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As the 2030 deadline for the Sustainable Development Goals (SDGs) approaches and the international community grapples with the impacts of a global pandemic, climate change, and multiple humanitarian disasters, the need for better data is greater than ever before. Since our founding, Open Data Watch (ODW) has advocated for resilient statistical systems that make data openly available to facilitate evidence-informed policymaking and good governance.
The Open Data Inventory (ODIN) provides the basis for monitoring global progress on the availability and accessibility of official statistics, engaging countries through technical assistance workshops, and advocating for better resources for data systems across sectors and geographies. Advocacy and country engagements by ODW and many partners has led the United Nations Statistical Commission to endorse “open by default” as a principle of official statistics. The ongoing evolution of national statistical organizations as “data stewards” will draw more attention to the importance of how open data are produced and used. We thank all countries and partners for working with us and look forward to an even brighter future for open data.
We hope you find the resources of ODIN and this biennial report useful. Please send any comments and feedback to email@example.com.
Managing Director, Open Data Watch
The Open Data Inventory (ODIN) provides an objective measure of the state of official statistics and serves as a guide to national statistical offices (NSOs) as they build and strengthen their statistical systems to better serve policymakers, journalists, academics, and the public. In its sixth edition, the 2022/23 ODIN includes 192 countries, a net increase of 5 countries from the previous edition. The data from 6 rounds of ODIN record the progress countries have made in building sustainable statistical systems that are open and accessible to users. But this year, for the first time, ODIN 2022/23 finds evidence of reduced data availability and weak growth in openness. Since the last ODIN assessment in 2020, the median score of all countries has increased by 1.8 points, the smallest increase since 2017, and 86 countries—almost half—have lost ground. This report investigates the causes and dimensions of this setback. It also finds many cases of exemplary progress by countries in every part of the world.
Many factors affect the scores of a country. For the 2022/23 round, the impact of the COVID-19 pandemic must be acknowledged. The ODIN 2020/21 assessments took place just as COVID-19 was spreading around the globe. Many NSOs struggled to adapt to working remotely, but they were still working with data collected prior to the pandemic. According to the United Nations Statistics Division (UNSD) and the World Bank, 96 percent of countries limited or stopped face-to-face data collection in May 2020. These disruptions persisted in 57 percent of countries the following year. The 2022/23 ODIN assessments clearly reflect the impact of these disruptions, particularly in countries without experience in remote data collection, signaling a strong need for increased investment to build resilient data systems. Recovery and further progress will require investments in staff and technology and a commitment to open data that serve the needs of all users.
RESULTS AT A GLANCE
Figure 1. ODIN Overall Scores, 2022
How to use this figure: Use the (+) and (-) buttons to zoom in and out. Hover over each country to reveal the name. Click a country to see a summary of scores. Clicking the country’s name will redirect you to the Country Profile page on the ODIN website.
The map boundaries used by ODW are for analytical work. The boundaries, colors, denominations, and other information shown on any map used in ODIN do not imply any judgment on the part of ODW concerning the legal status of any territory or the endorsement or acceptance of such boundaries.
ODIN 2022/23 overall scores ranged from 1.5 to 90. Figure 1 shows the scores for each country included in ODIN 2022/23. Hover over a country to see its coverage, openness, and overall scores or click the country name to see a detailed profile of its scores and comparisons with previous years.
More countries were included in ODIN 2022/23, but many lost ground.
More countries have made their data available online. ODIN 2022/23 includes 192 countries, a net increase of 5 from 2020/21: 7 are new to ODIN, 2 returned after an absence, and 4 countries were dropped from the assessment because their websites could not be reached. The median overall score of all countries has continued to improve, but 86 countries lost ground, and there is evidence that the rate of progress has slowed.
Data openness improved but coverage scores fell.
In 2022 official statistics were more accessible, but data for many indicators became less available. The median ODIN openness score, which measures the accessibility of official statistics, reached 53.9, 1.8 points higher than in 2020 for comparable countries. The median ODIN coverage score, which measures the availability and completeness of official statistics fell by 1.6 points to 46.8.
Changes in methodology in ODIN 2022/23 may have contributed to the decline in coverage scores. These include requiring more indicators to have sex disaggregated data and modifications to the energy category that require datasets to report on more than just electricity supply and consumption. Likewise, changes in the scoring of the openness elements have contributed to an increase in the median openness score of 1.6 points. Without the change in methodology, the median openness score would have remained essentially unchanged from 2020. See the Methodology section for further information.
Median scores for the 165 countries that have participated in all 5 ODIN assessments since 2016 are shown in Figure 2. In 2017, as in 2022, methodology changes contributed to a drop in coverage scores, but scores rebounded in 2018, slowed in 2020, and fell in 2022.
Figure 2. Median coverage, openness, and overall ODIN scores, 2016-2022
How to use this figure: Hover over the data points to see the data values. Click the score types in the legend to remove or add them from the graph.
The section on Coverage and Openness provides further discussion of the factors driving these changes.
Economic and financial data remain the most available and most open.
