This dataset provides values for MAPS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

GEM's Global Socio-Economic Vulnerability Maps

The Global Social Vulnerability Map (viewable here: https://maps.openquake.org/map/sv-global-human-vulnerability) is a composite index that was developed to measure characteristics or qualities of social systems that create the potential for loss or harm. Here, social vulnerability helps to explain why some countries will experience adverse impacts from earthquakes differentially where the linking of social capacities with demographic attributes suggests that communities with higher percentages of age-dependent populations, homeless, disabled, under-educated, and foreign migrants are likely to exhibit higher social vulnerability than communities lacking these characteristics. Other relevant factors that affect the social vulnerability of populations include in-migration from foreign countries, population density, an accounting of slum populations, and international tourist arrivals.

The Global Economic Vulnerability Map (viewable here: https://maps.openquake.org/map/sv-global-economic-vulnerability) is a composite index that was designed primarily to measure the potential for economic losses from earthquakes due to a country’s macroeconomic exposure. This index is also an appraisal of the ability of countries to respond to shocks to their economic systems. Relevant indicators include the density of exposed economic assets such as commercial and industrial infrastructure. Metrics used to measure the ability of a country to withstand shocks to its economic system include reliance on imports/exports, government debt, and purchasing power. The economic vulnerability category also considers the economic vitality of countries since the economic vitality of a country can be directly related to the vulnerability and resilience of its populations. The latter includes measurements of single-sector economic dependence, income inequality, and employment status.

The Recovery/Reconstruction Potential Map (viewable here: https://maps.openquake.org/map/sv-global-recovery-and-reconstruction) is closely aligned with the concept of disaster resilience. Enhancing a country’s resilience to earthquakes is to improve its capacity to anticipate threats, to reduce its overall vulnerability, and to allow its communities to recover from adverse impacts from earthquakes when they occur. The measurement of recovery and reconstruction potential includes capturing inherent conditions that allow communities within a country to absorb impacts and cope with a damaging earthquake event, such as the density of the built environment, education levels, and political participation. It also encompasses post-event processes that facilitate a population’s ability to reorganize, change, and learn in response to a damaging earthquake.

Criteria for indicator selection
To choose indicators contextually exclusive for use in each map, the starting point was an exhaustive review of the literature on earthquake social vulnerability and resilience. For a variable to be considered appropriate and selected, three equally important criteria were met:

- variables were justified based on the literature regarding its relevance to one or more of the indices.
- variables needed to be of consistent quality and freely available from sources such as the United Nations and the World Bank; and
- variables must be scalable or available at various levels of geography to promote sub-country level analyses.

This procedure resulted in a ‘wish list’ of approximately 300 variables of which 78 were available and fit for use based on the three criteria.

Process for indicator selection
For variables to be allocated to an index, a two-tiered validation procedure was utilized. For the first tier, variables were assigned to each of the respective indices based on how each variable was cited within the literature, i.e., as being part of an index of social vulnerability, economic vulnerability, or recovery/resilience. For the second tier, machine learning and a multivariate ordinal logistic regression modelling procedure was used for external validation. Here, focus was placed on the statistical association between the socio-economic vulnerability indicators and the adverse impacts from historical earthquakes on a country-by country-basis.

The Global Significant Earthquake Database provided the external validation metrics that were used as dependent variables in the statistical analysis. To include both severe and moderate earthquakes within the dependent variables, adverse impact data was collected from damaging earthquake events that conformed to at least one of five criteria: 1) caused deaths, 2) caused moderate damage (approximately 1 million USD or more), 3) had a magnitude 7.5 or greater 4) had a Modified Mercalli Intensity (MMI) X or greater, or 5) generated a tsunami. This database was chosen because it considers low magnitude earthquakes that were damaging (e.g., MW >=2.5 & MW<=5.5) and contains socio-economic data such as the total number of fatalities, injuries, houses damaged or destroyed, and dollar loss estimates in USD.

Countries not demonstrating at least a minimal earthquake risk, i.e., seismicity <0.05 PGA (Pagani et al. 2018) and <$10,000 USD in predicted average annual losses (Silva et al. 2018) were eliminated from the analyses so as not to include countries with minimal to no earthquake risk. A total study area consists of 136 countries.

