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July 2024
Introduction
Open Data Watch (ODW) has developed an Open Climate Data Template (OCDT) that enables countries to quickly evaluate the availability and openness of critical climate change adaptation and resilience indicators. By adopting a user perspective on data from nationally maintained websites, the OCDT helps countries identify where capacity to produce and disseminate data can best be improved to facilitate the use of these vital datasets in policymaking.
Building on ODW’s experience with the Open Data Inventory (ODIN) and as part of the Climate Change Data Ecosystem project in collaboration with PARIS21 and the Center for Open Data Enterprise (CODE), ODW has identified 19 indicators that connect to important resilience and climate change adaptation frameworks. These “sentinel” indicators are representative of the foundational information needed to formulate policies for adaptation and resilience to climate change (see Annex I – List of Indicators). The OCDT evaluates each indicator along dimensions of availability and openness to allow countries to assess the capacity of their statistical systems to produce data needed by policymakers and by citizens. As part of the Climate Change Data Ecosystem project, ODW conducted a pilot assessment using the OCDT to review the national databases of six countries: Cote d’Ivoire, Gambia, Kenya, Mali, Mauritania, and Senegal.
Overall messages:
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- Climate Change resilience and adaptation data are not widely available in national databases among the pilot countries, but other categories also need improvements and the availability of indicators within categories varies widely.
- Across all indicators and countries, the timeliness of data and availability of data beyond the national level are poor and need improvement for the data to be relevant for users who need up-to-date information for policy formulation.
- Better subnational data can help particularly for climate change adaptation and resilience, where local actors can use adaptation and resilience data to improve local conditions and create localized solutions.
- Publishing data with an open license encourages their use and reuse. The license adopted by the Senegal Open Data for Africa site, for example, meets the openness criteria and ensures all available data are available to be freely used.
- Gaps in climate change adaptation and resilience data need to be filled, particularly for indicators of education about climate change, climate adaptation finance, and cost estimates of climate change-related disasters.
- Stronger coordination between stakeholders of the national statistical systems can facilitate the production of data, particularly where indicators are cross-cutting, for example when accounting for the damage caused by climate change-linked disasters. Adopting a user perspective on climate change adaptation and resilience indicators can connect groups of producers and users to improve the availability and dissemination of data.
Methodology
The OCDT contains a detailed list of the indicators and the scoring template for use by climate change data actors across the national statistical system, including non-governmental stakeholders.
ODW’s indicator selection specifically builds on the CODE Climate Data for Adaptation and Resilience Typology (Climate-DART). The Climate Dart identifies 14 Focus Areas of adaptation and resilience. The OCDT distills each focus area to one or more indicators that meet the following criteria:
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- Indicators are clearly defined and use an internationally agreed methodology. Many climate change indicators are still in development, and countries should prioritize those already in general use and where reliable methodologies exist. This will also enable comparison across countries to encourage peer learning.
- Where possible, indicators that use data collected at the national level have been preferred. While many of these indicators correspond to data published by international custodian agencies, the methodology for each indicator should indicate that they are based on data collected at the country level. Some indicators have been included that involve production of data by international actors but with national coordination and dissemination.
- Indicators align as closely as possible with existing data frameworks, such as the SDGs or the Sendai Framework. The CODE focus areas are already based on international frameworks such as the Paris Agreement, the SDGs, and the Global Set of Climate Change Indicators.
- Indicators are less affected by unique geography. For example, mean surface air temperature has been prioritized over sea level, because over 20 percent of all countries do not have coasts.
The 19 indicators are further grouped into four categories to enable countries to identify areas of focus in efforts to improve statistical systems for better climate change data:
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- Climate Change policies, plans, and programs
- Population vulnerability
- Infrastructure
- Natural resources and environment
The goal of this exercise is to create a minimum set of indicators that reveal a country’s ability to capture and use information relevant to National Adaptation Strategies and other climate change adaptation and resilience undertakings. A simple scoring system provides countries with a quick assessment that allows them to focus on areas for improvement of the availability and openness of climate data.
During August and September 2023, researchers from ODW conducted a desk review assessment of the sentinel indicators available for Cote d’Ivoire, Gambia, Kenya, Mali, Mauritania, and Senegal. Researchers started by trying to find information on a country’s national statistical site, if no data were found they proceeded to a country’s open data or SDG portal followed by the relevant ministry’s website (like a ministry of environment). If no data were found at any of these locations, they performed a Google search on the country and indicator. A full list of sources is available in Annex II – Data sources consulted.
Assessing Availability
ODW measures the availability of each indicator by three criteria:
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- Availability of at least one datapoint with all required disaggregations (such as age or sex, specific to each indicator). This is to set a floor for data availability while ensuring data are comprehensive.
- Availability of data in the last five years to ensure timeliness of data for planning.