ODIN assesses the coverage and openness of 22 categories of statistics in 3 major categories: Social Statistics, Economic and Financial Statistics, and Environmental Statistics. Figure 3 shows how these major category scores have changed over time for the 165 countries that have appeared in every ODIN assessment since 2016. The Economic and Financial Statistics category has consistently received the highest overall scores in ODIN assessments, both for coverage and openness. The Social Statistics overall score fell in 2017 due to methodological changes, but scores have risen by almost 9 points since 2016, adding a full point since 2020. Environmental Statistics surpassed Social Statistics in 2018 but decreased by 1.2 points in 2022. This reflects a significant challenge that countries must overcome, particularly as they work to measure risk factors and plan strategies for climate change mitigation and adaptation.
Figure 3. Median ODIN scores by major data categories, 2016-2022
How to use this figure: Hover over the data points to see the data values. Click the data categories in the legend to remove or add them from the graph.
The Sectoral Analysis section provides further discussion of the factors driving these changes.
Low- and middle-income economies have fallen farther behind.
Income, measured by gross domestic product (GDP) per capita, is an imperfect but significant indicator of the resources available to the national statistical system (NSS); it may also reflect the maturity of a country’s infrastructure and technical capacity. Statistical systems in low- and middle-income countries face a large gap in available funding from their own resources and international donors. As shown in Figure 4, the median scores of low- and middle-income countries have fallen since 2020, while scores in high-income countries have crept up by a little over a point.
Figure 4. Median ODIN scores by income group, 2020-2022
How to use this figure: Hover over the bars to see the data values.
The Income Analysis section illustrates the difference in country performance and discusses the funding gap.
Eastern Asia has made the most progress since 2016, but other regions are not far behind.
Every country is different, but countries in the same region often share a common experience. Figure 5 shows the progress by region of countries that have participated in all ODIN assessments since 2016. The countries of Eastern Asia had the largest increase in their median score over the last 7 years, despite falling by just over one point in 2022 (as discussed in the section, Regional Analysis). Between 2016 and 2022, Eastern Asia increased its score by 20 points. The greatest opportunities for improvement occur in regions that have lower scores and thus, more room for progress. The Caribbean region is an example, increasing its regional score by nearly 14 points starting from a median regional score of just 23. The smallest improvements are often found in high-income countries that already have the highest ODIN scores. North America, one of the highest performing regions in 2016, is the only region where the median score has fallen from its 2016 level, but gains were also small in Northern Europe and Pacific Islands. Closing the last mile remains a significant challenge even for countries with advanced statistical systems.
Figure 5. Change in median ODIN scores by region, 2016-2022
How to use this figure: Hover over the data points to see the data values.
The Regional Analysis section provides further discussion of the factors driving these changes.
Gender data are less available but just as open as other data.
Eleven categories of statistics that include sex-disaggregated data or indicators unique to women, such as maternal mortality ratios and access to reproductive health care, make up the ODIN Gender Data Index (OGDI). These data are crucial for monitoring gender equality outcomes and taking action to promote the welfare of women and girls. The OGDI has consistently lagged non-gender data categories in ODIN. OGDI coverage scores, measuring the availability of gender data, have not made meaningful improvement since 2020 and remain consistently behind non-gender data categories, but in 2022 the median openness OGDI score matched that of non-gender data for the first time (less than 1 point difference).
Figure 6. ODIN Gender Data Index and non-gender data categories, 2016-2022
How to use this figure: Select options from the drop-down menu to view coverage, openness, or overall ODIN scores. Hover over the bars to see the data values.
The Gender Data Analysis section provides further discussion of gender data and information about a new Open Gender Data Index under development.
Box 1. What do ODIN scores mean?
The overall ODIN score serves as an indicator of the availability (coverage) and accessibility (openness) of data published on national statistical office (NSO) websites. The coverage score measures the availability and scope of a country’s data offerings measured by five elements:
- Data Availability and disaggregation of indicators
- Number of years for which data are available in the last 5 and 10 years (two separate elements)
- Availability of data at the first and second administrative levels (two separate elements)
The openness score measures the accessibility of these data and aligns with the standards of the Open Definition and Open Data Charter. The five elements of openness assess:
- Open formats (both machine readability and non-proprietary formats are separate elements)
- The presence of download options, such as APIs, bulk downloads, and custom data exports
- The completeness of metadata
- The use of an open license
All scores are represented on a range from the lowest at 0 to 100 at the best performance.
COVERAGE AND OPENNESS
Data openness improved but coverage lost ground.
ODIN provides separate scores for a country’s data coverage and data openness that target specific stages of the data value chain to understand the evolution of data from collection to analysis, dissemination, use, and the final impact of data on decision making. Data coverage gaps identify issues primarily in data collection and governance in the earlier stages of the data value chain, while data openness gaps identify dissemination issues, such as open formats and licensing issues that affect data use and impact.
Figure 7 shows changes in coverage and openness scores between the last 2 rounds -- 2020 and 2022 -- for the 183 countries assessed in both rounds. (These values differ from those reported in Figure 2 because Figure 7 includes 18 countries that did not appear in one or more earlier rounds. It does not include countries that appeared in 2022 for the first time.) The median coverage score dropped by 1.6 points, while the median openness score increased by 1.8 points. However, changes in the ODIN methodology in 2022 contributed about 1.6 points to the increase in the openness score.
