite often I see because you have this great power with all these different map layers or map data that you can add that. I often see maps like the top here. People just add all kind of information because they have the possibility. And then, but then it's impossible to read. What means this number? What are the symbols? It's too busy. So go for simplicity like the map at the bottom, provide a legend so you can see what the map is, the title map is about, how you should read it. So don't overwhelm the audience, try to keep it simple. And often I think it's better to present multiple maps than having everything in one map. And then it's also a rule. We talk more about later, it's important to normalize your data that you have a denominator or it's per capita when you are comparing districts. Also with research shows that people have a great trust in maps. When people see a map, they often think they give an accurate picture, but it's basically you can tell every story with a map. There is a very popular book called How to Lie with Maps, giving, showing lots of places that sometimes on purpose others is just doing the wrong thing. So basically you can tell whatever story you would like to tell, you can make the numbers look better by just changing the colors and so on. So don't misuse this, try to be truthful, and also tell the user when there is uncertainty in your data. And also we are having these webinars here is that it's a very good opportunity for you to provide feedback. We also learn a lot when we look at how we use the Maps app. It's a bit more difficult now online. But we will do our best to gather feedback and then always try to improve the Maps app if we see we lack something. So now I'm going to introduce the app just briefly before. You can see that we are adding quite a few new features for every release. I've added a number of participants here in the last column. So I saw that 23 of the people signing up were on the 235, most are on 233 and 234. So we will come back to this one but this will sort of see what sort of features we are demoing that you can use or not. So, but already at like at least 233 we have quite a good coverage of features that we will present today. Yes, so now I will switch to the Maps app. I will start on the dashboard. So to open the Maps app is like how you open other apps. It's very often placed here at the top. You can also search for it. If you don't have the Maps app, if I switch back to this one. Some of you have been using DHS for a long time. You are used to the, sorry. You are used to the old GIS app. This was completely removed in 233. So after that one, you can only use the Maps app. Before that you can see both the Maps and the GIS app. I would recommend then using the Maps app. So, and we will not cover since the old GIS app is no longer in use or it's no longer supported. We will not cover that in this webinar only the Maps app. So you can click on this one. And then we are entering the Maps app. I will briefly explain the interface you see here. So everything is centered around the Maps that you will always see in the middle. And then we have the Interpretations panel to the right, which is the same we have as we have for other analytics apps. Then we have a data table, which is a table view of the same data that you can see in the map that you can open at the bottom. We will show you later. And then on the left-hand side, we have all the different map layers that you have added to your map showing. And then at the top, we have the main menu. So we will go through all of them, but this is like the big overview of the user interface. So I will start by opening a map that is already saved. So I go on File and Open. And then I can select A and C one coverage for chiefdoms this year. And then the map is loaded. It automatically assumes into the content. And then you will have the, if there are any interpretations for this map, you will see them by toggling this button here in the menu top bar. So normally I keep this closed, but if I want to see if there are any interpretations or discussions around this map, you can open it here. And then on the left-hand side, we have the layers panel. Normally I think this is where all the action and descriptions, so I keep this panel open. But if you need more space on your map, you can also toggle this one by clicking on this button. And then the data table, it's per layer. So for, and then there is a layer menu showing here. We call this a layer card here for this layer showing. So you can click on this button and then select data table. And I will show you how this can be used later, but then you will see all the data shown here in a table format. Now I will close it again. And then we have some, I think most of, I'm sure you have used Google Maps and other mapping applications. And we use the same way of navigating a map that has become very popular. So you can just drag the map to move around. You can use the scroll wheel to zoom out or zoom in. You can also double click to zoom in. And then also we have some zoom buttons here that you can zoom in and out in steps. There is also like a helper button here. If you have zoomed far in and then you want to zoom out to see the whole country, you can, or the whole, all of your data, you can zoom to content by clicking this and you will go back out. I will also show you two other tools that we have. One is the full screen mode. So if you want to only see your map in full screen, you can click on this button and you will have all the available space on your screen. And one important feature, I know in the beginning, the first versions of the maps that we didn't have a download feature, but now it's, we had it for many releases. And so you can always download a map. Then you will have the possibility, depending maybe on your shape of the country, where you would like to place the legend, if you would like to see a title or not. And then you can just click download. This works best in Google Chrome. We normally recommend always to use Google Chrome with the Maps app and also DHS2 in general. So we click download and then you will have an image of your map that you can use in your presentations or documents or whatever. There are also two other useful tools. I just, often I use, when I just want to clear the view, I go on file and new to have a clean map. So we have a search tool here. So if you want to go to a specific place, these are often most faster than Zoom in, especially if you don't know where it is. So I would like to go to Malavi, to Blantyre. And then if you click, you will get some suggestions and then you can select one of them. And then we will zoom to that city. What I would like to show you here is that we provide different, we call them base maps, like different backgrounds. So by default, we have one that is called OSM light. OSM means open street map, which is a popular mapping provider with quite good coverage in the regions where DHS to operate. And we use this as a default because you can see it's quite light and bright. So because very often your purpose is to show data on top. You want to show your own health data on top. So we don't want the background to be too noisy and busy. So that's why this is the default. But we also have a more detailed map where you can more easily see different types of facilities, buildings, roads are more visible and so on. So you can switch between them after your purpose of the map. We used to have some support for Google Maps. Sadly, because of licensing restrictions, we can't provide Google Maps like this. I know we are discussing with them and they might come back at the later stage. There are also some technical limitations. So we had to remove them for not violating some restrictions also. So, but as a replacement, we added the lay map layers from Microsoft Bing. So you can see here is an alternative for showing mainly roads. And then the satellite imagery for forum Bing is quite good. So here you can see zoom in and see aerial images for the entire. There is also another one which is including labels on top. So you can see the name of the roads and so on. So while I'm having this, I'm going to show you the last tool we have here on the right side and that is a measurement tool. So if you want to measure the distance or area in the map, you can use this. So we click the button and then we can click the map and then we can start drawing and measuring a line. So while we are drawing, you can see the distance here. So the distance I measured here is about half a kilometer. And then if I continue around this group of houses, I can then finish. I can see that this area is about six hectares large. So this can be useful not so much with your own data, but for this detailed imagery and to measure areas, this can be a quite useful tool. I will not cover this file menu at the detailed, but this is the same for different analytics app. And the most important thing here that we will use is a new map. If you want to start on a new with a blank canvas and then open, if to save us, open a same map and then you can save or save a copy or delete it later on. And you have some sharing and translating options as well. So I talked about the download, the different base maps that you can select. You will have a link to these slides afterwards. You can go in there to see. I didn't present this scale bar, but also as you zoom in, you will see the scale bar at the lower left of your map. The place search, which I recommend to use, you can also use if you have a coordinate for, but you don't have a place name, you can also paste in the coordinate, latitude, longitude format, and then it