Global digital-adoption signals (World Bank connectivity)
Global digital-adoption signals from World Bank connectivity indicators (keyless API, annual, ~1990 -> 2024, 200+ economies): Internet use (% of population), mobile subscriptions and fixed broadband subscriptions (per 100 people), with 10-year changes, OLS adoption-velocity trends, 3-sigma anomaly flags, 5-year linear-extrapolation forecasts, per-year cross-country ranks, a 5-year catch-up momentum gauge, the digital-divide gap versus the global median, and a connectivity-laggard flag. The first tech/digital-domain value-added set: which countries are catching up and which are falling behind. World Bank API terms permit non-commercial use only — commercial_use flagged 'no' in the UI. All rows normalized to ISO alpha-3 country codes so they join cleanly with every other global dataset. Raw data: World Bank (via ITU).
Quality
Attribution
World Bank (indicators via ITU); non-commercial use only per World Bank API Terms of Use; derived signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Reference year (World Bank API field date; YYYY, annual). |
| country | string | Country short name (World Bank API field country.value). |
| country_code | string | ISO 3166-1 alpha-3 country code (World Bank API field countryiso3code). |
| series_id | string | World Bank indicator code: IT.NET.USER.ZS (Individuals using the Internet, % of population), IT.CEL.SETS.P2 (Mobile cellular subscriptions per 100 people) or IT.NET.BBND.P2 (Fixed broadband subscriptions per 100 people). |
| series_label | string | Official World Bank indicator name as published in the API metadata. |
| value | float | Indicator value: percent of population (Internet use) or subscriptions per 100 people (mobile, fixed broadband); World Bank, sourced from the International Telecommunication Union (ITU). |
| change_10y_pp | float | |
| trend_slope | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| adoption_momentum_5y | float | |
| digital_divide_gap | float | |
| laggard_flag | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | change_10y_pp | trend_slope | anomaly_flag | forecast_1m | rank | adoption_momentum_5y | digital_divide_gap | laggard_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1960-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1965-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1970-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1975-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | — | 0 | — | 1 | — | 0 | 0 |
| 1976-01-01 | Aruba | ABW | IT.CEL.SETS.P2 | Mobile cellular subscriptions (per 100 people) | 0 | — | 0 | 0 | 0 | 1 | — | 0 | 0 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/digital_signals/wb_digital_adoption_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/digital_signals/wb_digital_adoption_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/digital_signals/wb_digital_adoption_signals
Tip: fetch /llms.txt for the full machine-readable catalog.