High Level Principles for Data Integration - Statistical Integration - Why?
High Level Principles for Data Integration series
- High Level Principles for Data Integration
- About CPSIC
- Statistical Integration – why?
- PRINCIPLE ONE - Strategic Resource
- PRINCIPLE TWO - Custodian's Accountability
- PRINCIPLE THREE - Integrator's Accountability
- PRINCIPLE FOUR - Public Benefit
- PRINCIPLE FIVE - Statistical & Research Purposes
- PRINCIPLE SIX - Preserving Privacy & Confidentiality
- PRINCIPLE SEVEN - Transparency
- Statistical Data Integration
Statistical data integration involves integrating unit record data from different administrative and/or survey sources to provide new datasets for statistical and research purposes. The approach leverages more information from the combination of individual datasets than is available from the individual datasets taken separately. Statistical integration aims to maximise the potential statistical value of existing and new datasets, to improve community health, as well as social and economic wellbeing by integrating data across multiple sources and by working with governments, the community and researchers to build a safe and effective environment for statistical data integration activities.
Integrated datasets provide public benefits in terms of improved research, supporting good government policy making, program management and service delivery. Integrated datasets also create an important opportunity to expand the range of official statistics to better inform Australian society.