will zoom to that coordinate. And then the measurement tool. So now we are ready to add new layers. So I go back to the Maps app. So we will start with a clean map and then add a new layer. So these are the layers we provide. The top row here is layers for your own DHS-2 data. And then we have some global available data that we load from something called the Google Earth Engine, but they are provided by different international organizations. I will talk about them later. But so at the beginning now, we will start on this. We have sort of arranged them after the one that was maybe the most important. So we will spend the most time on these two, but right now I will start at the other end because these are the facilities and boundaries are the easiest and simplest layer to have an easy start. So we'll click on the boundaries and then you can select which boundaries of your organization units you would like to show. So with my use, I often go for a level, district, so I would like to see the district levels in Sierra Leone where we have the demo data. So we can just click on this and then add layer. We will zoom to the area automatically and you will see the districts. So when you have added a layer, often you want to edit it afterwards. So then you can just click on the edit button here or you can use the more actions and have a menu of layer actions that you can do and you can click edit layer. So if I want to add another level, I will add the next, the chief done level below district. I just click on this one and again, update the layer and you will have the two different colors here. Also we can restrict the view. So if you don't want to focus on the whole country but maybe only the district where you are working, you can select one district and then the same will apply. And then update layer and we will only have the district of bow with the chief done inside. Then we also have a style tab. So not so many possibilities for this layer but you can add the labels to your districts which can be useful, increase the size of it and then update. And then you will see here the labels. There are some other tools here for the layer. So one thing is that you can toggle the visibility of the layer on and off. So now I don't want to do it for this layer but to make the labels more visible, I can turn out of the background and only show the map like this. The other possibility is to have it on but then you can change the opacity so you can make the layer brighter. So you can still sort of show it but not so busy as when you have, especially when you have these or these, it can be really hard to read the labels if you don't change the opacity. Okay, so that is the district level of the boundary layer briefly. I will create a new map and then we can go to the facility layer which are good for showing your health facilities or anything that is connected to a single, not a area but a single point in play out. So we'll select a new facility layer then to show this, you need to select an organization unit group set. So all your facilities are depending on a setup grouped into different group sets. So here we can select the facility type and then we need to select the organization units you would like to see on which level. If I just add this layer, I will get a message that I haven't selected any organization unit. So the Maps app doesn't know what to show. So you need to select your level where your facilities are. So here it's also named facility. So we'll click on that one and then add the layer. So here you have all the facilities in Sierra Leone. Again, if I would like to only see one district of both, for example, I can select this one and then update the layer and I will only have this. And then we also have some styling options. So the icons you see here, I think I had it. So when you are defining your organization groups in the maintainer, there is another app called the maintenance app where you can define your organization groups and then you can assign different icons. So this can be changed. That will be also not something the end user is doing but something when you set up the system. But you can do some other styling here. So if you click on the style tab, we can add labels to the map and there is also a possibility to add a buffer. If you, for example, would like to see what is the area, if you go five kilometers from the facility, which area would you cover? So I will turn on that one. You can change this number. So maybe we can reduce it to 3000. And then update. You should see that we have added the name and then you have the buffer around it seeing how far you reach three kilometers from the facility. So that was what I plan to say about the facility layer. We will move on. I go and create a new. So now it's time to look at the thematic layer which you use to show, I think this may be the layer at least I use the most because this is where you map all your aggregated data to see the results for different districts. So for this layer, there are quite a few options of things you can select, but we also try to keep it simple and also that you can, it should be easier just to create a layer and then you can edit and change it later on to sort of adapt it to your need. So the minimum requirements for adding a new thematic layer is to select what indicator or data elements you would like to map. So by default, we are indicators are selected. You can also select data elements, reporting rates, event data items and program indicators. So, but now we go for an indicator and then you select an indicator group as there can be a lot of indicators. And so we will have a look at malaria and then we will look at those who have slept under a bed net last night. You can also select how the data should be aggregated by this. I won't go into details here, but I normally use the one that is defined for the data elements in use, but you can try the others here. And then, so the only thing you really need to select is to select an indicator and then add a layer and it should just go with the rest of the default values and then show them. So if this is the map, you can see darker color means higher rate of sleeping under a bed net, where I stand it's correctly. If you go and edit and then we can look at the period. So by default, this is also something you can set up for your instance. You can have a default period, the one that you maybe use the most to automatically be selected. So for this instance, this is the last 12 months. So this is a relative period. We also have fixed period. So if you want to look for a specific month, you can select the monthly period type and then select the month you would like to look at. And you also have the possibility to select start and dates for your indicator. But now I will go back to relative and then for the relative period, I will go for last, let's have last six months and then update. So now we have changed this only this map from the last 12 months to last six months. But we also have some other options here for period. And these are, let me check. So these are from 233. You should have this display periods option. So by default, and this everybody supports this that we just aggregate. So you have all the aggregated data for the six months and then show the results. But if you have two maps, 233 and a bow, you can also select to view the map as a timeline. So if I select the timeline, update the layer, then you will have a timeline here at the bottom. And we will not show all six months together anymore, but we will show the data month by month. And if you click on the play, it will loop through the different months. You see some arguments, we don't have data for that particular month. And you can see how it changed. You can also just click here so you can switch between the different months and see the change. Still, it can be a bit hard to see this way because you sort of need to memorize how it was the month before. So for this reason, we have also added another period, display period type, and that is split map views. So instead of just having one map, it will create one map for each month. So we can add this here, and then you will have a side by side view. So you can very much more easily see how, if you are interested in one district, you can easily see how it changes from month to month. And these maps here are synchronized. So when you zoom into one map, it will do the same with all of them so that you can easily compare all the way. There is also a possibility here to show that you can, something we call drill down. So instead of having to go back and create a new map, if you are only interested, if you see that, oh, this has bad data or low numbers and you want to see how is it within this district, you can right click on the map and select drill down one level. Then it will do the same for all maps, consume in a bit, and you will see the chief dumps within the districts and still have the same split map view. So now I will go back to the single map again, org units, I will still have chief dumps. This is the same org units we have shown before. And then I will go and see, let's drill up again. So we will have the full country. Sorry, so we have the full country on chief dump levels. There is a new tab here that you can also add a filter to your data. So for example, just to give an example, if you would like to only show data from facilities having a specific facility ownership. So I can select facility ownership and then I'm only interested in not private clinics but public facilities. So I can select this one and then update the layer and then we will only see data from public facilities within this indicator. Now