ADB Asian Transport Observatory (ATO)

Operator: Asian Development Bank, with SLOCAT and AIIB URL: https://asiantransportobservatory.org/ (redirected from asiantransportoutlook.com) ADB Data Library: https://data.adb.org/dataset/asian-transport-outlook-database Zenodo mirror: https://zenodo.org/records/15232577 License: Personal and non-profit use with attribution. Commercial use requires written permission. Update cadence: Primary data extracted at least annually; secondary data updated after upstream sources refresh

What This Dataset Is

The largest structured transport dataset for Asia-Pacific. 459 national-level indicators across 51 economies spanning 1990-present (some projections to 2100), plus 260+ urban indicators covering 460 urban centres, ~1,200 transport project cost records, and ~1,100 policy documents.

Launched in March 2021 as the "Asian Transport Outlook", now rebranded to Asian Transport Observatory. Phase 3 (2023-2025, co-funded by AIIB) focused on translating data into policy-relevant insights.

Five Databases in One

ATO is actually five databases:

Database	Records	Coverage	URL Path
National indicators	459 indicators × 51 economies	1990-2100 (projection)	`/data/`
Urban indicators	260+ indicators × 460 urban centres	Varies	`/suddata/`
Cost database	~1,200 transport projects	Asia-Pacific	`/cost/`
Policy documents	~1,100 documents	51 economies	`/transportpolicy/`
Policy support activities	Mapping of international support	EST Forum countries	`/uncrd-est-support-activities-database/`

National Indicators — Schema

459 indicators across 9 categories

Category	Code	Count
Infrastructure	INF	54
Transport Activity & Services	TAS	108
Access & Connectivity	ACC	11
Road Safety	RSA	26
Air Pollution & Health	APH	43
Climate Change	CLC	51
Socio-Economic	SEC	94
Transport Policy	POL	40
Miscellaneous	MIS	32

Indicator code format

Three-part code: {CATEGORY}-{SUBCATEGORY}-{NUMBER}

Examples: SEC-TIV-001 (Transport Investments), TAS-PAT-001 (Passenger Activity). When multiple sources exist for the same indicator, suffixes like (1) or (2) are appended.

Indicator metadata

Each indicator carries:

Field	Description
Code	Three-part indicator code
Name	Human-readable indicator name
Definition	Full description
Scope	National, urban, rural, regional, or NA
Mode	Road, rail, shipping, aviation, all modes, or NA
Sector	Passenger, freight, combined, or NA
Source	Name and weblink of data source
Units	Unit of measurement
Status	Pending or complete

Download format

Three export views:

Indicator View — one indicator, all 51 economies, years as columns (wide format)
Country View — all selected indicators for one economy, years as columns
Raw Data (long format) — economy code, economy name, indicator code, indicator name, source, units, header, year

Available as .xlsx, .csv, .json.

Excel workbook structure (from Zenodo bulk download)

The Zenodo mirror has 11 Excel files (6.5 MB total). Internal layout:

Row 1: Title
Rows 2-10: Metadata (field name in col A, value in col B)
Row 14: "Series" label
Row 15: Column headers
Row 16+: Observation data
Columns: Economy Code, Economy Name, then year-indexed columns, plus Remarks and Source annotations

Urban Database — 260+ indicators

Covers 460 urban centres (412 Asia-Pacific, 48 rest of world). 41 cities have detailed assessments with 180 indicators plus policy information.

Same 9 categories as national data, with urban-specific subcategories (SEC-UDB-* codes). Same download formats.

Cost Database — ~1,200 projects

Transport infrastructure project costs for cost benchmarking and planning.

Fields per project record

Field	Description
Economy	Country
City	City name (where applicable)
Project type	Active Mobility, Air, Rail, Road Asset Management, Road Construction, Urban Public Transport
Typology	Subtype (e.g., Heavy Railway, BRTS, Metro, Highway Widening)
Infrastructure length	km
Cost (local currency)	In original currency
Cost (nominal USD)	At year of estimation
Cost (PPP USD)	Inflation and parity-adjusted
Unit cost	PPP USD per km
Cost type	Estimate or actual
Year	Year of estimate/construction start
Source	Link to original data
Remarks	Free text

Policy Document Corpus — ~1,100 documents

Searchable by keyword, economy, focus area, document type, and year range.

