All source data files undergo some form of processing to extract them into a common format, see our main article on processing of sources for full details, however there are 4 sources which undergo some form of re-calculation of the original data:

• the Global Data Barometer,
• the GovTech Maturity Index,
• the International Survey of Revenue Administration, and
• the Open Data Inventory.

This article summarises the pre-processing we have undertaken of these sources, the source code for this processing is available on Github.

Global Data Barometer

The D4D.net and ILDA Global Data Barometer attributes its underlying data to both 4 “pillars” (availability, capability, governance, and use and impact) and 7 “modules” (capabilities, climate action, company information, governance, health & covid, land, political integrity, public finance, and public procurement). The re-processing of the Global Data Barometer extracts and aggregates the data for each of the governance and capabilities pillars to create two overall scores for each country, it then aggregates the remaining data on availability and use & impact by module to create seven further scores for each country relating to each module.

The 9 variables extracted from the re-processed Global Data Barometer data cover:

• Climate data availability – sum of the availability scores relating to climate data
• Company data availability and impact – sum of the availability and impact scores relating to company data
• Data capability – sum of the scores relating to data capability measures
• Data governance – sum of the scores relating to data governance measures
• Health data availability – sum of the scores relating to health data
• Integrity data availability and impact – sum of scores relating to the availability and impact of integrity data
• Land data availability and impact – sum of scores relating to the availability of land data
• Procurement data and impact – sum of scores relating to the availability and impact of procurement data
• Public finance data availability – sum of scores relating to finance data availability

GovTech Maturity Index

The World Bank’s GovTech Maturity Index (GTMI) provides a detailed assessment of national governments digital government policies, technologies and digital public services. The high-level results of the GTMI are outputs from a factor analysis of the raw input data, it is therefore not easy to directly identify from the overall results how countries can take action. Furthermore, in addition to its own questionnaire (completed by government officials or World Bank researchers in the case of non-response) the GTMI incorporates some data from other sources which are either already used by the Blavatnik Index of Public Administration (in the case of the ITU’s Global Cybersecurity Index) or have been rejected for inclusion (components of the UN’s E-Government Development Index). The GTMI data is therefore re-processed to extract its own aggregates of the original raw data.

The variables 7 extracted from the re-processes GTMI data cover:

• Administrative IT systems – the existence and nature of IT systems for administration (HR, payroll, financial management and e-procurement)
• Back-end technologies and infrastructure – the existence and extent of enabling technologies and frameworks (cloud computing, enterprise architectures, service busses, interoperability frameworks)
• Digital methods for public participation – the existence of digital tools to enable public participation and feedback
• Digital services and technologies for end-users – the existence of end-user service portals and related technologies (e-payment and digital signatures).
• Open government and data portals – the existence and nature of any open government portals and open data repositories
• Strategy and policy for digital government – the approach to and policies in support of digital government (strategy documents, institutional structures, open source policies, data privacy laws and institutions, support for skills development)
• Support for digital innovations within government – the existence of any policies and practices encouraging digital innovation (innovation strategy, institutional structures, support for digital SMEs).

International Survey of Revenue Administration

The International Survey of Revenue of Administration (ISORA) is collected and published by the Inter-American Center for Tax Administration [CIAT]; the International Monetary Fund [IMF]; the Intra-European Organization of Tax Administrations [IOTA]; and the Organization for Economic Co-operation and Development [OECD]. The ISORA dataset provides in-depth information about tax collection and operations from 172 tax agencies, the re-processing of the data in order to calculate proportions, coerce categorical data into numerical values, and exclude outlier values.

The 14 variables extracted from the re-processed ISORA data cover:

• Administrative costs (% of revenue) – the administrative operating costs of the tax agency as a proportion of net revenue
• Corporate tax (% filed on-time) – the number of corporate tax returns filed on time as a proportion of all corporate tax returns
• Corporate tax (% paid on-time) – the number of corporate tax returns paid on time as a proportion of all corporate tax returns
• Electronic filing: corporate tax – the number of corporate tax returns filed via an electronic method as a proportion of all corporate tax returns
• Electronic filing: personal tax – the number of personal tax returns filed via an electronic method as a proportion of all personal tax returns
• Electronic payments (%) – the volume of payments made electronically as a proportion of all payments, of the value of payments made electronically as a proportion of the value of all payments (if volume not available).
• Personal tax (% filed on-time) – the number of personal tax returns filed on time as a proportion of all personal tax returns.
• Personal tax (% paid on-time) – the number of personal tax returns paid on time as a proportion of all personal tax returns
• Proportion of all tax officials that are female – the number of officials that are female as a proportion of all officials
• Proportion of senior tax officials that are female – the number of senior officials in that are female as a proportion of all senior officials
• Proportion of service contacts via digital channels – the number of service contacts via a digital method (online account and chat/digital assistance tools, but not including email) as a proportion of all service contacts (including email)
• Tax debt (% of revenue) – the value of tax arrears as a proportion of net revenue
• Turnover of tax agency staff – the change in the number of staff in the reporting year as a proportion of the average number of staff for the reporting year
• Use of innovative practices and technologies by the tax administration – the extent to which the tax agency is using or putting in place any of 10 practices or technologies (behavioural insights; distributed leger technologies; artificial intelligence or machine learning; cloud computing; data science and analytics; automation; API services; whole of government ID; digital identification technologies; virtual assistants/chatbots).

Open Data Inventory

The Open Data Watch’s Open Data Inventory (ODIN) measures the coverage and openness of official statistics across a several different categories of social, economic and environment statistics. The raw data is processed to calculate a coverage and openness score for each of these three sets of statistics.

The 6 variables extracted from the re-processed ODIN data are:

• Economic statistics coverage
• Economic statistics openness
• Environmental statistics coverage
• Environmental statistics openness
• Social statistics coverage
• Social statistics openness