Data Innovation Hub
In October 2020, the ABS established the Data Innovation Hub (DIH) initiative to help build enterprise capability in the innovative use of traditional and emerging data sources for official statistics. The DIH will bring together multidisciplinary teams of ABS methodologists, data scientists, technologists, and statistical subject matter experts to pilot new data solutions to improve the production of national statistics and provide new insights to government. Such solutions involve not only new data types and providers from across government, industry and academia, but also the methods and systems needed to systematically acquire, access, combine and analyse them.
The priorities, scope and objectives of innovation activity undertaken by the DIH will align with a set of Innovation Drivers that advance the strategic data capabilities of the ABS:
- Utilising non-traditional data sources – leveraging the information value of emerging ‘big data’ for statistical purposes, particularly in combination with existing administrative data sets.
- Delivering new information solutions – producing new analytical insights into current and emerging economic, social and environmental phenomena.
- Improving the statistical production process – automating or otherwise enhancing selection, coding, imputation, editing, and estimation processes.
- Combining heterogeneous multisource data – associating and resolving observations of statistical entities over multiple disparate data sets.
- Recognising patterns and correlations in data – identifying significant factors associated with a certain concept, and detecting outliers, anomalies, and spatial and temporal features in data.
- Protecting personal and sensitive data – applying privacy-preserving data transformations and models that minimise the loss of analytical utility.
The DIH will progress three significant projects in the first tranche of its work program to July 2021:
- Produce a monthly indicator of household final consumption expenditure (HFCE), using financial transactions data.
- Analyse changes in trade performance due to the disruption in global supply chains and the global economic downturn caused by COVID-19, using merchandise trade records and business activity statements.
- Analyse the effect of reduced business activity due to COVID-19 on employment and jobs, using payroll records, business activity statements, social security payments and job advertisements.
A key objective of these projects is to quickly produce experimental outputs that demonstrate the value of new data sources and methods, and to set out a clear a path to ongoing production. A second objective is to help build a technical environment that can support more effective and timely provision of information to policy makers.
For more information, please contact Ric Clarke at email@example.com.
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