As countries’ overall ODIN scores increase, they reach a threshold where progress is not possible without further investment in their data collection and governance practices. Improving data coverage is harder to achieve because it requires ongoing investments in data collection, staff training, and technology. Improving openness is typically easier, as basic improvements require fewer resources and once achieved, are enduring. In previous years, coverage scores have typically increased slowly, while openness scores improved more rapidly. This year coverage scores have decreased and the rate of increase of openness scores has slowed or fallen for many countries. The COVID-19 pandemic halted data collection efforts for many countries, resulting in a more pronounced decrease in coverage but with less effect on openness. Openness scores for 80 countries fell between 2020 and 2022 as did the coverage scores of 96 countries.
Figure 7. Median coverage and openness scores, 2020 and 2022
How to use this figure: Hover over the bars to see the data values.
Despite evidence of falling scores, availability of first administrative level data and machine readability improve.
ODIN coverage scores are calculated by assessing indicator availability, their disaggregations, the presence of subnational data (first and second administrative level), and how often the data are collected and published. ODIN openness scores are calculated by assessing machine-readability, non-proprietary data formats, download options, completeness of metadata, and the data license. Figure 8 shows the median scores for each element of coverage and openness for the 183 countries assessed in 2020 and 2022.
In 2022, the most improved coverage element was data availability at the first administrative level. Subnational data (at both the first and second administrative level) are consistently the lowest scoring coverage elements in ODIN. First and second level administrative data are more difficult for countries to collect because they require more resources. Even when these data exist, many countries are reluctant to publish them because of lack of knowledge about how to adequately anonymize the data. The slight increase in first administrative level data may indicate that some countries are learning how to anonymize their data appropriately.
Additionally, there was a very small increase in the amount of data made available in the last 10 years. An increase of scores for this element happens when countries start to publish more historical datasets or data in time series. A mistake many countries make when developing new data portals or websites for publishing data is only focusing on the most recent data, often neglecting to upload data that would allow users to see trends over time. The slight increase in ten-year data availability may indicate that some countries are reversing this mistake.
Figure 8. Median coverage and openness element scores, 2020 and 2022
How to use this figure: Select coverage or openness elements to view data by each type. Hover over the bars to see the data values.
The most improved openness element in 2022 was machine-readability. Open formats are those which are both machine readable and non-proprietary. Non-proprietary scores are the highest scoring openness element because many governments publish data in PDF format, which is non-proprietary but not machine-readable. For many countries, this is standard practice and not an attempt to adopt open formats. On the other hand, countries that make data more available in machine-readable formats are more likely to adopt a format that is both machine readable and non-proprietary, such as CSV or XLSX. Therefore, machine-readability scores are a much better predictor of whether countries are moving to open formats. The 2.4-point increase in this score is evidence that this is happening.
Openness element scores for metadata availability and download options increased by less than 1 point, and non-proprietary stayed the same. These small changes can be mostly attributed to methodology changes in 2022 that you can read more about in the Methodology section. Despite methodology changes that boosted many countries openness scores this year, data license scores saw a sharp decline of nearly 10 points.
More countries adopt open data licenses, but others move backwards.
Other countries simply edited their existing licenses to align with the Open Definition. Malaysia is an example; instead of adopting an entirely new license, their existing license was edited to remove a statement that required users to ensure that the data they use are republished “accurately.” Vague requirements such as this, that are not defined, are found in many countries’ data licenses. Because they are not explicit about what is prohibited (or in this case, what is considered “accurate”), they create a legal grey area that could potentially be used by government agencies to restrict the use of their data. These requirements should not be found in open licenses; they should be removed or replaced with specific statements, such as “These data cannot be used for illegal purposes.”
Box 2. What categories of statistics does ODIN cover?
ODIN assessments of coverage and openness are conducted for 22 data categories grouped into three major categories: Social Statistics, Economic and Financial Statistics, and Environmental Statistics. Social data categories cover issues related to population, health, education, and other important topics. Economic data categories cover national accounts, prices, labor statistics, balance of payments and international trade, and government finances. Environmental data categories include natural resources and land use, pollution, energy, and other topics. The indicators assessed in each data category represent the types of statistics that a strong statistical system must be able to produce. The progress countries have or have not made in each category reveals sectors where the greatest opportunities—and need—for improvement exist.
Small increases in Social and Economic Statistics are offset by decreases in Environment Statistics.
Figure 9 shows the changes in the median coverage and openness and overall scores of the 22 statistical categories assessed by ODIN. The fall in Environmental Statistics was driven by declines in Energy, Resource Use, and Built Environment. Although Economic and Financial Statistics continued their improvement, coverage of International Trade fell sharply, and Social Statistics experienced a drop in the openness score of Health Facilities.
Figure 9. Median overall, coverage, and openness scores by category, 2020-2022
How to use this figure: Select options from the drop-down menu to view coverage, openness, or overall ODIN scores. Hover over the data points to see the data values.
Data on Reproductive Health are available in more open formats.
In Social Statistics, the median openness scores for Reproductive Health increased from 50 in 2020 to 60 in 2022, mostly because of large increases in data available in machine-readable and non-proprietary formats, along with small increases in download options and metadata availability. Having Reproductive Health data in more open formats allows researchers, policy analysts, and practitioners to monitor and analyze trends in childhood mortality, fertility, and maternal health.