- Availability of data at the first administrative geographic level. Climate change data will be relevant to national but also sub-national actors and better planning can be carried out with more subnational data.
Assessing Openness
ODW measures openness of each indicator by three criteria:
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- Availability of data in machine-readable formats to ensure usability of data.
- Availability of reference metadata for each indicator to ensure accountability and better understanding of each indicator to enable greater use. ODW looks for three components of reference metadata that are common in all metadata standards:
- Definition of the indicator, or definition of key terms used in the indicator description (as applicable), or a description of how the indicator was calculated.
- Specific date the dataset was uploaded to a website or when a dataset was last updated. The date must include the day, month, and year.
- Name of the agency responsible for the dataset.
- Availability of an open data license or open terms of use to enable users of the data to use data freely.
Each of the six elements are scored and receive equal weighting in the final availability and openness scores. The scoring criteria and methodology are contained in the OCDT workbook. The assessment workbook also contains a list of substitute indicators alongside the list of official indicators for this assessment. Although most of the indicators have strict definitions, closely related indicators can act as substitutes.
Availability and openness of climate change adaptation and resilience data:
The 19 indicators of climate change adaptation and resilience are grouped into four thematic categories to enable targeted data system improvements. For each indicator the score reflects an average of the scores for data available with relevant disaggregations across the last five years, and data available at the subnational level. The data availability score for each category is the average of the indicator scores in that category. It has a possible range from 0 (for no available data) to 100 (for complete data).
Table 1 shows the average Availability and Openness scores for the six pilot countries. A full listing of the indicators within each category can be found in Annex I – List of Indicators.
Table 1 OCDT category scores
| Category | Number of indicators assessed | Example indicator | Availability Score (0-100) | Openness Score (0-100) |
| Climate Change policies, plans, and programs | 3 | Proportion of local govts. with disaster risk reduction strategies | 10 | 20 |
| Infrastructure | 5 | Total energy supply | 20 | 40 |
| Natural Resources | 5 | Forest area as a proportion of total land area | 20 | 40 |
| Population Vulnerability | 6 | Population using safely managed drinking water services | 40 | 60 |
| All indicators | 19 | 20 | 40 |
Availability
Indicators grouped under the category Climate Change Policies, Plans, and Programs stand out for their low availability. All three indicators are SDG indicators, but SDG indicators 13.3.1 and 13.a.1, in particular, are not available for many countries in international databases such as the SDG Global database, which serves as the ultimate source of much of the data presented on this topic by country databases. Better data on financing for adaptation and integration of climate change awareness into national curricula would help fill in information gaps on the budgetary and social dimension of climate change adaptation.
The availability score is composed of three elements; the first element that tests for the presence of any datapoint with required disaggregations shows a much broader range than the overall availability: Climate Change, Policies, Plans, and Programs indicators score on average 10 out of 100 whereas Population Vulnerability indicators score 80. This suggests that across these six countries, indicators on population vulnerabilities, which include social indicators on poverty, social protection, and others are much more commonly produced compared to indicators on the implementation of plans for climate change adaptation and education.
Even for categories with broader availability like population vulnerability, testing for the presence of time series data and the availability of subnational data drags down all availability scores across all countries, indicating that the data that are produced are not available across many years or below the national level. Exceptions are Infrastructure indicators in Mali and Senegal, which publish relatively robust time series for indicators like municipal waste and total energy supply. Cote d’Ivoire’s data for Population Vulnerability provides the exception for subnational data, with three of the six indicators having available data at the subnational level.
Between the six countries, availability scores range from 18 (Mauritania) to 27 (Senegal) out of a possible 100, reflecting a need to produce more climate change related data no matter the country. For individual indicators, commonly produced indicators like the count of the urban population, livestock production, proportion of the population using safely managed drinking water, and total energy supply score highest for overall availability (score of 50 or above). Three of the 19 indicators have not been produced by any of the six pilot countries: climate change education (SDG 13.3.1), climate financing mobilized (SDG 13.a.1), and damage to infrastructure attributable to climate change (11.5.3). These are conceptually difficult indicators because they draw on multiple disciplines to construct the indicator, such as education and environment in the case of climate change education. These indicators are managed by international organizations who also provide technical assistance to countries to produce the indicator. Hopefully, as these indicators become conceptually clearer to statistical systems, production of these important indicators will improve.
Openness
The openness of data on climate change resilience and adaptation is largely correlated with the availability of data: you cannot make open data that do not exist. Nevertheless, there are interesting variations of openness across data categories. For example, although the average availability of machine-readable data is fairly similar in Infrastructure, Natural Resources, and Population Vulnerability, the Infrastructure has much more variation in country’s use of machine-readable formats. Some of this is explained by country’s different publication of total energy supply. Mali and Senegal score highest on the use of open formats for this indicator, due to the availability of data in multiple machine-readable formats. On the other hand, total energy supply is not available in more than one machine-readable format for Kenya, Mauritania, and Cote d’Ivoire.
