Check the data notes!

I know it’s boring, but some of the most useful information in the .id demographic tools is hidden away in a link at the bottom of each table. In profile.id, as well as having the exact wording of the Census question at the top right of each page, and beneath, the total population to which it refers, we include comprehensive data notes with each topic, to help you understand how to use it, where it comes from and how it’s put together.

Data notes, also known as “metadata”, are “data about data”. They explain everything from how the dataset is collected, to what the categories mean, to how you might use them, and any issues with the data you need to be aware of when making informed decisions based on them.

In profile.id and economy.id,  data notes are accessed via the “Explanatory Notes” section of the left-hand menu. This includes general notes about the Census, profile.id, different population types, randomisation of Census data, and the definition of the geographic areas. In addition, each table has specific notes accessed from the link directly below and to the right of the table, between the table and the charts.

So what can the data notes tell you? Generally, the specific table notes include:

• The Census question which was asked.
• What population it refers to.
• Any populations who are excluded from the topic.
• The make-up of any aggregated categories.
• Definitions for any terms which may be ambiguous.
• Any issues with comparing the dataset over time.
• The non-response rate (not stated), and a link to the data quality statement on the ABS website.

This can all help you make an “informed decision” about what the data is actually saying about the population you’re looking at.

For instance, in the example shown above, we’re looking at Housing Tenure in Parramatta. You can see from the dominant chart above, that Parramatta has a lot of rental, which includes social housing and private rental. These are defined in the data notes.

You can see from this that social housing is defined as both public housing rented from the government and community housing rented from a co-op, so a rise in this category could be from either of those sources.  You can also see a note on a change in wording of the question between 2001 and 2006, which means that if you compare tenure types to 2001 or earlier you may get an overcount of people in the “fully owned” category and an undercount in the “being purchased” category. These are the sorts of things you need to be aware of if you’re going to use this dataset.

In economy.id, data notes also give you comprehensive information about the different data sources used, as much of the data is not sourced from the Census. This includes the methodology by which the data modelling is done.

So if you’re scratching your head about a particular dataset and what it shows, don’t forget to check the data notes, there may be a simple explanation in there! But if you’re still confused, please feel free to call .id or send us an email. That’s what we’re there for.