Worrisome decline in availability of data on International Trade.
Meanwhile, there was a precipitous drop in coverage scores for International Trade – from 83.3 in 2020 to 50 in 2022. There are high standards set for International Trade in ODIN’s assessment: trade data should be available on a quarterly or monthly basis—in a globalized world, having timely data on trade is critical for a detailed understanding of global markets. The lack of such data, just as the world recovers from the unprecedented shock of the COVID-19 pandemic, is concerning and needs to be addressed. As shown in a subsequent section, data standards for financial data, including trade, can help guide countries to make more of their macroeconomic data available in a way that encourages investments that may lead to economic growth.
For Environment Statistics, there were drops in the overall median scores across 3 of 5 categories, chief among them Energy. The next section will delve into the Energy category in greater detail, but all Environment Statistics need to improve for countries to have the necessary data to make smarter use of their resources and chart a path forward to mitigate and adapt to climate change.
Better energy data are needed as scores show continued underperformance.
A large decrease in the openness scores for Energy Statistics contributed to the decline in Environmental Statistics. Though Figure 9 shows no changes in the median score, the arithmetic average of Energy coverage scores also declined. This is at least in part explained by ODIN’s methodology: ODIN now requires energy statistics to include disaggregations of energy use and production by type of energy commodity, a more useful set of data in a world where the demand and supply of energy are rapidly changing. In many cases, countries only publish data on electricity.
On openness too, the Energy median openness score has also dropped in Energy—from 60 to 40, showing a worrying decrease in the accessibility of energy data. Figure 10 shows the average scores for the elements of Energy Statistics coverage and openness, which show larger changes than the corresponding median scores. In 2022, the average score decreased for all elements of coverage and openness.
Figure 10. ODIN 2022 scores for Energy Statistics, by elements of coverage and openness
How to use this figure: Hover over the data points to see the data values. Click the data elements in the legend to remove or add them from the graph.
Facing the challenges of climate change, open energy data is critical because energy production and use is at the core of climate change mitigation. The International Energy Agency (IEA) should be leading the way in publishing open data about energy supply and use but continues to charge for data despite publicly committing to finding ways to make open data work with the organization’s funders. A year after this commitment, the IEA must remain steadfast in working with its funders to open more energy data for all.
IMF data dissemination standards encourage open macroeconomic data.
The International Monetary Fund (IMF), an international financial institution, works to increase both the availability and openness of macroeconomic data through the Enhanced General Data Dissemination System (e-GDDS) and the Special Data Dissemination Standard (SDDS). Open to all member countries, e-GDDS focuses on the improvement of macroeconomic data and guiding countries to improve the collection and publication of macroeconomic data. SDDS is a step up from e-GDDS. SDDS has two levels: SDDS and SDDS Plus. SDDS defines standards for data coverage, periodicity and timeliness, data accessibility, integrity, and quality of disseminated data. Building on SDDS, SDDS Plus entails more ambitious data dissemination and data transparency standards. Both SDDS and e-GDDS “are expected to enhance the availability of timely and comprehensive statistics and therefore contribute to the pursuit of sound macroeconomic policies; the SDDS is also expected to contribute to the improved functioning of financial markets.” Adoption of these standards increases the reliability of macroeconomic data, the transparency of economic and financial policies, countries’ creditworthiness, and therefore access to financial markets.
Figure 11 shows ODIN scores for Economic and Financial Statistics by countries that subscribe to IMF’s SDDS and e-GDDS. As expected, countries that subscribe to the SDDS and SDDS Plus standards have much higher Economic and Financial Statistics scores than e-GDDS participants or countries that do not subscribe to SDDS or e-GDDS. It is notable that coverage scores for all groups of countries are higher than their openness scores. The data dissemination standards appear to have had a greater impact on data production, while openness remains a more distant goal.
Figure 11. ODIN scores for Economic and Financial Statistics by IMF subscriber status
How to use this figure: Hover over the data points to see the data values.
Small island developing states lack environmental data.
The Intergovernmental Panel on Climate Change (IPCC) recognizes the importance of data for building country capacity to assess climate change and prepare policies to adapt to and mitigate its effects. While ODIN does not have a dedicated set of climate change indicators, the ODIN Environment category looks at data on Agriculture and Land Use; Resource Use; Energy; Pollution; and the Built Environment of households. Climate change directly impacts these data categories, with the most vulnerable countries being hit the hardest.
Small Island Developing States (SIDS) are especially vulnerable to climate change. In the span of the last two decades, SIDS have experienced 20 natural disasters a year. Figure 12 shows median overall scores for Environment Statistics categories by SIDS status. There is a large difference in the median Environment score for SIDS and non-SIDS countries in every year. Non-SIDS countries’ scores increased but decreased slightly in 2022. SIDS countries rose slowly through 2018 and, after a sharp increase in 2020, their median score fell significantly in 2022. With limited environmental data, they lack the tools needed to build greater climate resilience and need greater assistance to build data systems that help inform these tools.
Figure 12. Median overall score for Environment categories by SIDS status
How to use this figure: Hover over the data points to see the data values.
Many countries do much better than their peers with similar incomes, and many high-income countries do much worse.
