Foundation spatial data now a ‘must use’ for NSW

By on 26 March, 2025
A computer-generated image of streams of data, representing the FSDF
Image credit: ©stock.adobe.com/au/Quardia Inc.

NSW has announced that the Foundation Spatial Data Framework (FSDF) has been endorsed as the state’s first Core State Digital Asset (SDA).

The endorsement was achieved following a comprehensive assessment process that followed the governance set out in the SDA Reuse Policy.

SDAs are sets of data or digital tools used by multiple NSW government agencies to deliver services.

According to Digital NSW, some of the SDAs already in place are “delivering benefits through modern licensing, digital identity, payments processing and consolidated financial systems, collectively forecasted to deliver over $1 billion in benefits”.

The FSDF itself is “a structured and standardised system for organising, managing, and sharing spatial data” comprising “approximately 300 datasets clustered into 10 broad themes, providing state-wide coverage of the best available, current, and authoritative spatial data”.

Those 10 current themes are:

  • Administrative boundaries
  • Land parcel and property
  • Geocoded addressing
  • Transport
  • Positioning
  • Place names
  • Elevation and depth
  • Imagery
  • Water
  • Land cover

NSW FSDF data is generally accessed in one of three ways:

  • Through the Spatial Collaboration Portal, a centralised delivery mechanism;
  • The Incremental Feed service, which provides nightly data updates to key customers; and,
  • Monthly deliveries that provide extracts of the FSDF datasets at a set point in time.. 

The endorsement milestone means that NSW government agencies will be able to build spatial datasets upon a unified base, with the aim of developing seamless connections across disparate services.

According to Digital NSW, “agencies must use this asset when the spatial datasets comprising the FSDF are required”.

NSW government agencies can access the FSDF datasets free of charge, although they might incur their own costs when analysing the data.

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