High Level Principles for Data Integration - Principle Four - Public Benefit
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 integration should only occur where it provides significant overall benefit to the public.
This principle ensures there is a demonstrated ability to produce significant outputs from the integrated dataset and an independent assessment is made that the public good outweighs the privacy imposition and risks to confidentiality.
There should be a demonstrated ability to produce significant outputs from the integrated dataset. There should be an independent assessment of the balance of public good against the privacy imposition and risks to confidentiality. Examples include community representation on the steering committee, the use of an ethics committee, or the use of an advisory committee with community representation and the ability to report independently of the agencies involved in the proposal.
Ongoing programs should be reviewed on a three yearly basis to ensure a continuing overall benefit.