Focus tags (19 categories)

National (General), Climate, Road Safety, Shipping/Inland Water Transport, Energy, Urban, Aviation, National Development Policy, Rail, Road, Multi-Modal, SDG, Public Transit, E-mobility, Automotive, Active Transport, Logistics, Air Pollution, Gender, Others

Document types (10 categories)

National Development Policy, National Transport Policy, Transport Subsector Policy, National Report to International/Regional Processes, Transport Laws/Regulations, NDC, Long-term Strategies, Presentation by National Official, Secondary Source, Other

Geographic Coverage

51 economies (may now be 52). The 49 ADB regional developing members plus Australia, New Zealand, and possibly Iran and Russia.

Subregions: Central and West Asia, East Asia, South Asia, Southeast Asia, Pacific.

Economy metadata includes: ADB subregion, AIIB subregion, World Bank income group, and membership tags (LDC, LLC, SIDS, ASEAN, CAREC, G20, GMS, OECD, SAARC, SCO).

API Access

No dedicated REST API. This is the biggest gap.

Access method	Status
Dedicated REST API	Does not exist
ADB Data Library (CKAN)	data.adb.org hosts the ATO dataset page, but API access returns 403
ADB KIDB SDMX API	kidb.adb.org/api exists, but unclear whether ATO indicators are included
Internal AJAX endpoints	`/economyq`, `/indicatorq`, `/indicatorsndmq` — undocumented, not stable
Zenodo bulk download	11 Excel files, 6.5 MB total, DOI: 10.5281/zenodo.15232577
Web interface export	CSV/JSON/Excel per query — functional but manual
TDC Python package	`transport_data.ato` module fetches and converts to SDMX-ML

The TDC Python package (transport_data) is the most practical programmatic access path. It fetches ATO Excel workbooks, converts them to SDMX-ML, and validates economy codes. This is the integration route TGIS should use.

Join Keys

Economy code crosswalk — required

ATO uses ADB-specific 3-letter codes that diverge from ISO 3166-1 alpha-3 in several cases:

ADB Code	ISO Alpha-3	Economy
BAN	BGD	Bangladesh
CAM	KHM	Cambodia
INO	IDN	Indonesia
PRC	CHN	China
SRI	LKA	Sri Lanka
VIE	VNM	Viet Nam
TAP	TWN	Taipei,China
PHI	PHL	Philippines
BRU	BRN	Brunei

Matching codes (no crosswalk needed): AFG, ARM, AUS, AZE, FIJ, GEO, HKG, JPN, KAZ, KGZ, KOR, MLD, MON, NEP, NZL, PAK, PNG, THA, TKM, UZB and others.

A crosswalk table is essential for joining ATO data with World Bank (ISO alpha-3), OPSIS (ISO alpha-3), PortWatch (ISO alpha-3), and OECD/ITF data.

Other join dimensions

Dimension	ATO field	Linked datasets
Year	Year columns	All tabular datasets
Transport mode	Mode tag per indicator	ITF statistics, OPSIS layers
City name	Urban centre name	WRI city data, CAF OMU
Policy theme	Focus tags	SLOCAT NDC Tracker

Integration Path for TGIS

Bulk ingest via Zenodo — download the 11 Excel files, parse with the TDC transport_data.ato module, convert to SDMX-ML or flat CSV
Build ADB-to-ISO economy code crosswalk — essential for joining with any other dataset
Index by indicator category — map ATO's 9 categories to the TGIS taxonomy
Wrap as MCP server — expose query_ato_indicators(economy, category, year_range) and query_ato_urban(city, category) as agent tools
Policy corpus as RAG source — the ~1,100 policy documents are high-value context for an LLM answering questions about Asian transport policy

The cost database is particularly useful — per-km infrastructure costs by project type and country enable "how much would it cost to..." questions that no other open dataset answers for Asia-Pacific.