we'll go back to the filter. I will remove it to show all and then to the last tab where there is also quite a few options. What you can see here, you have the legend to the left. And by default, if there is, what you can have in DHS-2 is that you can have predefined legends. So you can define the legend. Now these legends can also be used in the data visualizer app. And so you can have this predefined legend and often when you create an indicator there might be the same legend you would like to use all the time. So if you select predefined legend you will see all these different legends here that are created for your instance. So by default, this will be selected for your indicator but for this specific malaria indicator there was no predefined legend. So then we have something called an automatic legend or it's also a legend that you can change yourself. But by default, this legend will divide your data into we call it classes. So by default, this is divided into five classes and we use a classification method calling equal intervals. And that means that from the mean and the max value we divide your data into equal space. So from this, this is the mean value, this is the max value and then it's about six percentage for example between each of these. And then you can also see in parentheses here we will have added the argue in it so you can see how many falls into the different class. So we have equal intervals and then we also have equal counts. So if I switch to that one we just having the same color scale and number of classes it might change the view a little bit because here instead of having equal gaps between equal size of the class like it's 6% gap between each this one will make sure that you have the equal number of org units or facilities within each class. So you can see one is has 31 here but else is 30 in each of these class but then you will see that like the lowest class is almost 30 percentage big and then the next one is 12. So, and also back to this this is in a way you can make your data maybe look better or worse if for example a dark color is bad so use this with care but you have these two options to classify your data. I will go back to equal intervals I normally prefer that one and I will update the layer to demo the data table. So here you can see that we have two in the highest range here, two org units. What I discovered while I was or I can show you open the we open the data table for this so select this menu and data table and this is as I mentioned before a line listing or table view or a line listing or table view of your own data and it's connected to your map so whatever you change filter or change something here the map it will reflect on the map. So one thing is that you can search for a specific org unit so if you just start typing for example here it's all org units containing both you can also go on the value so if we only want to see below 50% for example if this was percentage we can be less than and then the number and you will see those org units falling within this range or 60 you will have more. You can also sort this so if you click on the column header here you will can sort the table ascending or descending so you can easily see which one has the best value. We have made some improvements in the last version so actually I will demo it later when you hover the row here it will also highlight the map so you can easily see where the different places are located. So this is what we call a coroplet map where we add color to all the district that reflects the value and if you use this mapping type it's quite important that your data is normalized so for example it's per capita because you will often compare across districts and if these are total numbers for example numbers of of covid cases for example it could give the wrong picture if it's not normalized because you need to take into account the population of course when you look at the number so this map type is not recommended to view raw numbers, total numbers so in 235 we added support for something called bubble maps it's also often called proportional symbol maps that you can use to show total numbers so I will create a new map add layer thematic and then often like the indicators will be normalized you have a denominator population that you that you use while data elements are often totals so I will select a data element and then again I will select the malaria indicator and let's look at malaria referrals so I select that one period can still be last 12 months again if I just add this it will look like this and here again it looks like there aren't many more malaria referrals in in this district and the neighbor district but this could also be be due to the population or other reasons so normally we don't recommend to view the show the data like this instead you go on style and you select a bubble map so instead of shading the whole district you select bubble maps we will add these circles so and these are scaled again according to your data and you can see the legend over here so you can change some of this for example the size of the we can increase this to 50 you can also again for this one maybe you don't want because the size is representing the value maybe you don't want to have color in addition so we can just switch to the single color and then update the layer and it will look like this and this don't give the same impressions that that of course you will see bigger bubbles some places than another but it don't give the same impression of these changes between the districts again for this layer we can have some labels and then update add them to the map yes so I think that was the most important thing for the thematic layer I would like to I was wondering if there are any questions so far yeah there are a couple questions here they had more to do with some of the things you demonstrated a little earlier but they came in very recently so the first one which is a good question is how do you make boundary layers update based on your organization unit filter in the dashboard so we didn't talk too much about plugins on the dashboard but this is an interesting point and I think the answer is that they are not reflected by the in the org unit filter on the dashboard today that was the boundary layers but maybe you have a more nuanced answer to that no that is true so but that is something we could add if that is something we should look into yeah the thematic layer should update according to the filters yeah so I can actually demonstrate that if you let me share my screen very quickly okay so this is a just simple map that I have added to a dashboard and as you can see I've included a filter here to filter this map and all the other items that would be on this dashboard to the organization unit bow which is a district in Sierra Leone and if I remove that filter we'll see that it goes back to showing the entire country of Sierra Leone and we have in this map that we've saved in the maps application we have both the boundary layer as you can see here this is the boundary of each chieftain and then we also have a thematic layer which Bjorn has demonstrated shows in this case we have the ANC visits per clinical professional if we now go to add a filter for organization unit you can go down to let's do bonbali this time and now we can confirm that so now this will restrict the thematic layer in this map to the bonbali district and we can see the bonbali district in the as the boundary here as well but we you'll see that you still see the boundaries for the other chieftains and districts in your in your country or in your organization unit tree this is actually quite useful in many cases potentially to be able to see the context of of where you're where you're looking but if that is something that interferes with someone's use case I think it'd be good to learn about that cool and then there was one other question that I saw oh there's two two more questions now maybe Bjorn I'll turn it back over to you to answer these but the first one is was sort of answered but is it possible to drill up in the map yeah so I can show you again the the drilling if I just open a map here take the first one so if you right click again a district and then we're not actually seeing your screen oh sorry you can share it again sure yeah you see it now thank you yes so I'll just open the map here and then if you right click you have this drill down so you don't have drill up here because there is no we don't have like a country polygon for Sierra Leone in the demo database but you can drill down and then when you have drilled down you can always drill up again one level so you can drill down and then also you can go further down depending on your hierarchy so you can even go to the to the individual facilities here and see their values I think the other question was that if you could display the values in the map unfortunately not currently that is also something we could add support for you have it on most over you can only turn on to see the names not the values for that particular org unit yeah and that question was specifically about bubble maps so that is yeah you can you can visually see the value but you won't see that actual number presented in the map at this point okay if anyone else has any questions please feel free to raise them now we'll be moving on I believe to event layers next seems like I don't see any at the moment okay I will be sharing my screen here to demonstrate some event layers which is the next one in the list here I'm going to go ahead and start with the slides just because we can this is just an example of an event layer and I'll show you how to