Figure 13 shows the correlation between ODIN country scores – grouped by their World Bank income level – and the gross national income (GNI) per capita of the country, where the bars in the graph show median scores by income groups. Countries, even at the same income level, vary widely in their scores: 11 middle-income countries score higher than the median scores for high-income countries while 9 high-income countries score lower than the median score for low-income countries. Countries at similar levels of income can learn from high performers to improve their statistical systems. The reverse is also true. For many high-income countries, their relative underperformance should spur further improvements and build political will to bring the country’s resources to bear on their open data systems.
Figure 13. Country overall scores by GNI and income group, 2016-2022
How to use this figure: Hover over the data points to see the data values.
Support for data systems in low- and middle-income countries continues to fall short.
High- and upper-middle-income countries rely on their own resources to fund statistical activities, while low- and lower-middle-income countries face a funding gap that is only partially addressed by resources from multilateral and bilateral donors. In 2021 the annual funding needed by countries eligible for financing by the International Development Assistance (IDA) or International Bank for Reconstruction and Development (IBRD) to produce the core statistics was estimated to be $6.2 billion with $1.4 billion coming from external sources. Yet 2022 estimates of the Partnership Report for Estimating Support to Statistics (PRESS) by PARIS21 show that national and donor resources fall far short. Low- and lower-middle-income countries will need to innovate to make their own resources go farther and, with only 7 years to achieve the SDGs, donors must step up to fund critical data systems.
Global ODIN scores show that countries across the world have stagnated or reversed in their efforts to improve the availability of and access to official statistics. ODIN findings at the regional level show a similar pattern of stagnation, with only some regions showing even modest improvement. In previous ODIN years, each region saw at least some improvement, but in 2022 the overall median score of half the world’s regions decreased. Figure 14 shows that 6 regions made improvements of more than 1 point (green); 4 regions made minor improvements of less than 1-point (light green), and 10 regions saw some degree of regression (in red). On the ODIN website, users can compare regional results for the 20 geographic regions listed in Figure 14 or download individual regional reports.
Figure 14. Changes in regional median overall scores, 2020-2022
How to use this figure: Use the (+) and (-) buttons to zoom in and out. Hover over each region to reveal the region name and data values.
Only three regions improve in both coverage and openness: South America, Central America, and South-Eastern Asia.
Overall progress between regions is split, with half showing improvement and half regressing. A closer look at each region’s openness and coverage score indicates that only three regions saw improvement in both coverage and openness - South America, Central America, and South-Eastern Asia. All other regions had at least a minor decline in either coverage or openness.
Figure 15 shows that six regions improved in openness but regressed in coverage; five regions improved in coverage but regressed in openness; and six regions regressed in both coverage and openness. Readers can toggle Figure 15 between coverage and openness scores that show the differences between 2020 and 2022.
In each region that had an increase in both coverage and openness, the coverage scores made only a slight improvement. In the three regions where this happened, coverage scores increased by 0.8 points or less. Even Northern Europe, which saw the highest increase in median openness scores--with over a 9-point increase--saw a slight decrease in coverage scores of 1.3 points.
Figure 15. Changes in regional median coverage and openness scores, 2020-2022
How to use this figure: Select coverage or openness elements to view the map by each type. Use the (+) and (-) buttons to zoom in and out. Hover over each region to reveal the region name and data values.
Each region has an open data champion, regardless of overall trends.
For a more thorough understanding of what is driving regional scores, consider what individual countries have done. While aggregate score changes within each region reflect overall challenges, every region has champion countries that have actively made improvements. The countries highlighted in Table 1 serve as examples that other countries in each region can look to for lessons and best practices and some are discussed in greater detail in the Country Stories section of this report.
Table 1. Most improved country scores by region
|Region||Most Improved Countries|
|South-Eastern Asia||Lao PDR (+7), Malaysia (+6), Vietnam (+5)|
|Western Asia||Jordan (+15), Saudi Arabia (+10), Israel (+7)|
|Central Asia||Uzbekistan (+4), Kyrgyz Republic (+3), Kazakhstan (+2)|
|South America||Chile (+19), Paraguay (+13), Guyana (6)|
|Northern Europe||Latvia (+19), Estonia (+8), Norway (+6)|
|Central America||Belize (+6), Mexico (+1)|
|North America||Greenland (+4)|
|Western Africa||Togo (+9), Mauritania (+8), Sierra Leone (+6)|
|Australia and New Zealand||Australia (+5)|
|Southern Europe||Andorra (+28), San Marino (+9), Serbia (+6)|
|Eastern Europe||Romania (+5), Moldova (+4), Russian Federation (+3)|
|Southern Asia||Bhutan (+4)|
|Caribbean||Anguilla (+9), St. Kitts and Nevis (+7), Trinidad and Tobago (+7)|
|Western Europe||Liechtenstein (+16), Belgium (+12), France (+6)|
|Eastern Africa||Ethiopia (+21), Somalia (+13), Mozambique (+10)|
|Northern Africa||Morocco (+2), Tunisia (+2), Libya (+1)|
|Eastern Asia||Taiwan (+5), Hong Kong, SAR China (+5), Mongolia (+4)|
|Pacific Islands||Papua New Guinea (+5), Palau (+4), Tonga (+3)|
|Middle Africa||Gabon (+10), Chad (+9), Sao Tome and Principe (+2)|
|Southern Africa||Eswatini (+7), Botswana (+4)|
The countries in Table 1 are the primary drivers of their regions. Some represent small improvements in high-performing regions. Others are outliers in struggling areas. South America, Central America, and South-Eastern Asia show some of the most improvement of all regions, driven by countries that made significant improvements such as Chile, Malaysia, Jordan, and Saudi Arabia. Progress in other regions such as Central Asia has been driven by minor improvements in multiple countries.
