This page (work in progress) will list the data scenarios and characteristics we have discovered as we go through the data acquisition process.

^{Please note that headline refers the indicators' aggregate/highest level of data}

The distinction between statistical and non-statistical indicators is not always clear cut, for example indicators 1.5.3 or 5.a.2 are statistical at a global level and non-statistical, i.e. TRUE or FALSE, for individual country reporting.

In cases where we have a single year of data we need an alternative data visulisation method to line charts, which are better for time-series. We have used column charts.

We can use a units column in the indicator data to separate the data. Doing this looses comparability between the units on the line chart but enables appropriate y and x axis scaling for the individual units, which can be very different.

Case where disaggregation availability are only applicable when specific criteria are met. Here are some examples:

• A specific units needs to be selected (e.g. 1.4.1)
• A disaggregation is dependent upon the selection of another disaggregation (e.g. 1.2.1). This is hierarchical data.
• A combination of both (e.g. 3.2.1)