build this in a minute but there are a lot of different things that an event layer can do and we'll talk about what those are here as we go along as Bjorn mentioned there are multiple different layer types here's another example of an event layer I'm going to go ahead and in this case just as the demonstration this is showing the malaria case registrations in Sierra Leone and I've added a filter for only showing the malaria case registrations for people that are under the age of five we have a legend here as well in this case we only have the events themselves which are all black dots in this case but we can edit that as well and this is showing over the last 12 months so you can see for all of these different layer types as you make changes to your configuration for that layer you'll see that reflected in this card for that layer to demonstrate what the context or the values that you're seeing on the map actually represent let's go ahead and delete this layer so that we start by the fresh map again and now we're going to create an events layer so as Bjorn mentioned that we had the boundaries layer on the right here the facilities layer and then the thematic or chloropleth layer on the left which is for aggregate data and we can also look at individual events that have been registered in the DHSU system this is distinct from tracked entities which are associated with oftentimes an individual patient or person but a tracked entity does not need to be a person or a patient it can also be something like a focus area for a particular longitudinal study or a building even anything that you want to keep track of an individual over time that is a tracked entity instance in DHSU and we can represent both of those on maps in the maps out as different layers I'm going to focus initially on events which are not affiliated with an individual these are just recorded as something that we can see something that happened at a certain point in time and also at a certain point in space which we'll see demonstrated here so I'm going to click on the event layer and similar to the thematic layer that Bjorn demonstrated we have a number of tabs here to select the data and how we want to display it for event layers we have to select the event program that we want to represent here so I'm going to pick Malaria case registration that has a lot of events so it's a good kind of demonstration here but there are others that have fewer numbers of events and we can see how we might display those in different ways for you can also select the stage of a particular program in this case there's only one stage for Malaria the Malaria program in this database and you can also do some more advanced things that we won't get into too much here but you can select different fields where the location to plot on the map is located in this case we're going to select where the event actually took place so this is where the Malaria case was registered but that might not be the same as the household location of the person that was registered as a Malaria case so having the household location would show a different location on the map for the same event and that depends a lot on how you configure your event program in DHS2 in the maintenance app in particular and how you capture that data in the capture application similarly we can also select a period here sorry the last one here on in the data tab is the stage of the or sorry the status of the program that we are talking about so we're going to go ahead and go with all but you could also show only the active cases or active events the only the completed etc in the periods tab we have a again the the same options as the thematic layer you'll see that start and end dates is up here at the top because that might be particularly interesting for an event layer unlike a thematic layer these are not aggregated values so the last 12 months will show every event that happened in the last 12 months not an aggregate of that information over the last 12 months and that's important to keep in mind so we're going to go ahead and do the last 12 months but we could also similarly say the same thing start and end date so this is automatically set the start date to one year ago today and the end date to today and that will give you the same information let's go ahead and do the last 12 months here again we can see we can select the org unit that we want to specify I'm going to keep it at the default here with Sierra Leone you can also specify the org unit based on the organization unit defined for this particular user so whoever is logged in as the user of this map to application you can also specify that organization unit that they have been assigned the ones one level below that or two levels below that similar to the filter that Bjorn demonstrated we can add a filter to this layer I'm going to go ahead and do that here because the malaria events have about 100,000 points in this database so there are quite a few and that can get quite busy in a map you can render them and I'll show you that in a minute as well but for now I'm going to start with a little bit of a simplification so I'm going to show all of the age and years less than five for these malaria case registrations and then we'll get into more of what you can do with the style tab for this layer type it's quite powerful but for now we'll leave this as grouped events and we'll go back and edit this layer to show you how you can change the display of the event layer let's go ahead and add this layer now so as you can see this does what it says on the tin effectively in the style tab we have selected group events so you can see in this map the events are grouped by their location and there are basically each group is a number of events that actually happened somewhere in this region so if I click on this 331 here in the middle and then I can see that this is a breakdown of as we zoom in more and more events appear in the regions where they occurred this type of kind of grouping of events is very useful for large databases where you might have hundreds of thousands or even millions of events that you it's not possible to display them all on the map from the from the highest zoom level for this particular map so we can get down as you can see to the individual event so this was a four-year-old male that contracted malaria at this location in Sierra Leone the Sierra Leone database is anonymized and kind of randomized data so this is not necessarily reflective of what you would see for the registration point for a malaria case but you can see that this maybe you could demonstrate that this happened along this river maybe there was in a particular outbreak number of cases of malaria in this region for that reason there are still a few groups here and we can zoom down into the individual points once we get down to a very low zoom level it's this doesn't give us a lot of context so we can again change the base map to something that shows a little bit more information let's go ahead and turn on the aerial map in this case we're in the middle of a field in a rural area so there's not a lot of labels going on but this does give you a pretty good idea of exactly where this event took place all the way to our top level where we see these groupings and these groupings are useful but they can kind of disguise a little bit some of the information that we're trying to see so let's go ahead and edit our layer here we can also select to view all of the events in this particular program so this will show us all of the malaria case registrations in the last 12 months for the country of Sierra Leone in this database and we're going to go ahead and turn that on so this will instead of showing groups of events this will show us every single event as an individual point and you can see that this is a smaller number of events than we've seen previously in the example that I showed earlier and that's because I have this filter here but this is still probably something in the thousands of events as we saw in the groupings and you can zoom all the way in I know it's a little bit jerky potentially on the Zoom call to view this but it is quite smooth to be able to zoom all the way in and quickly see exactly where each of these events took place so I need to get kind of an idea of groupings to show the total overview of cases but when you're all the way at this high Zoom level it's not very easy to distinguish how many events are in this region right here versus another region and that's where the groupings might have a little bit of better utility in showing the information that you want to convey let's go ahead and take this one step for further we have the option to style by data element and what that means is for each of these registrations as we saw when I clicked on an event for that four-year-old male case of malaria we have certain data elements that are collected when that event is registered in the system we in this case for this program we have age and years and gender but there might be many other data elements that are collected and in this case let's go ahead and disaggregate by gender so by selecting style by data element gender I can actually instead of showing every registration as a black dot I can show the ones that are male as a blue dot and the ones that are female as an orange dot let's go ahead and see how that works so just like before we see every event registered as an individual point but now we have a legend here on the left that shows male, female, or there's actually a black dot as well for registrations that didn't specify which gender was of what the gender of the patient was and we have blue for male and orange