Download Global Address Files (CSV & Excel)
Directory of sovereign states and territories with published geographic files. All entries are normalized to the Repository’s global schema.
Interactive Coverage Map
Highlighted regions indicate territories with downloadable datasets. Click any active area to open its dedicated data page and formats.
File Selection and Validation Guide
Pick exports based on the workflow stage: CSV is practical for quick QA and spreadsheet checks, XLSX is useful for analyst reviews with filters, and JSON is preferred for ingestion pipelines, APIs, and automated validation. All formats follow the same canonical field model so teams can switch between tools without remapping columns at each handoff.
A reliable implementation sequence is: ingest raw file, normalize UTF-8 and delimiter settings, validate mandatory identifiers, reconcile hierarchy levels, then persist only records that pass structural checks. For data governance, keep version snapshots, changelog notes, and checksum verification in the same runbook used by engineering and operations.
Recommended control points include duplicate-key checks, coordinate plausibility ranges, null-value audit thresholds, and deterministic rollback criteria for bad loads. This keeps delivery, analytics, and customer support aligned when records are updated at scale.
Teams that manage recurring imports often pair this directory with a lightweight validation checklist: confirm expected row volume, verify schema version tags, compare a random sample of hierarchy paths, and run a small geocoding sanity pass before publishing. For operational clarity, keep one concise release note per snapshot describing additions, removals, and normalization adjustments. This helps data consumers align API behavior, reporting baselines, and fulfillment rules without reprocessing legacy files on every update. Maintaining this routine typically reduces ingestion incidents and accelerates root-cause analysis when external source changes introduce unexpected field patterns.
For onboarding new teams, publish a short field dictionary with examples for code, locality, hierarchy level, latitude, longitude, and source timestamp. Clear definitions reduce integration ambiguity and shorten review cycles when analysts, developers, and operations teams validate the same dataset through different tools. Keep one canonical reference sample per format so every team can compare parser output against a stable baseline before release. Pair this with automated smoke checks that verify delimiters, encoding, and required columns before downstream jobs start.
Territory Directory
Browse the full list of ISO-3166 registries and download CSV or Excel exports for each territory.