 In this presentation, we will discuss the building blocks of DHIS-2. In DHIS-2, there are three core building blocks or dimensions that describe the data. This includes the where, which we refer to as the organization unit, the what, which we call the data element, and the when, which is known as the period. Every data value within DHIS-2 will have, at minimum, these three dimensions associated with it. Let's take a look at the example below. If we have a value of 100, this value on its own does not give us enough context. By attaching the where, what, and when dimensions to this data value, we have a better idea of what it represents. We first start with the organization unit. This is where that value is collected from. We then have the data element, A and C, first visit. This is what is being measured by that particular data value. We then have our period, October 2014. This is when that value was reported. We can see when we add these three dimensions to that data value, it now has some meaning and we understand what that value represents. Let's discuss these three dimensions a little bit more. In DHIS-2, organization units represent the geographical context. As an example, this can be the facility reward that is providing services in a health system, or it can be administrative units like a district or province. Typically, data is collected at the lowest level organization units that are available. In a health system, this might be the health facilities. Reports can then be aggregated for any level above this lowest level. As an example, if we want to add up data from multiple facilities, DHIS-2 will be able to perform these calculations for you. Organization units are located inside of a hierarchy. The organization unit hierarchy is meant to reflect the administrative structure and levels within the system that you are working with. How we build this organization unit structure greatly affects usability and performance within DHIS-2, and we will come back to this concept in other sessions. In training land, which is the training environment that we have created for you to use, there is a four-tiered hierarchy system. You may have noticed this when we were running through the very quick demonstration of some of DHIS-2's features. We start at the top with the country. This country is separated into two regions. We saw this when we went over the presentation of training land. Each of these regions have districts that belong to them. Underneath the districts we have facilities. All of these facilities belong to a particular district. Different systems have different types of hierarchies, but we will be using this example to demonstrate different principles within DHIS-2. The next aspect that we will explain a bit are the data elements. Data elements explain what we collect and analyze. As an example, we can collect information on the number of new malaria cases, the total population, the number of measles doses given, and in our first example we used ANC first visit. Sometimes data elements are referred to as indicators in other contexts. However, in DHIS, data elements and indicators are not the same. Data elements describe the raw data. This is what we are collecting on our forms. Indicators can refer to calculated data values. We will go over the principle of indicators through our analysis sessions. But just for now, we're focusing on data elements which collects this raw data. These data elements can be further disaggregated. For example, you can separate measles doses into less than one year and greater than one year. We will also cover this concept during the analysis sessions. The last core dimension that we will discuss are the periods. This is the when aspect of our data dimensions. Periods are organized by types and frequencies. This can include monthly, quarterly, six-monthly, yearly, and other period types. If we have data that is collected monthly, then we can create reports that are monthly, or we can aggregate these reports to be anything above that period. So that monthly data can be automatically aggregated to show data by monthly, quarterly, six-monthly, yearly, and any other period that is above that monthly period. We can also use this concept of relative periods. These allow us to reuse different reporting outputs without having to update them. Some examples of relative periods include last month, last quarter, this year, and there are many other examples that we will cover in the demonstrations. Relative periods always refer to the current date. As an example, if it is January 2017, the last month will be December 2016. In February 2017, this will automatically update, and the last month will now be January 2017. We will cover this concept in quite a bit of detail through our analysis sessions. So to summarize what we have discussed in this presentation, we have three core data dimensions for building blocks within DHIS-2. This includes the what, which we refer to as data elements in DHIS-2, the where, which are called organization units, and the when, which refers to our periods. We can go through one more example of this now. If we look at live bursts, this is the data element that we are collecting. This is collected within Cake Hospital. That is where we are collecting the data from. This is collected in February 2016. This is when this data item was reported. At minimum, these three aspects are attached to all of the data values within DHIS-2. This ends the second module. In the next module, we will be covering various aspects of data analysis. We will refer to these core concepts many times within those sessions. Please let us know if you require clarification on any of these concepts before proceeding.