The geocoded address database for Australian businesses and governments.

PSMA’s G-NAF dataset contains all physical addresses in Australia. It’s the most trusted source of geocoded addresses for Australian businesses and governments.



G-NAF Metadata Statement

More Information

G-NAF is built from addresses supplied by 10 contributors, including the land agencies in each state and territory of Australia.
The source data is:

  • Independently examined and validated.
  • Matched textually and spatially.
  • Assigned a geocode to place the address on a map.

Over 30 million contributed addresses are distilled into more than 14.6 million G-NAF addresses.

G-NAF is a complex dataset combining data from multiple sources into one comprehensive dataset. Metadata for each of the 14.6+ million principal addresses enhances the usability of G-NAF. This metadata captures:


Principals and aliases

Addressing is complex and sometime the same property might be identified by multiple address labels. For example, an apartment block may be listed as 5–7 Smith Road or 5 Smith Road or 1A & 1B can be confused with units 1 and 2. The G-NAF production process identifies these relationships and produces information linking the variations that exist between the addresses that people use and official addresses created by governments. The address provided by the government custodian is generally considered the principal and any other addresses are known as aliases.


This is a set coordinates or longitude and latitude values which enable the location of the address to be shown on a map. A geocode facilitates further manipulations, such as calculating the distance between the address and another point, such as understanding if an address is inside a catchment or risk areas or finding the nearest delivery vehicle for job allocation. All addresses in G-NAF are linked to coordinates with over 96% of addresses in G-NAF (including aliases) having a geocode placing them inside the associated property boundary.

Mesh block identifier

A mesh block is the smallest geographic region used by the Australian Bureau of Statistics. The application of a mesh block ID to each G-NAF address (including a quality placement indicator) facilitates linkages to relevant demographic and socioeconomic data.

Confidence levels

Each address is given a confidence level to indicate how many contributors support it. Not all contributors are exposed to all addresses, for example, jurisdictional addresses may not cover all private estate and complex addresses. If an address is no longer supplied by any contributor, it is given a negative rating. These addresses remain accessible in the dataset for specific use cases.

Primary and secondary

Addresses that contain sub-addresses, for example, a block of units or townhouses, have flags to denote the primary (e.g. 10 Smith Street) and secondary (e.g. Unit 6).

Unique persistent identifier

Each G-NAF address is allocated a unique identifier, or the G-NAF PID, which persists with the address label in the dataset. This enables information across different systems, departments or organizations to be shared based on a common address. Should the address label change a linking relationship between the old and the new address is provided in the dataset

G-NAF helps answer everyday questions about location. A well-defined location is not just an address, it’s how a place is described. G-NAF is widely used to support many businesses and governments with:

Profiling – to build profiles of suburbs and wider areas by combining G-NAF data with social, demographic, economic and environmental data.

Improved policy and services – to enable organisations to develop more accurate socioeconomic and demographic trend analysis for policy development and service delivery.

Find nearest – to show internet or mobile phone users the nearest provider of a service or retailer.

Emergency management – to identify and map areas under threat, recognising evacuation routes, and direct emergency services first responders.

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Get this dataset under open data terms from data.gov.au.