The Population Vulnerability category scores highest for the availability of metadata and climate change policies, plans, and programs score lowest, however, countries differ in how well they describe their data with metadata even within the same category and despite the fact that much of the metadata comes from international sources like the SDG Global Database. For example, Kenya lists the definition, last update date, and source of its indicator on the proportion of local governments that adopt and implement local disaster risk reduction strategies within the Climate change, plans, and policies category; it the only country to do so. On the other hand, the remaining four countries with data for this indicator provide just one or two elements of the list of metadata elements.
The availability of an open data license also varies widely across the indicators in the assessments. However, the scores for data licenses capture differences between country legal regimes as opposed to different treatments of categories or indicators. Most data portals apply one data license for all data on the site, which means that data license scores will be consistent for each country across all categories. For example, Senegal’s adoption of an open data license on its NSO and Open Data for Africa portal results in high data license scores for all indicators while Gambia and Mauritania’s lack of a data license means that all indicators receive a score of 0.
Between the six countries, openness scores range from 15 (Mauritania) to 56 (Senegal), reflecting a significant difference in openness practices. The availability of a data license is a big contributor to the gap between countries. This range also shows that even though many countries use the same basic data portal structure (through the Open Data for Africa portal), countries still present data in a variety of ways.
Conclusion
As countries draft national adaptation plans, the OCDT can be used by stakeholders of a country’s national statistical system to develop a snapshot of the state of national data for climate change adaptation and resilience. In addition, the template shows where capacity is missing to disseminate adaptation and resilience data and make them fit for use by policymakers, planners, academia, and civil society organizations The countries studied as part of this pilot of the OCDT face challenges like many low- and middle-income countries to produce disaggregated data relevant to climate change and to do so on a regular basis. While some indicators important to climate change are collected and published by international organizations like UNFCCC, countries should nevertheless invest in local data relevant to global monitoring efforts. In addition, data on people that national statistical systems already produce should be uploaded and disseminated more frequently and presented at the subnational level. An area ripe for innovation is around governance data for climate change to ensure plans for climate change adaptation and resilience can be part of local and global efforts to make more coherent policy to build sustainable futures.
Annex I – List of Indicators
| Category | Indicator |
| Climate Change Policies, Plans, and Programs | SDG 11.b.2 Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategies |
| Climate Change Policies, Plans, and Programs | SDG 13.3.1: Extent to which (i) global citizenship education and (ii) education for sustainable development are mainstreamed in (a) national education policies; (b) curricula; (c) teacher education; and (d) student assessment |
| Climate Change Policies, Plans, and Programs | SDG 13.a.1 Amounts provided and mobilized in United States dollars per year in relation to the continued existing collective mobilization goal of the $100 billion commitment through to 2025 |
| Infrastructure | Municipal waste collected per capita |
| Infrastructure | SDG 1.5.2 Direct economic loss attributed to disasters in relation to global gross domestic product (GDP) |
| Infrastructure | SDG 11.5.3 (a) Damage to critical infrastructure and (b) number of disruptions to basic services, attributed to disasters |
| Infrastructure | SDG 11.6.2 Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities (population weighted) |
| Infrastructure | Total energy supply (TES) |
| Natural Resources and Environment | Livestock production index (2014-2016 = 100) |
| Natural Resources and Environment | Mean surface air temperature |
| Natural Resources and Environment | SDG 15.1.1 Forest area as a proportion of total land area |
| Natural Resources and Environment | SDG 15.5.1 Red List Index |
| Natural Resources and Environment | SDG 6.3.2 Proportion of bodies of water with good ambient water quality |
| Population Vulnerability | SDG 1.1.1 Proportion of the population living below the international poverty line by sex, age, employment status and geographic location (urban/rural) |
| Population Vulnerability | SDG 1.3.1 Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerable |
| Population Vulnerability | SDG 1.5.1 Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population |
| Population Vulnerability | SDG 2.1.1 Prevalence of undernourishment |
| Population Vulnerability | SDG 6.1.1 Proportion of population using safely managed drinking water services |
| Population Vulnerability | Urban population (percent of total population) |
Annex II – Data sources consulted
Acknowledgements
Open Data Watch (ODW) developed the Open Climate Data Template (OCDT) as part of a collaborative project led by PARIS21 and including the Center for Open Data Enterprise (CODE), with support from the Hewlett Foundation.
This analysis was conducted and research brief written by Lorenz Noe, Research Manager. Project Management and Research Assistance provided by Amelia Pittman, Data Visualization and Design Manager. Additional research assistance by Tawheeda Wahabzada, Data and Policy Specialist. Assessments were conducted by Nadeem Shakhshir.
