 Again, hi everyone. My name is Andrés. I'm part of the Android team and I'm happy to be here with you to do my first presentation in this academy. So let's see how it goes. Well, I will try to present datasets and validation rules in about 15 minutes. Then I will do a live demo in order to show you what I explained you before. And in the end, we are going to try to do an exercise pretty similar to the live demo I will do. So, well, as every one of you know, dataset is a collection of data elements grouped together for a data collection. So how is this display in an Android application, in the Android app? It's integrated with the activity list, okay? So it is together with the program, with the programs. The way you have to identify it is with the subtitled dataset. So, for example, here you will see a program for the track entity person also here. But for example, here you can see dataset. So this means that this is a dataset. The access principles are the same as any other program. So you can share a public or private as any other program, work in the same way. And then the theme, the icons and color also apply. So if you can customize it, but it's not, you will inherit the default one. How dataset looks like? Well, we have the section you can prepare in a dataset as always rendered as tabs. So you will see as many tabs as sections you have. Here we only see one tab because there is only one section for this example. Then with these arrows, you can adjust the data entry column name where you can put it wider or tighter. And this, the way you configure it is will be kept for the rest of the dataset you will open. You always can modify it. In order to navigate for the dataset table, you can swipe left or right through the tables and you will see everything. So for swiping the sections with the tabs, you have to tap in the tabs specifically because the slide works for the tables. In tablets, you can put the phone in landscape mode. So we'll see in a wide way. So maybe it is better for usage. Okay. If you go to the first option of the bottom bar, you will see the details of the dataset. Here, you can see the completion status. For example, this example is open, the dataset. You can see the period. You can see the organization unit. And in the case that the dataset is not editable, you will see the reason why it's not editable here. Okay, let's imagine that we have a dataset completed and we would like to reopen it. If we tap on the three dots on the top right of the screen, we see a contextual menu. We have the option here to reopen the dataset. Okay, said that. I'm trying to explain you how the validation rules work together with the dataset. So for this, we have an example, a pretty actual example related to the COVID-19 test and PCR test. So this validation rule, what it's going to check is that the number of PCR tests are less or equal than the total amount of tests done. Okay. So if you see, imagine that we don't meet the requirements for this validation rule. So we will see the error in the Android application. And as you can see, we have like a title explanation and a subtitle explanation. In order to give them more information to the user to be able to solve this issue, you have to know that in the description section, when you configure the validation rule, you will have to put like the main title you want to explain. And then in the extraction, you should add the information to be able to solve this issue. There are different ways to execute a validation rule. So let's see the workflow holds both. In dataset management, in the server, you will see some option when you are configuring your dataset. Then this one called complete allow only if validation pass. This, as the name says, is to give the user the opportunity, the possibility to complete the dataset even if the validation has not been passed. So let's play with the different possibilities. Imagine that we don't have this option mark, so we don't force the user to meet the validation rule to complete. And we have an error. Okay. For example, here, the error is that the number of PCR is bigger than the number of total tests. So if you do the data quality check, you will see the error, but you have the option to complete anyway, even if the validation is not passing. Now let's see what happens if we check the complete allow only validation passes in the server. When you try to save the validation rules are executed, you will see the error as usual, but you don't have the possibility to complete the dataset. So you are forcing all the data entries to be compliant with your validation rules. And the third case is when everything goes fine, even if you have selected or not the previous option, when you meet the requirements, you will see a text saying everything looks good. Do you want to complete? Yes or no? Okay. Now we can see the, we can see this in the device. Okay. Let's see, we go to the datasets and we enter in a dataset that is not completed. Here, as I explained you before, you can play with the width and the height of the data entry names. Also, you can navigate between all the columns and rows, swiping left, right or up and down. Okay. Okay. So here, let's see, let's imagine that I have an error and I want to check the data quality. Okay. Here, we can, here we can see the error. And as I told you before, we can, we can, we have the option complete anyway. Now let's try, let's modify the server in order to, to don't allow the user to complete anyway. Is the validation? No, that's a pass. Okay. So I modify this, my mark complete allow all the validation pass. And I save. If I go to my device and I sync my configuration, if I try to run the validation, I see the same error information, but I don't have the possibility to complete the, to complete the dataset. Now, if we fix, we solve the issue, we have the, everything looks good. Do you also want to complete the dataset? And if we tap on yes, we complete it. Okay. So I think now it's your turn. I will try to, to explain you the, I mean, the objectives of this exercise is to, is how to enter data in data set for Android and know how the evaluation rules display. Okay. So the exercise is pretty similar or what I have just done. So you need to, to enter data for the dataset, COVID-19 surveillance. Okay. That is this, this program you, you should see in your home screen. And then you need to force an error in the validation rules. Then you should fix the error, save and complete the dataset. Now, as you, as you have seen before, we are not allowed to complete if the evaluation rule doesn't pass. So for you is, is the way you need to, you need to do it. You need to, to pass the validation in order to complete the submission is going to be to a screenshot. Okay. One screenshot is the, the dataset entry with the wrong values showing the message, the error message. And then you should fix the, the validation and do a screenshot with the, everything looks good message. So that's it. I think we have plenty of time to do the exercise. Please let me know any question you have.