Indonesia Import: Value: Maps and Hydrographic or Similar Charts of All Kinds, Including Atlases, Wall Maps, Topographical Plans and Globes, Printed; Other than in Book Form data was reported at 0.014 USD mn in Jan 2025. This records an increase from the previous number of 0.014 USD mn for Dec 2024. Indonesia Import: Value: Maps and Hydrographic or Similar Charts of All Kinds, Including Atlases, Wall Maps, Topographical Plans and Globes, Printed; Other than in Book Form data is updated monthly, averaging 0.012 USD mn from Apr 2022 (Median) to Jan 2025, with 34 observations. The data reached an all-time high of 0.028 USD mn in Aug 2023 and a record low of 0.005 USD mn in Mar 2023. Indonesia Import: Value: Maps and Hydrographic or Similar Charts of All Kinds, Including Atlases, Wall Maps, Topographical Plans and Globes, Printed; Other than in Book Form data remains active status in CEIC and is reported by Statistics Indonesia. The data is categorized under Indonesia Premium Database’s Foreign Trade – Table ID.JAH147: Foreign Trade: by HS 8 Digits: Import: HS49: Printed Books, Newspapers, Pictures, and Other Products of Printing Industry, Manuscripts, Typescripts, and Plans.

This world map shows the member economies of Asia-Pacific Economic Cooperation (APEC).

This dataset represents Exclusive Economic Zones (EEZ) of the world. Up to now, there was no global public domain cover available.
Therefore, the Flanders Marine Institute decided to develop its own database. The database includes two global GIS-layers: one contains polylines that represent the maritime boundaries of the world countries, the other one is a polygon layer representing the Exclusive Economic Zone of countries. The database also contains digital information about treaties. Please note that the EEZ shapefile also includes the internal waters of each country.

An exclusive economic zone (EEZ) is a sea zone prescribed by the United Nations Convention on the Law of the Sea over which a sovereign state has special rights over the exploration and use of marine resources, including energy production from water and wind. This maritime boundary is designed to be used with other marine boundaries in order to help determine areas of trade, commerce and transportation. The 200 NM zone is measured country-by-country from the baseline maritime boundary (usually, but not in all cases, the mean low-water mark used is not the same thing as the coast line). For each country, we've obtained the official list of the baseline points from the United Nations under Maritime Space.The exclusive economic zone stretches much farther into sea than the territorial waters, which end at 12 NM (22 km) from the coastal baseline (if following the rules set out in the UN Convention on the Law of the Sea). Thus, the EEZ includes the contiguous zone. States also have rights to the seabed of what is called the continental shelf up to 350 NM (648 km) from the coastal baseline, beyond the EEZ, but such areas are not part of their EEZ. The legal definition of the continental shelf does not directly correspond to the geological meaning of the term, as it also includes the continental rise and slope, and the entire seabed within the EEZ. The chart below diagrams the overlapping jurisdictions which are part of the EEZ. When the (EEZ) boundary is between countries which are separated by less than 200NM is settled by international tribunals at any arbitrary line. Many countries are still in the process of extending their EEZs beyond 200NM using criteria defined in the United Nations Convention on the Law of the Sea. Dataset Summary The data for this layer were obtained from https://www.marineregions.org/. Link to source metadata.Preferred Citation: VLIZ (2014). Maritime Boundaries Geodatabase, version 8. Available online at http://www.marineregions.org/. Consulted on 2015-03-28.These limits and boundaries were created for NOAA's internal purposes only to update the charted maritime limits and maritime boundaries on NOAA charts. These limits and boundaries do not represent the official depiction. For official depiction, please see NOAA's paper or raster nautical charts (Sourced from NOAA_Version 4.1, 9/10/2013). Also, this map service contains data from NOAA and BOEM sources and the VLIZ (2014) Maritime Boundaries Geodatabase, version 8. Available online at Marineregions.org. Consulted on 2014-12-02.What can you do with this layer?Within its EEZ, a coastal country has: (a) sovereign rights for the purpose of exploring, exploiting, conserving and managing natural resources, whether living or nonliving, of the seabed and subsoil and the superjacent waters and with regard to other activities for the economic exploitation and exploration of the zone, such as the production of energy from the water, currents and winds; (b) jurisdiction as provided for in international law with regard to the establishment and use of artificial islands, installations, and structures, marine scientific research, and the protection and preservation of the marine environment, and (c) other rights and duties provided for under international law.The features in this layer can be used for showing areas and limits of sovereignty, revenue sharing, for siting a renewable energy project, for commerce routes, and for vessel transportation tracking within ArcGIS Desktop and ArcGIS Online. An example application of the layers is listed below, from the Marine Cadastre site. If, by example, a renewable energy project is located within state waters, the rules of leasing for that particular state will apply (and therefore vary by state), and no revenues will go to the federal government.If any portion of the project location falls within the federal 8(g) zone, then 27 percent of the revenues collected by the federal government will be shared with those states whose coastlines are within 15 miles of the geographic center of the project area. If the shoreline of more than one state is within 15 miles of the geographic center of the project, all the states will share the revenue payments in proportion to the inverse distance of the nearest points of their respective coastlines to the geographic center of the project. See more on this topic at U.S.C. and C.F.R. If the location is entirely in federal waters seaward of the 8(g) zone, no collected revenues will go to the state(s).This layer is a feature service, which means it can be used for visualization and analysis throughout the ArcGIS Platform. This layer is not editable.