for female and every single point has this value or this color zoom in and show that there were two females in this location and one male in this location and really get to more information about these cases similarly if we go ahead and take off this filter so previously I had specified a filter for only showing the malaria case registrations that have an age and years of less than five so I'm going to go ahead and delete that filter and update the layer as I mentioned about 100,000 points so it might take some time to render but it will show me all 100,000 individual malaria case registrations on the same map this is a new feature in 235 I believe that is called WebGL and we're using that to render the maps in a much more performant way so that you can actually conceivably render 100,000 events on a single map and still be able to very smoothly again it might be a little bit disjointed in the zoom call but it is very very smooth to zoom all the way in to an individual case and then all the way back out to the 100,000 points that are rendered on this map at the national level and that can be quite cool you can also get again get an idea for how useful or not useful it is to render this many points at this high of a scale so as we're looking at the entire country this doesn't tell us very much here in this huge cluster of a lot of different malaria case registrations and we'll show how we might be able to disaggregate that again with a grouping in a minute but before I do that I'm actually going to change this style by data element and I'm going to change it to say age and years so age and years instead of having just two options has is a is a number and we can again as Bjorn mentioned used either use either a predefined color legend set which is defined in the maintenance application we have a predefined one for a 10-year interval of ages we also have an age of 15 years and there are many other predefined legends for different types of data or we can use an automatic color legend which is similar to what Bjorn mentioned we can select either equal intervals which is preferred in most cases or equal counts and select the number of classes or different colors to show the number of different groupings to show in this legend I'm going to go ahead and use the predefined legend set for age of 10 years and I'm going to update this later this is again rendering the entire database so it's or the entire set of malaria case registrations for 100,000 or so in the country of Sierra Leone and hopefully my demo did not just break here I will yep we should be okay so it should be rendering all of these case registrations we have about 100,000 points again it's not super useful to see all of these in on top of each other from this very high zoom level but you can see on the left here that we have 10 or so different categories in groupings of 10 10 years of age so the very lightest color which is difficult to see on the left in the legend here is 0 to 10 and then you have 10 to 20 20 to 30 30 to 40 et cetera all the way to 90 to 100 so we have we have no malaria cases registered for people over the age of 90 or over the age of 80 but we do have quite a few in the 70 to 80 range in this case we can turn the opacity up and down just like other other layers as we've seen before but as you mentioned or as we mentioned this isn't super useful from this high zoom level if we zoom all the way in we can see kind of the clustering of the the different events the malaria case registrations and their colors represent the age but it might not be super interesting to see individual points individual cases and the age of that individual person so instead let's go back to our style tab and now let's group again so previously we had all the we were viewing the group of events without any style by data element selected now we've been trying style by data element with viewing all the events all 100,000 points in this case now let's go back to group by a to the group events option but we're going to keep the style by data element so instead of seeing a black circle with a number in it that doesn't represent too much other than just the number of cases that occurred in that general region we have a also a style by data element selected which will group those or kind of assign a color to those points when we zoom all the way in for a particular age in years let's go ahead and update this layer again it zooms us back out and here we have what we call donut charts and donut charts were introduced I believe in 235 and they allow us to be incorrect me if I'm wrong on that by the way they allow us to see the grouping of all of these events but with a a donut or a kind of a wheel that shows how many of the that number in that group are in each of these age categories so we can see here that they're fairly fairly evenly distributed but we can go ahead and look at some of these individual cases and you'll see that here we have two events and half of them are younger than the other half it's hard to tell exactly what these numbers are which legend they are but when you have a whole range like this 117 you can see that there is a distribution of each of these age groups if we then go all the way in we can see that there are two points here one for a male age 13 which is going to be in this second category of color legend and one for a male age or female age 57 which is the sixth or so category here on the left this is a nice way to get an idea not only of the number of events that occur in a certain place but also how they break down in each of those regions or areas by the some data element in this case age and years so that's quite a handy feature to be able to show I'm going to add one more thing in the style tab before we move on here I'm going to go back to view all events and just for simplicity I'm going to add the filter again so I'm going to say age and years less than five I'm going to go ahead and continue to have this style by data element here so yeah so actually this is correct so you can see that because I've set the filter to be aged less than five all of the points in this entire map are going to be in this first category of age zero to 10 so they're all going to be the same color so this style of data element isn't super useful for us anymore let's go ahead and go back to the the gender disaggregation we could also specify an automatic color legend with equal intervals and five and that would show us the number that are one year, two year, four year, and five year more or less but let's go ahead and do gender here instead so now we have those all of the malaria case registrations for children under the age of five and the color indicates whether they are male or female we can add one more thing here in the style tab and that is a buffer so in the buffer we could is similar to the facility layer that Bjorn demonstrated earlier we can have a radius of some number of meters around an individual case for malaria case registration this might make sense it might might not make that much sense but it might give us a an ability for for a different type of event to show a radius of maybe 10 kilometers or something like that around a case of a particularly infectious disease to show where that it might be likely that that disease might spread that's just one example use case there are a lot of different use cases here depending on what you're modeling with your event program let's go ahead and just make this one kilometer instead of yeah instead of 10 go ahead and update this layer we see basically the same thing but if we zoom all the way see that each of these individual case registrations points has a buffer around it which is also colored with the legend so this is a male I'm going to go ahead and switch back to the normal road map so that we can see this a little bit easier but you can see that each of these has a buffer around it that is one kilometer in radius you can also see that displayed in the legend on the left here so that's just another tool you can use depending on the data that you're using to analyze this information in geographical space next I'm going to show the data table which is very similar to what Bjorn mentioned about the thematic layer so we can open up oops sorry that's download data which we will not get into today but I can cover it very briefly afterwards let's look at the data table here so as we can see we have a table of all of the points that are on this map you can see the data elements that are collected for each of those events so we have the age of the person in question the gender of that person the color just represents whether it's male or female in this case but it would be different colors based on whether you select the age desegregation or the gender desegregation in your style by data element selection similar to the thematic layers you can sort so we could sort by organization unit here in this case the organization unit is representing the place where this registration took place so this is a community health facility for instance there's a health post where other ones were registered and maybe we want to only see the the events or the the registrations that happened at hospitals so let's go ahead and type a hospital here so this is a little bit it's a little bit imprecise it's more for kind of exploring your data and finding information about it similarly you could use less than three in order to find the age and years of less than three for these these registrations this is actually just searching the text of the name of this organization unit so you might have a hospital that doesn't have hospital in the name in that case it wouldn't appear