DataCube Sources and Limitations

The FutureAbility DataCube (FADC) is an online interactive data platform that allows for the manipulation of variables in tabular, graphic and mapping formats. It brings together data from the following sources:

  • Australian Bureau of Statistics: Census 2011
  • Survey of Disability Aging and Carers (2009, 2012)
  • Australian Census and Migrants Integrated Dataset (2011)
  • National Disability Administrators: Small Area Estimates (2009)
  • Family and Community Services NSW: CIS 2012-2015
  • Department of Social Services: Payments Dec 2014
  • Department of Social Services – Settlement Reporting 2000 to 2014

The FADC is user-friendly and self-explanatory and is designed to be a tool that can allow the user to explore independently and acquire information using the available filters. For those who are planning to respond to the NDIS roll out in their jurisdiction, understanding how the distribution for state level estimations occurred within that state or territory, especially for minority populations is critical.

Estimates of the prevalence of disability across NSW have been captured and are presented in a way that highlight the ethnicity, disability type, religion, and preferred spoken language. It is important to note that this is quantitative data not qualitative.

The data is of various counts and estimates for people with disability from CALD backgrounds under 65 years. There are limits to what is possible in the FADC. One of the inherent limitations is the basis of the estimations used. They are based on the estimations produced by the Australian Bureau of Statistics small area estimates for the 2009, 2012 Survey of Disability, Ageing and Carers (SDAC).

The data is limited due to a lack of consistency and usability. It is not possible to have an absolute number of the estimations of ethnicity and disability because of the scarcity of available data regarding people with disability. In addition, differences in definitions, around disability types or ethnicity indicators, coupled with insignificant or inappropriate sample size may result in errors or limitations with the data collected.

FADC users can produce an expected estimation based on population distribution and density. There will be over-counting with some communities and under-counting with other communities. Thus there is the possibility that the estimate may be an undercount or an overcount, so a range is given based on a 95% probability within an upper and lower range. It is not possible to have an exact figure.

The FADC cannot provide commentary or analysis of all the data available due to the sheer volume of what is captured and presented. The data has been supplied in a Tableau format which is a data visualisation tool that enables the user to create custom queries, in particular, dataset (Rose, 2014).

Disability Groups Estimates

  • National prevalence rates for each disability group have been calculated by age and sex using data from the SDAC.
  • These rates have then been applied to the Disability Population Estimates at the LGA level to produce Low and High estimates for Disability Group Populations at the LGA level.
  • LGAs Disability Group Population Estimates have been aggregated to SA4 Regions and States to produce Low and High Estimates at the Regional and State Level.
  • Please note that in the SDAC respondents were able to choose more than one disability group.


These estimates should be used with caution as they are subject to a number of potential error sources, as listed below:

  • Around 6% of people did not answer the Core Activity Need of Assistance question in the Census.
  • Numbers from the SDAC contain a sampling error.
  • In applying national rates to LGAS, the methodology has accounted for variations in disability prevalence due to age and sex but not for other factors.
  • Aggregate numbers at the SA4 Regional and State levels are based on national rates.
  • The estimates do not include population variations from 2011-2012 to the present.
  • Errors will tend to be greater for areas with small populations.

Source: NDS, NSW branch Nov 2015.