The challenges of physical addressing for NBN deployment

Brian BeckorDirectorCallpoint Spatial Pty Ltdwww.callpointspatial.com.au Comms Day SummitSydney, 9th April 2013

Overview

• Review NBN Co public statements• Describe the G-NAF build process• Outline key issues• Examples of continual improvement

About Callpoint Spatial

• Geospatial resources to 30 Aust telcos since 2000

• ACMA and DCITA projects• Broadband reports for 70 LGAs• Web services Geocoder• AQ Pro for telcos• (Much of above with PSMA G-NAF)• Full Access PSMA VAR

#1: Mike Quigley, CEO NBN Co (Senate Estimates, May 2012)

• When we try to use the (PSMA G-NAF) data there are a number of inconsistencies in it for our use. It is obviously a very useful dataset but it is not quite what we need to do this job

• We have cases where many addresses are assigned to a single point, often in the centre of a street. This is particularly an issue in the case of multi-dwelling units, such as blocks of flats and office blocks. It could be that anything up to about 30 per cent of the details we get in those files are inaccurate

• This level of data inaccuracy means we have to take more time in the design stage to clean up the data. We have also been directing our contractors to walk down every street in every FSAM in order to verify addresses. This is time consuming, costly and itself prone to error

• I should say that we are not in any way criticising the PSMA data. It is a very good dataset. That is just the reality of the complexity of dealing with a database that is trying to capture every address in the country

#2: Gary McLaren CTO NBN Co(NBN Realised forum, Nov 2012)

What is G-NAF(Geocoded National Address File)

What is PSMA G-NAF• Australia’s authoritative, structured, rich

meta-data, most comprehensive and accurate national geocoded address dataset

• Data Contributors:– Australia Post– Australian Electoral Commission (AEC)– State/ Territory land mapping agencies

• Full data release each quarter • Continual improvement by PSMA

The G-NAF build process

G-NAF build process• Multi-stage build - simplified description:

– Data imported – 200,000 business rules e.g. convert Fairybower Rd

Manly to Fairy Bower Rd Manly– Validate against reference datasets– Merge the addresses – must match 11 key fields

• “Confidence” column indicates match result:– “2” – all three contributors supplied the address– “1” – only two contributors supplied the address– “0” – only one contributor supplied the address

The Confidence 2 Universe

Direct match all three sources

Matched through current rules

Potentially matched through achievable new rules or effort with existing Data Contributors

Source data unavailable from current Contributors e.g.• AEC data largely doesn’t include commercial/ industrial/

government addresses• Aust. Post can lack vacant land data• Mapping agencies can lack private estate etc. data

Theoretically possible

= 61%+

= 39%+ +

Specific match challenges

• Ranged/ complex addresses• multi-dwelling units• Dual frontage properties• Aliases• Prefix/ suffix e.g. 17A vs 1/17• Timing mismatch re new address creation• 1:1 address: land parcel in 80% of cases• these and other complexities…

Examples of how PSMA has lifted:* Street to parcel level geocode

* Confidence 1 to 2

Example lift from street to parcel levelAugust 2012 November 2012

Map legend:Green circle – Property level geocode - Confidence 2Yellow triangle – Property level geocode – Confidence 1Red triangle – Property level geocode – Confidence 0Purple circle – street level geocode

Bathurst, NSW

Source: PSMA

Example lift from Confidence 1 to 2

Map legend:Green circle – Property level geocode - Confidence 2Yellow triangle – Property level geocode – Confidence 1Red triangle – Property level geocode – Confidence 0Purple circle – street level geocode

November 2012 February 2013

Cunningham, SA

Source: PSMA

Address confidence improvement

Summary G-NAF confidence of principal addressesConfidence level Aug-04 Nov-09 Feb-13

2 43.9% 58.1% 61.3%1 20.5% 17.7% 16.5%0 35.6% 24.2% 22.2%

National statistics

August 2004 – first G-NAF updateNovember 2009 – update post NBN Co establishment

Geocode reliability improvement

Summary G-NAF geocode reliability of principal addressesGeocode reliability Aug-04 Nov-09 Feb-13Within site boundary 82.2% 91.0% 93.0%Gap geocoded 1.9% 1.4% 1.2%Street level 11.4% 7.1% 5.4%Locality level 4.3% 0.5% 0.4%

National statistics

August 2004 – first G-NAF updateNovember 2009 – update post NBN Co establishment

Strategies to increase the match rate

• Continued proactive PSMA approaches– Data Contributor workshops– Business rule refinement– Web notification services/ G-NAF Live

• Provide resources/ expertise to jurisdictions where needed most

• Improve Local Council access to private development data

• Introduce new Data Contributors

Conclusion

• Important to understand how G-NAF is built, the role of meta-data and supporting tables

• Need to devise strategies to tackle the issues• Enhanced datasets and services to help• PSMA continually improves G-NAF• G-NAF is Australia’s best available national

geocoded address dataset