However, there are many regions experiencing negative growth that include countries making remarkable progress. For example, while Eastern Africa’s median score decreased by 1 point, Ethiopia improved by 21 points. In Western Europe, although the regional median score decreased, Liechtenstein and Belgium increased their scores by over 16 and 12 points, respectively. Even in the two regions where median scores decreased the most, Middle and Southern Africa, Gabon, Chad, and Eswatini made progress of over 7 points each.
Chile, Paraguay, Trinidad and Tobago, Australia, and Jordan are examples of how national statistical offices can improve the accessibility and usability of their country’s data. All five are highlighted in Table 1 as one of the most improved countries in their region.
Chile, Paraguay, and Trinidad and Tobago participated in workshops held in 2021 and 2022 as part of a joint project between the Inter-American Development Bank (IDB) and Open Data Watch. Each workshop series had four components: an overview of the essentials of data coverage and accessibility; a survey of data gaps by sector; a checklist of core aspects of open data (like licensing and file formats); and a review of how data are used by groups inside and outside of government. For more information about the technical support offered by Open Data Watch, please visit this page.
To read each country's story, select a country from the drop down under the heading of Figure 16.
Figure 16. ODIN scores for selected countries, 2020-2022
How to use this figure: Select a country from the drop-down menu to view scores for each one. Hover over the data points to see the data values. Click the score types in the legend to remove or add them from the graph.
Chile, one of only 7 countries in South America to increase their ODIN score in 2022, led the region with an overall score increase of 18.9 points. Chile’s achievement was driven by increases in their coverage and openness scores of 13.3 and 23.7 points, respectively.
Chile’s coverage scores were increased by publishing more economic data. Their Economic and Financial Statistics coverage score nearly tripled to 87 points in 2022, because Chile’s National Institute of Statistics (INE) provided direct links to many datasets produced by other statistics producers, including Chile’s Banco Central, La Dirección de Presupuestos (DIPRES), and the Servicio Nacional de Aduanas. Overall coverage scores would have improved further, but some social and environmental indicators were no longer published.
Chile improved its data openness by publishing more data in machine-readable formats (score increase of 45 points) and publishing a new data license (score increase of 55 points). Many datasets previously available only in PDF format, which is not machine-readable, were published in machine-readable formats in 2022. However, some datasets available in 2020 in PDF format were removed entirely in 2022 without being replaced. By replacing these datasets with machine-readable versions, Chile could easily see another sizable increase in their data openness scores by the next edition of ODIN.
Data license scores increased drastically after INE published a new data license to replace its restrictive license that forbade commercial use of their data. Now, INE releases its data under a Creative Commons Attribution-Share Alike 4.0 International license--one of several Creative Commons licenses that meet the criteria of the Open Definition.
Paraguay had the second largest increase in South America after Chile. Buoyed by an openness score increase of 23.4 points, Paraguay jumped from ninth in the region in 2020 to sixth by gaining 13.4 points for an overall score of 54.8 in 2022.
The inclusion of a new open data license significantly helped Paraguay’s openness score. Since there was no data license available in 2020, the addition of this new license that meets all openness standards increased the score from zero to 89 points. Chile and Paraguay both increased their openness scores primarily through the inclusion of a data license, but Paraguay did not adopt a Creative Commons license. Instead, Paraguay created its own country-specific license.
Openness scores also improved because Paraguay’s Institute of National Statistics (INE) published more data in machine-readable formats (score increase of 16 points). Since 2020, Paraguay was able to publish more data in machine-readable formats for all years available for five additional ODIN indicators.
Scores for many Caribbean countries fell in 2022, but Trinidad and Tobago was one of four countries in the region that saw an increase. Trinidad and Tobago had the third highest increase in score and jumped three spots since 2020 – from tenth to seventh in the region.
Trinidad and Tobago improved their overall score by improving their coverage scores. Trinidad and Tobago’s Central Statistical Office (CSO) published more disaggregated data and more historical data from the last 5 and 10 years, leading to 22- and 27-point increases. Trinidad and Tobago also increased their openness score by publishing more data in non-proprietary formats.
A 10.4-point increase in their openness score allowed Australia to earn an overall score of 68.2 in 2022. Australia’s Bureau of Statistics published more data in non-proprietary formats, nearly doubling their score for this element. Several data categories, among them Built Environment, Crime and Justice, and Education Outcomes, received higher scores for openness by publishing data in machine-readable and non-proprietary formats.
With a 14.6-point increase, Jordan led the 18 countries of Western Asia region with the largest increase in its overall ODIN score, moving up 6 places in the region. This is particularly impressive considering that Western Asia had the fifth largest increase of its median score among all regions.