Thailand Cargo Volume: IP: Thai Prosperity Terminal Co. Ltd (TPT) data was reported at 122,018.721 Metric Ton in Jun 2018. This records a decrease from the previous number of 162,431.279 Metric Ton for May 2018. Thailand Cargo Volume: IP: Thai Prosperity Terminal Co. Ltd (TPT) data is updated monthly, averaging 177,625.943 Metric Ton from Oct 2010 (Median) to Jun 2018, with 93 observations. The data reached an all-time high of 274,650.833 Metric Ton in May 2012 and a record low of 64,030.941 Metric Ton in Dec 2010. Thailand Cargo Volume: IP: Thai Prosperity Terminal Co. Ltd (TPT) data remains active status in CEIC and is reported by Map Ta Phut Industrial Port Office. The data is categorized under Global Database’s Thailand – Table TH.TA023: Port Statistics: Map Ta Phut Industrial of Thailand.

Abstract

The Partnership for Economic Inclusion (PEI) Landscape Survey 2019 - 2020 aimed to provide a comprehensive inventory of ongoing economic inclusion programs, or those that are in the development pipeline. For the purpose of the PEI Landscape Survey 2019 - 2020, the PEI management team (PEIMT) defined economic inclusion programs as multidimensional interventions that support and enable households to achieve sustainable livelihoods and increase their incomes and assets, while building human capital and promoting social inclusion.

To map the universe of economic inclusion programs, the PEIMT reviewed the World Bank financing portfolio as well as external sources. The first stage of the World Bank portfolio scan involved manually reviewing ongoing and pipeline programs from the Social Protection and Jobs (SPJ) Global Practice, listed in the World Bank Operations Portal, across all geographical regions. To determine whether a program focused on economic inclusion, the PEIMT reviewed each program's development objective and the component description included in its Project Appraisal Document (PAD) or, when a PAD was not available, its Project Information Document (PID), Project Paper (PP), or Project Information and Integrated Safeguards Data Sheet (PSDS).

Kind of data

Administrative records data [adm]

Sampling procedure

To map the universe of economic inclusion programs, the PEIMT reviewed the World Bank financing portfolio as well as external sources. The first stage of the World Bank portfolio scan involved manually reviewing ongoing and pipeline projects from the Social Protection and Jobs (SPJ) Global Practice, listed in the World Bank Operations Portal, across all geographical regions. To determine whether a program focused on economic inclusion, the PEIMT reviewed each project's development objective and the component description included in its Project Appraisal Document (PAD) or, when a PAD was not available, its Project Information Document (PID), Project Paper (PP), or Project Information and Integrated Safeguards Data Sheet (PSDS).

As a second stage, in order to validate each economic inclusion program and to speed up the mapping process, the PEIMT worked with the Text and Data Analytics (TDA) team from the Development Economics (DEC) department of the World Bank. Using a predefined set of keywords , the TDA team applied advanced text analytics to projects' summaries as well as to their PADs, PIDs, PPs, or PSDSs. They applied this technique to a total sample of approximately 1,200 projects (both active and pipeline) across all geographical regions under these Global Practices: Urban Resilience and Land; Social Development; Social Protection and Jobs; Finance, Competitiveness and Innovation; and Agriculture and Food. The team then ranked projects based on the number of keywords found. Any project that had at least one keyword could be considered an economic inclusion project. The PEIMT then compared the TDA-assisted selection with the manual selection for the SPJ projects and found that the results were accurate in correctly excluding projects. The TDA-assisted selection, however, also included far more projects than the manual review did.

To finalize the mapping of World Bank-financed economic inclusion projects, the PEIMT team manually reviewed the TDA-assisted selection of economic inclusion projects for the remaining Global Practices. The team assessed the relevance of a project based on project summaries, the types of words identified through the TDA techniques, and the frequency with which keywords came up in the project documents. In some cases, when a summary did not provide enough information, the PAD was reviewed to make a final decision. Overall, the TDA methods allowed the PEIMT to trim the number of projects for review by half. In total, the PEIMT identified 149 World Bank economic inclusion projects (representing 92 individual government programs in 57 countries ). Surveys were sent to these 92 unique identified programs, and responses were received back from 77 of them. The mapping of World Bank-supported projects was updated in June 2020 through a full manual review of nearly 50 projects from the Environment and Natural Resources Global Practice, which resulted in 17 additional projects and a total of 166 economic inclusion projects supported by the World Bank.

