transportationtransportationlogisticsinfrastructureaviationrailroadsmaritimetradeworld-bankLPIglobalcountry-leveltime-series

Transportation & Logistics Infrastructure Indicators

1960–2023

Free

Open dataset

Sample structure: 76.3 / 100

5 download links issued

Seller: waseemahmad

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Not documented — confirm reuse terms with the seller
Source / creator: Supplier-cited: World Bank Open Data
Collection method: Supplier description: Expansive dataset covering transportation infrastructure, logistics performance, and trade connectivity for 217 countries spanning 1960–2023. Contains 12,027 country-year observations across 23 transport and logistics indicators sourced from the World Bank, International Transport Forum, and World Logistics Performance Index.
Coverage / snapshot: 1960–2023
Data last updated: Not documented
Update schedule: Not documented

Source documentation ↗

Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract. Coverage is stated by the supplier; it has not been verified against every record in the full file.

Sample structure score: 76.3 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	26.3 / 50	147 of 280 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	147 of 147 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
country_code	0 / 10	string	0 / 10
country_name	0 / 10	string	0 / 10
region	0 / 10	string	0 / 10
income_group	0 / 10	string	0 / 10
year	0 / 10	number	0 / 10
rail_lines_total_km	9 / 10	number	0 / 1
rail_passengers_million_km	10 / 10	unknown	0 / 0
rail_freight_million_ton_km	9 / 10	number	0 / 1
roads_total_km	10 / 10	unknown	0 / 0
roads_paved_pct	10 / 10	unknown	0 / 0
air_passengers_carried	3 / 10	number	0 / 7
air_carrier_departures	3 / 10	number	0 / 7
air_freight_million_ton_km	4 / 10	number	0 / 6
container_port_traffic_teu	9 / 10	number	0 / 1
motor_vehicles_per_1000	10 / 10	unknown	0 / 0
passenger_cars_per_1000	10 / 10	unknown	0 / 0
road_traffic_deaths_per_100k	8 / 10	number	0 / 2
lpi_infrastructure_score	9 / 10	number	0 / 1
lpi_customs_score	9 / 10	number	0 / 1
lpi_logistics_competence	9 / 10	number	0 / 1
merchandise_imports_usd	0 / 10	number	0 / 10
merchandise_exports_usd	0 / 10	number	0 / 10
trade_pct_gdp	2 / 10	number	0 / 8
trade_in_services_pct_gdp	3 / 10	number	0 / 7
energy_use_per_capita_kg_oil_eq	6 / 10	number	0 / 4
urban_population_pct	0 / 10	number	0 / 10
population_total	0 / 10	number	0 / 10
gdp_per_capita_usd	0 / 10	number	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Country-year observations covering rail, road, aviation, maritime, and logistics performance across 23 indicators. Includes World Bank LPI scores, vehicle safety metrics, trade flows, and socioeconomic context. Coverage varies by indicator; aviation data at 66%, trade data at 95%, population and urbanization near 99%.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py 2496606c-947f-476e-8f51-ff27f4730b30 --output dataset.bin

Full supplier documentation

Original supplier listing: Transportation & Logistics Infrastructure — 217 Countries (1960–2023) Expansive dataset covering transportation infrastructure, logistics performance, and trade connectivity for 217 countries spanning 1960–2023. Contains 12,027 country-year observations across 23 transport and logistics indicators sourced from the World Bank, International Transport Forum, and World Logistics Performance Index. ## Key Indicators **Rail Infrastructure:** Total rail network (km), passenger-km, freight ton-km **Road Network:** Total road network (km), paved road percentage **Aviation:** Passengers carried, carrier departures, air freight (million ton-km) **Maritime:** Container port traffic (TEU) **Vehicles & Safety:** Motor vehicles and passenger cars per 1,000 people, road traffic deaths per 100,000 **Logistics Performance:** World Bank LPI scores for infrastructure, customs efficiency, and logistics competence **Trade Context:** Merchandise imports/exports (USD), trade as % of GDP, services trade **Socioeconomic Context:** Population, urbanization rate, GDP per capita, energy use per capita ## Sources - World Bank World Development Indicators (WDI) - World Bank Logistics Performance Index (LPI) - International Civil Aviation Organization (ICAO) via World Bank ## Coverage - **Countries:** 217 sovereign nations and territories - **Time span:** 1960–2023 (varies by indicator) - **Format:** UTF-8 CSV, one row per country-year - **Best coverage:** Aviation data (66%), trade data (95%), population/urbanization (99%)

Schema

Name	Type	Description
country_code	string
country_name	string
region	string
income_group	string
year	string
rail_lines_total_km	string
rail_passengers_million_km	string
rail_freight_million_ton_km	string
roads_total_km	string
roads_paved_pct	string
air_passengers_carried	string
air_carrier_departures	string
air_freight_million_ton_km	string
container_port_traffic_teu	string
motor_vehicles_per_1000	string
passenger_cars_per_1000	string
road_traffic_deaths_per_100k	string
lpi_infrastructure_score	string
lpi_customs_score	string
lpi_logistics_competence	string
merchandise_imports_usd	string
merchandise_exports_usd	string
trade_pct_gdp	string
trade_in_services_pct_gdp	string
energy_use_per_capita_kg_oil_eq	string
urban_population_pct	string
population_total	string
gdp_per_capita_usd	string

Sample Data

Preview a sample of the data before downloading.

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Transportation & Logistics Inf" })
// Found: 2496606c-947f-476e-8f51-ff27f4730b30
get_download_url({ dataset_id: "2496606c-947f-476e-8f51-ff27f4730b30" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/2496606c-947f-476e-8f51-ff27f4730b30/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"