here but you could use the filter functionality in the event layer configuration itself to filter by facility type instead in this case it's just a simple way to restrict the view to only the cases that occurred in a org unit with the name hospital or with the word hospital in their name as you can see as I typed this filter not only did we restrict the the events that show up in this data table to only those that have hospital in their name but we also restricted the events that are appearing on our map so in this sample database there were not very many events that occurred outside of hospitals sorry in hospitals there were most that most of the events occurred outside of hospitals so this is a fairly small number that is returned also when you're restricting to only to hospitals many of these points might show up on the same at the same place as to where they're registered so it might be it might make sense to use the grouping rather than the individual points functionality let's go ahead and remove this filter you can also do this with all of the other types of of all the other columns in this data table but it's a nice way to really drill down and see some of the information or filter the view that you're looking at in order to do some exploration let me check my notes just to see what else I was going to talk about for the events layer I think that was it Bjorn is there anything I missed there on the event layer no the only thing is that this WebGL that you can actually show like 100,000 events at the same map and also the donut cluster this was not in 235 but from 334 so that should be accessible for quite a few of you and there's also a reason for to do your upgrade thanks did we have any questions again there are no there is not any one relevant for this so we will take that that was later okay the last point I wanted to to add here is we do have the option to download data for an event layer so you can download a Geo JSON of the malaria case registrations in the with the filters and everything applied and the style of data element applied that you've used in this map you select the the ID that you want to use to identify each of the individual events you can use ID or code you can use human readable keys rather than the like ID identifier values and we can go ahead and download that this might take some time but it will download a Geo JSON file that will be you can you then use in for instance QGIS or other software to do more sophisticated analysis of your of your data and we're not going to get into how to do that in other GIS software but this allows you to kind of construct the data set that you want in this in this maps application download it and then use it in that in a in a more advanced context we there is one relevant question before we move on and sure again some users are concerned with downloading this much data they already know from large pivot tables that that takes time so and and ask for some recommendation what I would say here is that by default we have this grouping on and if you are not grouping by or styling by a data element this grouping will happen on the server so we will only download very small number of data so instead of downloading 100,000 data we will just download these symbols showing that here it is 183 and and not the individual 183 events and then as you zoom in we will load more data so even on the slow bandwidth you should see that this by by just going with the default selections go pretty fast so it slows down when you decide to show all events or you decide to style by a data element because then we need all the data in the browser to be able to make this this visualization and of course also like like Austin showed that you can either restrict by adding a filter so you don't look at the whole population but maybe just below 20 years and you can also restrict by all units so you don't go for the whole country but one region and then there is another question it's about how more of the wish shows that it might look like when you have zoomed out that we have added a little white outline around each each of the events that might look like they are sort of a little bit melting together when you look at a very high density numbers but they should sort of spread out as you zoom in so if there are any suggestions of how we could style it differently please please suggest okay keep going sure so I just have a demonstration here this is the grouping without styled by data element and in this case it's very very fast even though we're still visualizing a hundred thousand points in total it would be very fast to do this and in order to do that you have grouped by events and you have no styled by data element selected if we update that layer it's very very fast to download that because it's not downloading the entire a hundred thousand points and you can still zoom in individual points and it will load as you zoom in more smaller datasets that you can see cool thank you for that another one is restricting by the by org unit even if you have all points shown you can show only the points in a particular region and that will restrict the the download size okay so next I'm going to demonstrate some tracked entity instance layers as as we've mentioned this is the the third layer type it's similar to events but you're actually visualizing something that you're tracking you're keeping track of over time you have longitudinal data about a thing it might in most cases it would be a person or a patient but it might also be something else that you want to track through time I've created a very simple representation here with with just a few a few tracked entities in this case we're looking at focus areas for a malaria case registration program so this is these are focus areas that are being kept track of by the team that's doing the investigation of malaria cases in this particular region in order to do that I'm going to go ahead and create this again but this this is just an example of a tracked entity that is not a person that you can track keep track of over time and you would enter data for this focus area in the tracker capture application in DHS2 I'm going to go ahead and remove that layer and add another one here so let's go ahead and focus area is what I had shown before so you can select the malaria focus investigation for to view those polygons that I had shown there and that was an interesting one as well because you could see that they weren't just points they could also be more complicated shapes on the map because for a focus area you're not focusing on a specific place you're supposed focusing on an area and in order to do that you can create focus areas or foci that are polygons or more complicated shapes in order to cover the area that you actually care about in for this case I'll get into relationships in a minute you can select period for your tracked entity instance unlike other map types or layer types you cannot select relative periods or absolute periods here you have to select a start and an end date and this reflects the enrollment of the particular tract entity into this program we can also select the org unit that we care about it's important to note that tracked entities are very often registered at a very low org unit level so they're probably registered at the facility level for instance and you need to have the user that's building this map needs to have view access to those tracked or that org unit and tracked entity instances in that program in that org unit so you often won't have a national view of tracked entity instances you'll have a more tailored view for a particular region for instance in order to show that we could select all of the individual facilities for instance or if we knew our tract entities were registered at the chiefdom level we could select chiefdoms but in order to make that a little bit simpler we're going to select Sierra Leone so the entire country and we're going to choose selected and all below which means all of the the Sierra Leone national level all of the districts all of the chiefdoms and all of the facilities that this particular user has access to we have a very simple styling selection here again we can select a buffer I won't show that in this case actually I'll add it just to just to have a little bit of extra information we can also select the color of this particular focus area that we're going to be rendering on the map let's make that green and point size for a polygon which is the the focus area is a polygon and not a point the point size won't make a difference but this would also adjust the size of the point for point layers going to go ahead and add this layer so as you can see we have these three focus areas and if I turn this back to we can see that there's a little buffer around the entire edge of this polygon as well if I change that buffer to be maybe 10 kilometers or something instead we actually quite large areas around these polygons that show the the areas where these that we care about for this case let's make that let's go ahead and get rid of that buffer because that's not not super useful in this case okay so we have these focus areas but we don't care so much about the focus area by itself in this case we want to know what what actual relationships that we have defined between that focus area and individual malaria case registrations so we can this is a a experimental feature that's been in since 234 I believe probably we'll see some significant improvements in 237 and beyond but what we can see is that we can actually show the relationship between different entities on the map using the relationships that are defined for this particular