Both coverage and openness scores received a boost from publishing data in categories that had received a score of zero in 2020. No indicators for the Crime and Justice category were found in 2020, but in 2022 indicators were available in multiple machine-readable and non-proprietary formats, with more than one download option, and accompanied by an open data license. Several other categories, such as Health Outcomes and Food Security and Nutrition, received higher scores for openness by consolidating data from multiple statistical yearbooks that were only available in 2020 as PDFs with no download options. These data are now available in machine-readable and non-proprietary formats with multiple download options.
Openness was also improved by the adoption of a new open data license (the Jordanian Open Government Data License) and a new open data portal to monitor their progress towards achieving the Sustainable Development Goals (SDGs). Because there was no data license available in 2020, the addition of this new license increased the aggregate score of this element from 0 to 77 points. The license, created by Jordan’s Department of Statistics satisfies all the requirements of an open data license.
ODIN AND THE SUSTAINABLE DEVELOPMENT GOALS
ODIN scores, which document how successful a country is at producing official statistics, reveal much about their capacity to produce data for the Sustainable Development Goals. The SDGs are an urgent call for action set by countries to address intersecting global challenges. They seek to end poverty, address climate change, and ensure peace and prosperity for all by 2030. To achieve these ambitious goals, countries and the international community need detailed and timely data to inform policies and track progress.
There are many gaps in the data required for the SDGs. Countries have struggled to provide real-time mortality data throughout the COVID-19 pandemic. Women have been disproportionately affected by overlapping global crises, but more than a third of relevant indicators lack sex-disaggregation in most countries. And even as the world struggles to mitigate the worst effects of climate change, 80 percent of countries lack data on climate action. These gaps exist not only in the international SDG database, but also in national sources that ultimately supply the data for international compilation of indicators.
ODIN takes the pulse of a country’s statistical system, measuring its strengths and weaknesses. It assesses the availability and openness of the core social, economic, and environmental statistics that every country should be capable of publishing. SDG indicators satisfy more than half of the 65 indicators required by ODIN assessments. Figure 17 shows the overlap between ODIN and SDG indicators. For example, SDG indicator 3.b.1 on the proportion of the target population covered by all vaccines included in their national program is included in ODIN Health Outcomes as an indicator of immunization rates. And almost half of SDG indicators rely on indicators included in ODIN either directly or as denominators that normalize them. For example, although there is no goal on the population size or age distribution of a country, any SDG indicator measured as a proportion of the population needs these data as a denominator.
Figure 17. Relationship between ODIN indicators and SDG goals
How to use this figure: Hover over each segment to view the SDGs that correspond with each ODIN indicator.
ODIN also reveals the state of the statistical foundations for many of the key SDG indicators. Vital statistics systems produce many of the key denominators that SDGs will need. Population data at varying levels of disaggregation inform more than a quarter of SDG indicators, and ODIN shows that 184 countries produce these data. 11 SDG indicators require mortality rates for varying causes of death, and ODIN shows that only 149 countries publish mortality rates. NSOs also produce economic indicators that can inform SDGs related to inequality and economic growth. GDP is a denominator for 16 SDG indicators, and ODIN shows that 187 countries produce these data.
The SDGs serve as the blueprint to a better and more sustainable future for all. Even with many competing priorities, data should not be an afterthought. The demand for data has reached new heights as policymakers and the public grapple with global challenges that have only been exacerbated through the COVID-19 pandemic, violent conflicts, and economic disruptions. The SDGs are guideposts to meeting these challenges, and ODIN shines a light on progress towards improving statistical capacity needed to achieve them.
GENDER DATA ANALYSIS
Gender data are less available than other data but equal in openness.
Sex-disaggregated data and measures unique to women, such as maternal mortality ratios and fertility rates, are crucial for monitoring gender equality outcomes and taking action to promote the welfare of women and girls. The past three years of the COVID-19 pandemic have underscored the importance of sex-disaggregated and gender-relevant data in public health, women’s economic empowerment, and public safety, among many other topics. In addition, the impacts of climate change are already being felt and, as in all crises, women and girls are particularly susceptible to the negative effects of displacement and disruption to everyday life. Open gender data are therefore needed to help policymakers, citizens, and external donors diagnose problems, advocate for solutions, and allocate political and financial resources.
The ODIN Gender Data Index (OGDI) measures the availability and openness of gender data worldwide. A sub-index of ODIN, the OGDI was first developed in 2020 and has been updated for this report. The index is based on the availability of 35 indicators in 11 statistical categories. Twenty-eight of these indicators require sex-disaggregation or apply only to women and girls. Seven indicators in the Built Environment and Poverty and Income data categories that are not usually sex-disaggregated, such as the poverty rate and access to water and sanitation but have important consequences for women are included in the OGDI. Combining the scores for these data categories yields a measure of the coverage and openness of gender statistics in a country or region. The overall index is an unweighted average of the 11 categories and 10 elements of data coverage and openness.
Figure 18. OGDI and non-OGDI Scores, 2022
How to use this figure: Select the score types to toggle between maps for OGDI scores and non-OGDI scores. Hover over each country to view the scores.
Half of all ODIN categories and over half of all indicators included in them contain gender-relevant information, highlighting the importance of gender data as a cross-cutting issue. But Figure 19 shows that gender data are less available than non-gender data categories. Many statistical systems are still struggling to regularly produce gender data, resulting in coverage scores for OGDI that are 25 percent lower than non-gender data categories. When data are available, OGDI finds little difference in openness.