To map projects outside of World Bank operations, the PEIMT used the PEI's 2017 survey dataset to identify projects that were still ongoing as well as partners, including governments, NGOs, regional organizations, multilaterals, and other development partners involved in economic inclusion programming. Organizations were approached to self-identify programs that met a prescribed set of criteria, which had been developed based on the working definition of economic inclusion programs. Since the 2017 survey captured mostly non-government programs, in order to map other relevant economic inclusion interventions the PEIMT scanned several databases and inventories of social protection and productive inclusion programs, including ECLAC's database of labor and productive inclusion programs in Latin America and the Caribbean and Manchester's Social Assistance database. The number of projects identified outside of the World Bank portfolio totaled 146, from which 140 responses were expected and 127 responses were received.

Mode of data collection

Internet [int]

Brazil Exports: HS6: Vol: Maps & Hydrographic or Similar Charts of All Kinds,Incl Atlases,Wall Maps & Topographical Plans,Printed (Excl Those in Book Form,& Maps,Plans & Globes,In Relief) data was reported at 427.000 kg in Apr 2022. This records an increase from the previous number of 46.000 kg for Mar 2022. Brazil Exports: HS6: Vol: Maps & Hydrographic or Similar Charts of All Kinds,Incl Atlases,Wall Maps & Topographical Plans,Printed (Excl Those in Book Form,& Maps,Plans & Globes,In Relief) data is updated monthly, averaging 40.500 kg from Aug 1997 (Median) to Apr 2022, with 210 observations. The data reached an all-time high of 4,822.000 kg in May 2008 and a record low of 0.000 kg in Dec 2017. Brazil Exports: HS6: Vol: Maps & Hydrographic or Similar Charts of All Kinds,Incl Atlases,Wall Maps & Topographical Plans,Printed (Excl Those in Book Form,& Maps,Plans & Globes,In Relief) data remains active status in CEIC and is reported by Special Secretariat for Foreign Trade and International Affairs. The data is categorized under Brazil Premium Database’s Foreign Trade – Table BR.HS: 6 Digits: Section 10: Exports: Volume.

Imports: Sitc Basic Heading: Vol: Maps & Hydrographic,Similar Charts of All Kinds (Including Wall Maps, Topographical Plans & Globes), Printed, Not in Book Form data was reported at 4,274.000 kg in Mar 2025. This records an increase from the previous number of 215.000 kg for Feb 2025. Imports: Sitc Basic Heading: Vol: Maps & Hydrographic,Similar Charts of All Kinds (Including Wall Maps, Topographical Plans & Globes), Printed, Not in Book Form data is updated monthly, averaging 1,961.000 kg from Jan 1997 (Median) to Mar 2025, with 333 observations. The data reached an all-time high of 29,567.000 kg in Jul 1998 and a record low of 1.000 kg in May 1999. Imports: Sitc Basic Heading: Vol: Maps & Hydrographic,Similar Charts of All Kinds (Including Wall Maps, Topographical Plans & Globes), Printed, Not in Book Form data remains active status in CEIC and is reported by Special Secretariat for Foreign Trade and International Affairs. The data is categorized under Brazil Premium Database’s Foreign Trade – Table BR.SITC: Basic Heading: Section 08: Imports: Volume.

United States Exports: Maps & Hydrographic Charts etc, Atlases etc data was reported at 0.454 USD mn in Jan 2025. This records a decrease from the previous number of 0.498 USD mn for Dec 2024. United States Exports: Maps & Hydrographic Charts etc, Atlases etc data is updated monthly, averaging 1.053 USD mn from Jan 2002 (Median) to Jan 2025, with 277 observations. The data reached an all-time high of 4.156 USD mn in May 2023 and a record low of 0.268 USD mn in Apr 2022. United States Exports: Maps & Hydrographic Charts etc, Atlases etc data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.JA021: Exports: by Commodity: 4 Digit HS Code.

France Ex: FOB: Maps & Technical Drawings, Photographic Plates & Films data was reported at 2.000 EUR mn in Sep 2018. This stayed constant from the previous number of 2.000 EUR mn for Aug 2018. France Ex: FOB: Maps & Technical Drawings, Photographic Plates & Films data is updated monthly, averaging 2.000 EUR mn from Jan 2000 (Median) to Sep 2018, with 225 observations. The data reached an all-time high of 12.000 EUR mn in Sep 2001 and a record low of 1.000 EUR mn in Mar 2018. France Ex: FOB: Maps & Technical Drawings, Photographic Plates & Films data remains active status in CEIC and is reported by French National Institute for Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.JA003: Trade Statistics: by Industry: NAF rev 2.

