1. Integrated Data Infrastructure (IDI) Project manager – Guido Stark June 2012 Linking data across government How Statistics New Zealand maintains privacy in large scale data integration projects

2. 2008 LEED – MSD Benefit data 2010 EOTE + secondary education data Person to Business Link 2009 Employment Outcomes of Tertiary Education (EOTE ) 2 EMS Self-employed IR Person to Business Link EMS Self-employed IR History Benefits MSD (BDD) Person to Business Link 2005 Linked Employer-Employee Data (LEED) 2004 Student Loans (SL) Education Tertiary MoE Student Loans IR MSD (StudyLink) SLAM 2007 Student Loans and Allowances (SLA) Education Tertiary MoE Student Loans & Allowances IR MSD (StudyLink) SLAM 2007 Prototype Longitudinal Business Database LBD EMS Self-employed IR Education Tertiary MoE Education Secondary MoE Education Tertiary MoE 2011 LEED – Household Labour Force Survey (HLFS) HLFS Stats NZ Person to Business Link EMS Self-employed IR

3. Lead the Official Statistics System Responding to customer needs Obtain more value from official statistics Transform the way we deliver statistics Maximise the use of administrative data Increase use of data integration Create a responsive, customer-focused, influential, and sustainable organisation Data integration raises real and perceived privacy risks 3 Statistics 2020 – Te Kāpehu Whetū Achieving the statistical system of the future

4. 4 Integrated Data Infrastructure (IDI) Project manager – Guido Stark

5. Data Integration Policy Four key principles 5 1. The public benefits of integration outweigh both: privacy concerns about use, and risks to the integrity of the Official Statistics System or other activities of government 2. The integrated data will only be used for statistical or research purposes 3. The data integration will be conducted in an open and transparent manner 4. Data will not be integrated where an explicit commitment has been given to respondents that would preclude such action.

6. Safe Data The triangle 6 Privacy ConfidentialitySecurity

7. IDI security Secure workspaces Limited access Access control Regular audits of access and use Output control 7

8. IDI confidentiality Encryption / transformation IDI rules Aggregating Rounding Suppression Output checking Statistical vs operational 8

9. IDI privacy Privacy Impact Assessment www.stats.govt.nz/IDI Risks Information used in a way that is detrimental to their personal circumstances Information might be released that identifies them and aspects of their personal circumstances Unrelated information might be collected about them in an ever-growing database for non-specific purposes (i.e. ‘Big Brother’). Benefits Potential for new official statistics Provides an evidence base for research, evaluation, and policy formulation Meets Statistics NZ’s strategic priorities

10. Data Integration Policy The Privacy Act 1993 Principle 1: Purpose of collection of personal information Principle 2: Source of personal information Principle 12: Unique identifiers The Statistics Act 1975 Section 3: Official statistics and coordination Section 15: Independence of the Government Statistician Section 37: Security of Information Section 21: Declaration of secrecy 10

11. Information flows SNZ derived unique identifier available Source data Load source data Clean source data Create link tables Linking Create core tables Restricted access in accordance with Statistics NZ’s Security Framework Access for bona-fide statistical purposes to required data sources only Clean source data Core tables Names, addresses, date of birth removed Unique identifiers are encrypted Outputs Confidentiality checks

12. Safe Data The triangle 12 Privacy ConfidentialitySecurity Safe outputSafe access Safe projects Safe researchers

13. Use of the IDI Developing regular measures of immigrant outcomes Developing tertiary education outcome indicators How successful is NZ in retaining qualifications Intellectual property and productivity Mapping post-compulsory school pathways and outcomes The impact of immigration on the labour market The influence of education on outcomes What is the impact of gaining qualifications for beneficiaries Who doesn’t participate in tertiary education Benefit to work transitions The effect of wage subsidies on individual and firm employment

14. Secondment Statistics NZ datalab Legal compliance Bona fide research Non-regulatory Proven researcher Confidentiality Suitable data source Access Making the most of the IDI

15. 15 Business data Person to business link Education secondary & tertiary MoE EMS Self-employed Inland Revenue Student Loans & Allowances Inland Revenue MSD (StudyLink) SLAM HLFS / NZIS Survey Benefits MSD (BDD) Outputs Relevant releases Dynamic datasets Cutting edge cubes Powerful research Central Linking Concordance (CLC) Migration data DoL LBD LEED Integrated Data Infrastructure (IDI) ? ? ? ?

16. Questions? IDI Project manager – Guido Stark June 2012 guido.stark@stats.govt.nz