Database Models
Last updated
Last updated
The Django apps and database models are divided into roughly two groups: models that store data, and models that are used to present information to the end-user.
Data models can be found in the datasets app. The central model is Dataset. It represents a dataset that was uploaded by the Data Administrator. Each dataset is associated with a Geography Hierarchy. Data files uploaded to the system are expected to have the following structure:
Geography
Group 1
Group 2
...
Group N
Count
geography
Value 1
Value 2
Value N
#observations
Only the Geography, Count, and at least one additional column are required. An example table might look as follows:
Geography
Gender
Age
Count
ZA
Male
20
10
ZA
Male
21
12
ZA
Female
20
15
ZA
Female
21
13
...
WC
Male
20
5
...
When this file is uploaded, a new Dataset object is created. Each row is stored in a DatasetData object. A typical DatasetData object might look as follows:
All groups and the Count column are stored in a JSONField.
Another key concept is an Indicator. Indicators represent saved aggregations and filters on a dataset. For example, the above Dataset can be used to create an Indicator containing population per geography disaggregated by gender. The equivalent query in SQL would look something like this:
Similarly, another indicator can be created to return population disaggregated by age.
When a new indicator is created, data from DatasetData is processed to create an IndicatorData object, one per geography. A simplified version of and IndicatorData would like something like this:
The actual structure of IndicatorData objects is a little more complicated. More detail can be found here: IndicatorData.
Universes represent saved filters on queries and enable the Data Administrator to run a query on a subset of the database. The default Universe is the total of all the distinct observations in a geography (e.g. the total population of the geography). It is possible to create a custom Universe and apply it to an Indicator.
A Universe which creates a filter on gender can enable queries on Female exclusively. PseudoSQL to represent this operation
The Universe filters field contains a dictionary that will be used in a Django ORM filter method. Below is an example filter to extract adults 60 and older.
This filter is then passed to the Django ORM as follows:
Other noteworthy models are Geography and GeographyHierarchy. These are discussed in more detail here: Geography Hierarchies.
Whereas models in the Datasets app focus on data, Profile App models are for presentation to end-users. The key model is Profile. A profile is a view of the data curated by the Profile Administrator. Each profile can be considered to be a complete Wazimap instance. A profile organises tabular data in Categories (IndicatorCategory) and Subcategories (IndicatorSubcategory). This data can be presented using three different models:
ProfileIndicator, ProfileKeyMetrics, and ProfileHighlight. ProfileIndicator is the most commonly used of the three.
ProfileIndicators present Indicators. They provide explanatory text, a custom label, and other attributes that control presentation. They are used in the Rich Data Panel in the form of graphs and the Data Mapper Panel in the form of choropleth maps.
ProfileKeyMetrics display only a single value from an Indicator. For instance, the number of youth between 15-24 living in the area.
ProfileHighlights are similar to ProfileKeyMetrics in that they display a single value from an Indicator, but are displayed in the Map View rather than the Rich Data View.