Much recent attention has been paid to the interaction between poverty and conflict in developing countries. However, it is surprising that neither the academic nor the international development community has as of yet, systematically examined the influence of international inequalities upon poverty and conflict. The project proposes that the prevalence of poverty and conflict is strongly conditioned by countries' position within the international economic system. The nature of a country's economic ties with the rest of the world - often deeply unequal - can create significant dependencies and / or incentives to challenge the status quo, resulting in poverty-provoked violence. The project uses network analysis and matching methods. The network analysis is used to map out key international economic networks (aid, trade, and FDI) and generate measures of countries' direct and indirect relations with other states plus their position within the overall structure. These network measures are then used in a statistical method of matching countries to infer whether dependent countries are more likely to succumb to poverty-provoked conflict. The findings from the project will identify the extent to which international inequality traps lead to poverty and conflict traps in developing countries, and help to draw out the policy implications of this.

The geology data set for this map includes arcs, polygons, and labels that outline and describe the general geologic age and type of bedrock of Iran. The geologic provinces data set includes arcs, polygons, and labels of geologic and petroleum provinces interpreted and designated by R.M. Pollastro from a number of literature and map resources to assist in the assessment of oil and gas resources for the USGS World Energy Project. The oil and gas field centerpoints data set is a point coverage that marks the approximate centerpoints of oil and gas fields in Iran. Political boundaries are provided to show the general location of country and/or other reference 'political' boundaries.

This dataset represents the polygons of the Exclusive Economic Zones (EEZ) of the world, in a high resolution: the coastline is based on GSHHG (Global Self-consistent, Hierarchical, High-resolution Geography Database) The data set of the Exclusive Economic Zones can be used in many applications. In biogeography for example, it is possible to create for instance species distribution lists per country.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows four condensed maps of the World, depicting the state of international affairs involving Canada circa late 1950s. The top left map shows countries of the Commonwealth. Dependencies of the countries shown on this map are also indicated. The top right map shows member states of the North Atlantic Treaty Organization, and the Canadian delegation to the North Atlantic Council along with member and cooperating states and the permanent delegation of Canada for the Organization for European Economic Cooperation. The bottom left map shows member states of the Colombo Plan for Cooperative Economic Development in South and Southeast Asia along with locations of Canadian Trade Commissioners, Commercial Counselors and Commercial Secretaries. The bottom right map shows the member states, trust territories and mandates of the United Nations Organization. Locations of Canadian diplomatic representation abroad are also shown on this map. These four maps are projected in the North Polar Azimuthal Equidistant projection with the longitude of the central meridian being at 100 degrees W.

The average for 2023 based on 193 countries was -0.07 points. The highest value was in Liechtenstein: 1.61 points and the lowest value was in Syria: -2.75 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

This dataset contains a comprehensive collection of geographic shapefiles representing the boundaries of countries and territories worldwide. The shapefiles define the outlines of each nation and are based on the most recent and accurate geographical data available. The dataset includes polygon geometries that accurately represent the territorial extent of each country, making it suitable for various geographical analyses, visualizations, and spatial applications.

Content: The dataset comprises shapefiles in the ESRI shapefile format (.shp) along with associated files (.shx, .dbf, etc.) that contain the attributes of each country, such as country names, ISO codes, and other relevant information. The polygons in the shapefiles correspond to the land boundaries of each nation, enabling precise mapping and spatial analysis.

Use Cases: This dataset can be utilized in a wide range of applications, including but not limited to:

• Creating choropleth maps to visualize and analyze various socio-economic indicators by country.
• Conducting spatial analysis to study population distribution, territorial areas, and geographic trends.
• Performing geopolitical research and country-level comparisons.
• Integrating with other datasets to enrich geographic analyses and insights.

Source: The shapefile data is sourced from reputable and authoritative geographic databases, ensuring its accuracy and reliability for diverse applications.

The United States recorded a trade deficit of 60.18 USD Billion in June of 2025. This dataset provides the latest reported value for - United States Balance of Trade - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The World Development Indicators from the World Bank contain over a thousand annual indicators of economic development from hundreds of countries around the world.

Here's a list of the available indicators along with a list of the available countries.

For example, this data includes the life expectancy at birth from many countries around the world:

The dataset hosted here is a slightly transformed verion of the raw files available here to facilitate analytics.