tracked entity type so for the malaria investigation focus area tracked entity type and program we have only one type of relationship defined and that is a relationship between the focus and an individual case of malaria we're going to go ahead and do that and so here you can see maybe we have some bad data here but you can see that there's actually a relationship between this polygon and the three points that are within it this might not be the most straightforward representation there might be other ways that you could look at this data which we will investigate in future versions of DHS2 but this is just an example of showing some of those relationships we're going to go ahead and remove this layer and create another one with a tracked entity type of malaria entity which was the the destination type that we just saw going to select the program I'm going to show relationships here but in this case we have a relationship back to the focus area but we also have a relationship between two cases from an index case to an individual case might be particularly useful for a communicable disease for instance like COVID-19 we can select selected and all below for our org units we can style here we show the the point size in this case let's let's make it a little bit larger make it eight we could add a buffer if we wanted to 100 meters and we can also now define the the color and the point size and the line color for the related entities in this case so here we have it we have a index case of whatever we're tracking here related to subsequent cases that we can demonstrate in the tracked entity instance layer that is for now the overview of what you can do in a tracked entity instance layer in DSS2 maps application again look for more coming soon but this is an interesting way to investigate not only individual events but entities that you track over time and how those are related to each other I think that's it for tracked entity instance layers Bjorn did you have any anything to add there or any questions that came up no I think that was good there are no specific questions for this so we I think we can move on correct so there are we are 20 minutes and two more layer types so I think we are on time so let me share my screen again so what I would like to demo now is that when now when we have added created all these different layer types I will see what you can do when you have more than one layer on your map so at the beginning I will just load a layer here this is just for demo purposes so which one is not so important and then I will add an event layer on top so I'm just selecting this program and add the layer so here you see you have two layers so the the rule is that the layer you add the last is always placed on top of the others and and the it will also be reflected in this column here to the left so at the bottom you have the base map and then above the base map you have this layer this thematic layer and then at the top you have the event layer but and the base map always needs to be at the bottom it's now it makes no sense to put the base map on top of the other it will just hide everything so but for these two layers here you can easily change the order so by just taking this handle and then drag it above the other so here in this case it really makes sense to have the event layer because above on the on the top because it's not covering so much as the other but if you are doing the other way and then you can also change the opacity of the different layers to reflect but normally I would always recommend to place points these points here above these color the shapes that we have so okay and then I will move on to the next layer type which is the row here on the second row and these layers are from different providers but they are all from something called the Google Earth Engine it has nothing to do with Google Earth like the 3D globe viewer from Google so Google Earth Engine is that Google is providing their infrastructure and computing power storage like for the this is for the common good so we don't need to pay anything to use this service we need to sign up to use it but for non-profit use it's freely available and what organizations can do for example we will look at population density data that is from an organization called WorldPop so they can upload the data to the Google infrastructure and then we can use it again in DHS too so we have just added a few layers there are hundreds of data sets available so and if you have some specific needs you can ask us and we will try to add those we will also try to enable that you can add your own good layer from this Google Earth Engine later on so you don't have only to rely on the one we have selected this is also greatly improved in the new release coming in next month so I will demo both what you can currently use and what the changes we have done for the upcoming release which is quite exciting but for now if you want to add an elevation layer you just click on that one and then here you can also work with the scale because like what works maybe for Sierra Leone wouldn't work for Nepal so you can invidually set the mean and max and the color scale for the layer I will just go with the default and then add the layer so these data sets are having a world coverage so you can zoom out and see the whole world so it can be a bit hard to orient here because it's covering the base map what one thing you can do then is to add a boundary layer that we looked at before so we can add the districts and maybe also the labels of the districts and then we will add that on top and then it's a little bit easier to see so this is what you can currently do with this layer there is one little feature here in that is you can right click anywhere on the map and you can see the elevation of that particular place so the elevation at just this point here is 1641 meters but this is about what you can do it it doesn't really give you the numbers for the odd units but give you a visual view of the elevation and then also I got a question that because I demoed this Malaria elevation map from Bhutan previously and I got a question how that could be created unfortunately we don't you can't do that in the maps app yet maybe in the future but you can do that in another application called QGIS and if you have signed up for the workshop we will introduce that program at the end of April when we have the two days workshop we don't have time today but what you can do is for this elevation layer you could try to adjust the number of steps reduce them and maybe you have like the Malaria risk zone is zero to 900 for example you can do this and update and you will see by the colors for example that above 900 it's a very low risk maybe higher risk but at this in these classes here so this is what you can currently do in the maps app but now I'm going to move on to the latest version so I will demo here on 236 which is soon coming so you will see that this has changed a bit this view is quite the same so I will also now start with the elevation layer at it what you then can do is that you can decide that you want to aggregate you don't want to see this you want to see the actual the mean population for example within your districts or maybe the mean on the max we will show this for population data after that might be even more useful but now I would like to have the mean and max elevation for all my districts this is the one you can select between and then by default we select the second organization level so we will select this and go with the default style again so what we are now doing this takes more time than before because now we are actually uploading your organization units to the google server it will still be on their restricted service so they won't use that data for for other purposes but we will add not individual data but this only the boundaries will be uploaded so it's also good to be aware that that that data will be shared with google and then for each of the odd units on their server we will calculate the elevation data so if you click on this one you can see that the max elevation in this district is 1,933 meters the mean elevation is 456 and the minimum elevation is 72 and then you can look at this for all the different districts I think this is even more useful for a layer like population because what you can now do especially if you have bad census data or you have some regions where you we didn't have a census you can actually calculate that here on the fly so we add a population layer for population I would just like to have especially the sum I'm interested in I can also have the mean which belongs to the goes to the population density for here we have different periods and these are not something we define these are the basically the years that are provided by the the international organization you provide these data and for world pop here it's they have data back to 2000 so you can actually also see how the population has changed over time but now I select the most recent year again I'm fine with going with the districts and I will also have the default style so I add this again it takes a little time because the day we have the calculations are not happening locally I don't think it should be so much slower on a low bandwidth infrastructure necessarily because the data sent between dhs2 and google are not that big but it's the calculations also that takes time because here Google needs to count all these individuals that these are by population by 100 and 100 meters so all of these needs to be counted within your districts so if I click on this one I will see that the population in 2020 for this district is