Yes, Resource Watch data are free and open to use for your own analysis as long as your use complies with the licensing and restrictions of the source data providers. Users can access links to download data and find information on the licensing of the data from the data set detail pages.

Different data sets measure different things, are derived using different methodologies, cover a different moment in time, or have different spatial resolutions. Be sure to read the details about the methodology and scale underpinning each data set before drawing conclusions.

Please cite the original source as noted on the data set detail page and include “Accessed through Resource Watch www.resourcewatch.org.”

We strive to make available the most up-to-date data for each topic and issue we cover. The frequency of data updates varies by the data source. Some data are updated every hour, some every 12 hours, some monthly, some annually, and some less frequently. The data set detail page will state the frequency.

Resource Watch is a dynamic platform that provides trusted and timely data for a sustainable future. Resource Watch features hundreds of data sets all in one place on the state of the planet’s resources and citizens. Users can visualize challenges facing people and the planet, from climate change to poverty, water risk to state instability, air pollution to human migration, and more.

Please contact Sergio Baldit at sergio.baldit@wri.org or Mansie Hough at mansie.hough@wri.org for media inquiries.

The data on Resource Watch come from various sources, including governments, intergovernmental organizations, research institutions, and scientific publications. The Resource Watch team works with experts to select data sets that are reliable and relevant to global sustainability challenges. Learn more about our curation process in our Data Policy.

We have a rigorous data collection process, guided by WRI’s independent, nonpartisan experts. Data on Resource Watch must come from established sources and be peer-reviewed or based on a transparent established methodology. Learn more about our curation process in our Data Policy. We strive to make the best data available. If you see something that could be improved, please let us know.

We’re always looking for the best open data available for Resource Watch. Please contact us at or send us a note at resourcewatch@wri.org.

The Resource Watch website was designed and built by Vizzuality. Learn more at Vizzuality.com.

Resource Watch includes a much wider range of environmental and socioeconomic data than WRI’s more focused platforms such as Global Forest Watch, Climate Watch, and Aqueduct. You can find these platforms and more in the App Gallery.

Anyone can use Resource Watch, but Resource Watch was designed with the following audiences in mind: government staff, business analysts, journalists, and researchers. Learn more about what you can do with Resource Watch.

We’re working on adding new data and features every day. Let us know what you’d like to see next, or sign up for our newsletter to get the latest updates.

Please contact us so we can fix it, or send us an email at resourcewatch@wri.org.

Convened by World Resources Institute, Resource Watch was developed by a partnership of organizations. “Resource Watch” refers to the online platform and the partnership of entities that created and sustain the initiative, and not to any one organization.

Overlaying two or more datasets on a Resource Watch map can illustrate geographic patterns, reveal potential connections between issues, support research with visualizations and highlight locations for further inquiry.

Example: To get a visual understanding of the relationship between deforestation and governance in a country you could overlay data on tree cover loss and the Environmental Democracy Index.

While overlays are valuable tools for discovering potential relationships and insights from the data, it is important to remember that correlation between datasets does not imply a causal relationship. A correlation may be interesting and spur further research, but researchers should refrain from drawing conclusions about causality without further evidence.

Example: When overlaying the national percent of rural population with access to electricity and the national percent of children underweight, you may notice a strong geographic correlation. From this, one should not conclude that low rural electricity access causes children to be underweight. The cause and effect relationship is not established because you have not eliminated other factors as causes.

You can easily share and embed overlays from Resource Watch by copying the hyperlink of the map you’ve created or using the share button to embed the map on a website. You should use the suggested citation on the metadata page and cite your source as being “accessed through Resource Watch.”

The maps shown on this platform do not imply the expression of any opinion on the part of Resource Watch or WRI concerning the legal status of any country or territory or concerning the delimitation of frontiers or boundaries.

Resource Watch and the World Resources Institute have access to a wide network of subject matter experts who can provide context and additional information for your analysis. If you have a story idea or a question for our data team, send us a note at resourcewatch@wri.org and we will do our best to connect you with the right person.

Accuracy and resolution vary by data set. Many of the data sets on Resource Watch are global. Higher resolution data may be available elsewhere at the national or subnational levels. You can find information and links to the source on each data set on its detail page, or learn more about our curation process in our Data Policy.

If you have questions about an overlay, any of the terminology used above or any of the data on Resource Watch, you can email us at resourcewatch@wri.org.

Every dataset on Resource Watch has its own dedicated metadata page with information on methodology, cautions, spatial scales and dates of coverage which you should check for every layer used in an overlay. It is always good practice to ensure that the time frame and spatial scales for your overlayed datasets are compatible before analyzing the data or drawing conclusions.

Example, regarding dates of coverage: When researching a country’s progress to increase tree cover in order to meet an international agreement, you should overlay tree cover change data that reflects changes in tree cover only after the agreement was signed.

Example, regarding spatial scales: When assessing the relationship between air quality and access to electricity, a misleading overlay would include data points of neighborhood-level air quality and national statistics about access to electricity. The air quality data, which is often collected in cities, may not align spatially with the lack of access to electricity, which includes statistics from rural areas.