I previously shared about the current Federal review of innovation indicators<\/a>, the global OECD Entrepreneurship indicators program<\/a>, and the Innovation and Science Australia\u2019s\\2016 review<\/a> of the national innovation system. In addition to those reviews, the DIPA program is establishing more robust and reliable data sources for improved policy development and industry and government decision making. Other documents related to the program include recommendations in the 2016 Public Sector Data Management Implementation report<\/a> and observations in the 2015 Department of the Prime Minister and Cabinet\u2019s submission to the Productivity Commission\u2019s Inquiry into Data Availability and Use<\/a>.<\/p>\n\n\n\n I am making my way through considering how nations approach data and information related to innovation and entrepreneur support. These posts act as a personal daily reference point as I aim to simplify what can seem complex on initial glance. It can help to document concepts in succinct daily post for public consumption. If others find value through the process, all the better.<\/p>\n\n\n\n The scope and scale of the DIPA program is significant. The structure includes: governance, administration, and technical input; creation of data assets; development of data integration assets; and data analytical units to utilise the data. The program provides a graphic to explain the program, included below.<\/p>\n\n\n\n I came across another diagram developed as part of a presentation by Strategic Policy & Data Analytics<\/a>, which adds in budgets for each of the components:<\/p>\n\n\n\n The process of creating diagrams can help make sense of the program and who is involved. I developed the one below to walk through the different aspects of the program:<\/p>\n\n\n\n The DIPA project sits under the Secretaries\u2019 Data Group, and is governed by a DIPA Board. Data 61 which is the data arm government research entity CSIRO provides technical review and advice, and the Department of Premier and Cabinet manages communication and engagement.<\/p>\n\n\n\n The program is building or supporting a series of data assets from different areas of health, education, finance, social services, and intelligence. Some assets appear to have been already in development, others were created as part of the project, and some there is little information apart from the initial announcement.<\/p>\n\n\n\n The Connected Health Data (CHD) Program<\/strong><\/a> with the Department of health aims to:<\/p>\n\n\n\n The Department of Social Service\u2019s Data Exchange<\/strong><\/a> was released in 2014 and was \u201cdeveloped to improve the way we collect and use administrative data to improve the wellbeing of people and families in our communities.\u201d<\/p>\n\n\n\n The Department of Education\u2019s $14.3 million National Education Evidence Base (NEEB<\/strong>) program<\/a> commenced in 2017 and is designed to<\/a> \u201cdraw together data on all aspects of education\u2014 early childhood education and care, schools, vocational education and training and higher education to be a resource available to staff to provide easy access to the data and analysis needed to inform policy and decision making.\u201d The program is in response to the increasing costs of education in Australia without corresponding improvements in education, as outlined in the 2018 Productivity Commission Inquiry Report<\/a>.<\/p>\n\n\n\n There is little online about the Finance Department\u2019s Secure Information Sharing Capability (SISC)<\/strong> program, apart from a 2017 news reference<\/a>.<\/p>\n\n\n\n The Digital Transformation in National Security Program<\/strong> was intended to investigate modernising and transformative benefits across the national security community. Similar to the SISC, there is little reference to the current program apart from the initial announcement.<\/p>\n\n\n\n Two organisations are funded to act as Accredited Integrating Authorities to \u201censure integrated data is de-identified, confidentialised and analysed in safe, secure and controlled environments.\u201d These are the Australian Institute of Health and Welfare (AIHW) and the Australian Bureau of Statistics (ABS).<\/p>\n\n\n\n Four integration platforms are included in the initial DIPA program:<\/p>\n\n\n\n The Multi-agency Data Integration Project (MADIP)<\/a> is \u201ca partnership among Australian Government agencies to develop a secure and enduring approach for combining information on healthcare, education, government payments, personal income tax, and population demographics (including the Census) to create a comprehensive picture of Australia over time.\u201d<\/p>\n\n\n\n The Business Longitudinal Analytical Data Environment (BLADE)<\/a> combines business tax data and information from ABS surveys over time to provide a better understanding of Australian businesses and the economy.<\/p>\n\n\n\n Examples of projects are listed for both BLADE<\/a> and MADIP<\/a>. The platforms share projects in many instances and there is a reasonable view that the integration platforms could be combined in the future.<\/p>\n\n\n\n The projects touch on all aspects of society and examine many of the complex issues that can be informed by data, including indigenous health, complex economic company structures, suicide rates, water use, innovation impact, and much more. An example specific to my personal focus area of entrepreneurship and innovation, Sasan Bakhtiari release two papers outlining Entrepreneurship Dynamics in Australia: Lessons from Micro-data in 2017 <\/a>and 2019<\/a>.<\/p>\n\n\n\n A more in depth review to map these projects will be valuable, but perhaps in a future post.