estimated to be 468 000 you can also again open the data table and you can see the population numbers here for for all here you can also see a new feature we added for 236 if you just hover the table you will see it highlighted on the map so it's more easy to see where it belongs and if you want to sort the population numbers you can just click the heading so western area is the most populous country district 1.4 million if you only want to see with lower population than half a million we can do like this and then the full layer will show but these ones are only having this value I will remove the filter again here you we have we tried to have the same functionality across all layers so if you would like to see within this district you can drill down one layer and then see the chiefdoms instead again with the same aggregations so in this chiefdom 64 000 people are estimated to live so we think this can be we have quite a few of requests of this and making it this easy to get these numbers it can be hopefully useful for many of you what we would like to support later on is that you can import this data also to a data element so if you have a like a population denominator that you will use for your indicators you can fetch these values directly from this source like worldpop so but this needs this needs careful considerations and it's because you can have a big consequence to change the denominator for that is used for many indicators so we need to do this probably and we probably not add it to the maps but to the import export app instead but we hope to get this in place for 237 but so far you can easily see the values you have the data table and you can also download the data and import it again to a data element by other means especially for covid there was also a request to have this population divided into age groups because maybe you want to start a vaccination planning and see what and see maybe about 80 years old how many are there in different districts so we added a new population layer for 236 which have these age groups so you can add it and then you have a new selection here so in addition to the aggregation methods you can select the age groups you would like to see you can select only one but you can also say like multiple so maybe we would like to have women for example about 70 years we can have men as well so we can have the same classes for men so we have these six groups we select again district is fine and I will add the layer so you will see here that the map is very bright I will show you in the second how you can change it but that is just because now we just have there are quite few actually in these regions being about 70 years men and women so most fall into the lowest class here in the in the legends but you can click on this and then you will see that for this district it's estimated that there are 5,732 to men and women above 70 years so this could be very useful for for vaccination planning what our plan is that you will work more on this data for the workshop coming up and even though you don't have 236 we will show you how you can select these values using another program so it's very good that most of you have signed up for that one we will also have world pop coming and having an hour introduction to these data sets and explain how they are created limitations if you can rely on the data and so on so please join the workshop to learn more about this just to show you that you can make this more interesting visually so we go to edit and instead of having a legend going from 0 to 10 we can have it going to 0 to 1 and then if we update the layer we should see more or more like how this distributed around the country so now you can see this has a higher population here than in other places lastly I would like to show you that because there is also that was not really related we have these districts that we call polygons we will explain more about polygons and points and how they differ in the workshop but the important thing is that the facilities even though they maybe have a catchment area or a coverage often they they you don't only have the point coordinates and maybe you want to know the population living around a health facility so what we have done so far is that we can go to style and then again create this buffer so we want to know the population living within kilometers from a health facility and then we also go to organization units we don't want to see the whole level but we would like to see the facilities here in this district so I select this chiefdom and I want to see these facilities we done update the layer sorry I need to also because now I only selected yeah so I get this polygon because I only selected the chiefdom but I also need to say that I want to see the facilities in this shift on only facilities so I select facility level and then update so what we are then doing here is that we are aggregating the data to 5000 meters distance from the facility so in this health facility here there is an estimated of 73 people living within 5 kilometers from the facility so this is what you can currently do in the workshop later on we will also see I'm running out of time now we will also show you that this can also be done by driving distance so the last layer I didn't plan to to demo but just to show you that we have that possibility so I will quickly jump to that one so we have something called external layers and this one allows you to add your own external layer not only down so we have from google earth so for example you can add a terrain map if terrain is important for for your visualizations or you can add aerial imagery or we have created some examples here for those of you who needed to show that borders can be disputed because there is no true country border map of the world so these are just some examples we might go into more detail with this in the workshop quick summary these are two maps should make it easy to create maps from your health data we I hope we have been able to show that and you can just start very easy and then add more complexity as you go along remember to make your maps easy to read it's not necessarily to add a lot of layers even though you have the possibility to do that for aggregated data you use the dramatic layer and for data about individuals you need to focus on event and track entities and then also from 236 you can aggregate data from external sources like population and elevation even temperature and rainfall to your own organization units this I would really recommend to use this data table more because it's an easy way to explore and and filter your data and then also remember that you can easily save download your maps export data that we will look into next in the workshop and also it's easy to add maps to your dashboard and I just recommend to also see the user documentation where we try to to write how you do all this for the workshop it's a two-day workshop to sort of to get a certificate you need to take part three hours each day which is between 10 and 1 where we will have short presentations and then we plan that you should actually can do exercises on your own DHS to instance or the demo instance so we don't plan any hand-ins because there are too many participants but you need to take care in take part in all the sessions to to get this certificate and then we will have after each day one hour with questions and answers and try also to buy you into at least two groups so we will try to help you as as much as we can there might also be some follow-up after these two days if we see that is needed one preparation you can do before this is to install QGIS it's a desktop mapping application that which is very powerful which we will use on the second day so you can download that from QGIS.org Alice I hand over I will just see if there are many more questions there is only one more question what's the difference between polygon and multi-polygon so this we will cover more in the workshop the short answer is a polygon is just like a single shape but for some districts two polygons maybe it's a state divided on two islands for example and that will be a multi-polygon to represent that but more on that in the workshop okay Alice yes so just a quick reminder to to everyone we have the DHS2 annual conference coming up from 21st to 25th June it's basically the largest event of the year last year we had over 900 participants so we aim at having even more participants this year so if you want to get some updates on the latest innovations and hear some very interesting use cases from all around the world basically I just shared the link in the chat so click on it and do not hesitate to register obviously it will be fully digital also this year and we have also a call for presentation proposals so if you want to share with the entire community your experience your use of DHS2 do not hesitate to submit your presentation proposal and you will hear from us by mid-May we also have the web and android app competition so if we have any developers who want to share their innovative work development work please go on the page you can read all the criteria and you can also submit your your project for the app competition that's it thank you so much okay thank you all I see that we are already a little bit over time but almost on time there are no new questions you can still use this page and ask questions and we will try to answer them or say if that is something we will cover in the workshop so I just want to say thank you for joining hope it has been useful and I hope to see most of you on the two-day workshop where you can practice on yourself and we can go more in detail thank you