Figure 19. Coverage, Openness, and Overall scores by OGDI status, 2022
How to use this figure: Hover over the bars to see the data values.
Lack of historical data is holding back gender data availability.
Figure 20 disaggregates the elements of coverage and openness of gender and non-gender data categories. Gender data score lower on the first coverage element, data availability and disaggregation, which handicaps their scores on the remaining elements. But the most significant gap is the lack of historical data for gender data. Lacking historical data, it is hard to monitor outcomes and measure progress. On openness, the gender and non-gender data are close, but machine-readability accounts for lower scores for gender data, most likely because gender statistics summary sheets are published in PDF, which is a nonproprietary but not machine-readable format. More regular production of gender data might also result in more standardized modes of publishing data as part of regular data dissemination efforts compared to irregular special reports on gender data. International donors should focus their assistance both on regular production of gender data, as well as highlighting the importance of these data in special reports.
Figure 20. Average 2022 scores by coverage and openness elements
How to use this figure: Hover over the bars to see the data values.
The availability and openness of gender data is a promising avenue for further research and advocacy. Starting in 2023, Open Data Watch will expand the OGDI by reanalyzing many of the existing indicators and complementing them with indicators on women’s economic empowerment, technology access, and other relevant topics. This work will result in an index that deepens the analysis of the availability of sex-disaggregated, gender-relevant, and intersectional data that leave no one behind. The results will be featured on a dedicated website (The Gender Data Monitor) that will complement the quantitative analysis with a review of country policies and initiatives, providing a comprehensive view of the production, dissemination, and use of gender data. We will publish more information about this new initiative in 2023 and link to the new website here once launched.
To download more complete ODIN datasets, go to the Data page on the ODIN website. You can use the custom scoring tool to manipulate the dataset further by selecting data categories, coverage elements, or openness elements. You can do this from the data page or by clicking the gear icon wherever you see it on the ODIN website.
Below is a summary of the methodology changes this year. Click here to read our full Methodology Guide.
UPDATES IN 2022
Country coverage: The number of countries assessed in 2022 was 192, of which 7 are new countries, not previously assessed in ODIN: Aruba, Barbados, Central African Republic, Grenada, Monaco, Nauru, and Tuvalu. Two countries, Kiribati and Vanuatu, were assessed as part of the ODIN 2022/23 round after an absence in the 2020/21 round. The countries Afghanistan, Sudan, Republic of Congo, Iran, Guinea-Bissau, and Venezuela were not included this year because their websites experienced significant technical issues that made it impossible to complete their assessments.
Emphasis on sex-disaggregated data: To reinforce the importance of gender data and encourage countries to publish the data needed to address gender issues, changes to the ODIN 2022/23 scoring methodology will ensure that no data category that includes gender data or sex-disaggregated data can receive full credit without publishing these data. This change affects the scoring criteria for the first coverage element (data availability and disaggregation) in the categories: Education Facilities, Education Outcomes, Food Security and Nutrition, Gender, and Crime and Justice Statistics.
Several indicators now require sex-disaggregation that did not before:
- (2.2) Number of teaching staff
- (3.3) competency exam results
- (7.1) prevalence of undernourishment
- (7.2) Prevalence of moderate or severe food insecurity
In addition, disaggregation by violence type, has been added to indicator (8.1) Proportion of women who are victims of physical, sexual, or psychological violence.
Change in the scoring of openness elements: In previous ODIN assessments, any category that received a 0 score for the first element of data coverage—Indicator Availability and Disaggregation—would receive zero scores for all elements of data coverage and data openness. In some categories, it is possible to receive a 0 score for Indicator Availability and Disaggregation even when some datasets are published, because they do not have certain disaggregations or include all the required indicators. In 2022/23, if a country does not publish enough disaggregated data to receive a score above 0 for Indicator Availability and Disaggregation, they can still receive credit for the openness of those datasets. Thus, it is possible for a category to have a zero score for coverage and a non-zero score for openness. If no data were found for any indicator in a category, the openness elements were all scored as zero.
New data frequency requirements: Data from the following categories must be presented on a quarterly or monthly basis for all available years to receive full credit on the first coverage element: National accounts, Price Indexes, and International Trade. In previous ODIN editions, quarterly or monthly data were only required for the last five years.
Energy indicators have stricter requirements: Energy indicators include energy supply and consumption. This year countries cannot receive credit for either if the data only includes one energy commodity. In many cases, countries lost credit on these indicators this year because they only produce data on electricity consumption or supply.
The Open Data Inventory (ODIN) is managed by Jamison Henninger who also authored this report with Eric Swanson, Director of Research, Lorenz Noe, Research Manager, Tawheeda Wahabzada, Data and Policy Specialist, Amelia Pittman, Data Visualization and Design Manager, and Taylor Hadnôt, Research Analyst. Primary research for ODIN was conducted by research team including Laura Batista, Miles Johnson, Niklas Jutting, Mama Sow, Jay Ensor, Nour Abdelbaki, and Luke Engelby. We are grateful for financial support from the William and Flora Hewlett Foundation.