<\/p>\n\n\n\n From a 2015 blog on data.gov.au<\/a>, a linked employer and employee dataset is designed to:<\/p>\n\n\n\n Justification for a LEED was demonstrated in a 2015 ABS research paper<\/a> and is an ongoing project with the ABS<\/a> to \u201csimultaneous analysis of met supply and demand in the Australian labour market.\u201d<\/p>\n\n\n\n A visual description of the LEED structure<\/a> from the ABS is below:<\/p>\n\n\n\n The Location index<\/a> commenced in 2018 and provides \u201ca framework that provides a consistent way to seamlessly integrate data on people, business, and the environment. Location Index aims to extend the characteristics of the foundation spatial data of taking geospatial data (multiple geographies) which is essential to support public safety and wellbeing, or critical for a national or government decision making that contributes significantly to economic, social and environmental sustainability and linking it with observational data. Through providing the infrastructure to support cross-domain foundation data linkages and analysis will open up substantial opportunity for providing a richer set of information to develop, analyse and evaluate policy, programs and service delivery by government. \u201c<\/p>\n\n\n\n The DIPA then supports five data analytical units to leverage the data integration platforms for specific aspects of society: Whole of government policy, Social welfare, Physical, Economy, and Government business data.<\/p>\n\n\n\n The Central Analytics Hub<\/a> is focused on policy<\/strong>, with an aim to \u201cuse integrated data to generate insights about complex policy questions in areas of government priority. These include projects focusing on whole-of-government priority policy issues, informing taskforces, policy development and other government processes.\u201d<\/p>\n\n\n\n Examples of projects include exploring the gender pay gap<\/a> and the national drought map<\/a>.<\/p>\n\n\n\n The Economic Data and Analysis Network (EDAN)<\/a> is focused on economic <\/strong>impact and \u201cis generating new insights into the operation of the economy and evaluating the performance of policies, programs and services that impact on business.\u201d<\/p>\n\n\n\n The project sits in the Department of Industry, Innovation, and Science<\/a> and produced the previously mentioned papers on Entrepreneurship Dynamics in Australia: Lessons from Micro-data in 2017 <\/a>and 2019<\/a>.<\/p>\n\n\n\n The Government Business Analytical Unit (GBAU) focuses on government data<\/strong>, \u201ccreating efficiencies and reduce duplication in collecting, creating and analysing government business data.\u201d<\/p>\n\n\n\n Headed up by the Department of Finance in 2018, the platform was credited in the Department\u2019s 2018-2019 budget report<\/a> as growing the Department\u2019s \u201ccapability and increased the use of data to inform public sector policy and government administration. New data analytics expertise and investment in technology is enabling Finance to use data, including from across the APS, in a more sophisticated way to build an evidence base, inform policy-making, and enhance reporting and transparency including through analysis of APS Employee Census data.\u201d<\/p>\n\n\n\n Plans for 2019-2020 include:<\/p>\n\n\n\n Physical Environment Analysis Network<\/p>\n\n\n\n The Physical Environment Analysis Network<\/a> program focuses data relating to the physical environment <\/strong>to \u201cenable faster and more comprehensive responses to current policy issues, such as building community resilience to natural disasters, links between urban environmental quality and heath and the effects of changing energy prices on businesses and regional communities.\u201d<\/p>\n\n\n\n Established in 2017, the program has working on projects relating to the Northern Territory, Water and society, Natural disasters, Energy, and Gas. Current projects include:<\/p>\n\n\n\nDIPA program details<\/h2>\n\n\n\n
![\"\"\/](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/dipa-overview.png\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/renando.com\/wp-content\/uploads\/2020\/01\/image-63-1024x682.png\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/renando.com\/wp-content\/uploads\/2020\/01\/Data-Integration2-1024x833.jpeg\")
<\/figure>\n\n\n\n1. Governance and administration<\/h2>\n\n\n\n
2. Data assets<\/h2>\n\n\n\n
Health<\/strong><\/h3>\n\n\n\n
Social services<\/strong><\/h3>\n\n\n\n
Education<\/strong><\/h3>\n\n\n\n
Finance<\/strong><\/h3>\n\n\n\n
Intelligence<\/strong><\/h3>\n\n\n\n
3. Data integration<\/h2>\n\n\n\n
i. Multi-agency Data Integration Project (MADIP)<\/h3>\n\n\n\n
ii. Business Longitudinal Analytical Data Environment (BLADE)<\/h3>\n\n\n\n
BLADE and MADIP Projects<\/strong><\/h3>\n\n\n\n
iii. Longitudinal Linked Employer and Employee Dataset (L-LEED)<\/h3>\n\n\n\n
<\/figure>\n\n\n\n
iv. Location Index (Loc-I)<\/h3>\n\n\n\n
![\"loci](\"https:\/\/renando.com\/wp-content\/uploads\/2020\/01\/lociDiagram-1024x786.png\")
<\/figure>\n\n\n\n4. Data Analytical units<\/h2>\n\n\n\n
Central Analytics Hub<\/h3>\n\n\n\n
![\"Central](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/cah-logo.jpg\"){kind=logo}
<\/figure>\n\n\n\nEconomic Data and Analysis Network (EDAN)<\/h3>\n\n\n\n
![\"Economic](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/edan-logo.png\"){kind=logo}
<\/figure>\n\n\n\nGovernment Business Analytical Unit (GBAU)<\/h3>\n\n\n\n
![\"Government](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/gbau-logo.png\"){kind=logo}
<\/figure>\n\n\n\n![\"Physical](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/pean-logo.png\"){kind=logo}
<\/figure>\n\n\n\nSocial, Health and Welfare Analytical Unit<\/h3>\n\n\n\n
![\"Social,](\"https:\/\/www.pmc.gov.au\/sites\/default\/files\/images\/shwau-logo.png\"){kind=logo}
<\/figure>\n\n\n\n