Sources and methods

Where the numbers come from and how we check them

Name: APAC Open Marketing Database
Creator: aTELiER FACTORY
License: https://creativecommons.org/licenses/by/4.0/

APAC Open Marketing Database is made by aTELiER FACTORY. This page lists every source, every exclusion with its reason, and our methods.

Licence

The database as compiled (table design and documentation) is licensed under CC BY 4.0: free for business, research and AI training with attribution. The numbers themselves follow the terms of each source.

How to cite
APAC Open Marketing Database (aTELiER FACTORY), version 2026-10-12. https://atelierfactory.jp/data/asia/

However, figures from the World Health Organization (WHO), such as alcohol, tobacco and obesity, may not be used for commercial purposes (CC BY-NC-SA 3.0 IGO). If you reuse them, share them under the same terms.

How it is made

We download files published by national statistics offices and international organizations. Each file is kept unchanged, with its URL, retrieval date and SHA-256 fingerprint recorded.
Country and category names are mapped to international codes (ISO3 for countries, COICOP for spending, and so on).
We read each licence and include only data that may be reused freely with attribution.
Where several organizations publish the same figure, we pick one by a fixed priority and keep the others with their differences.
For the numbers shown in Asia Diorama, we reopen the original files and check that the recorded location contains exactly the same text.

Sources included (72)

Show the list

Source	Country	Licence
`wb`	all	CC BY 4.0
`icp`	all	CC BY 4.0
`worldbank_icp2021`	all	CC BY 4.0
`findex`	all	CC BY 4.0
`wpp`	all	CC BY 3.0 IGO
`UN Household Size and Composition`	all	CC BY 3.0 IGO
`sdg`	all	UN terms (reuse allowed with attribution)
`ilo`	all	CC BY 4.0
`adb`	all	CC BY 3.0 IGO
`oecd`	all	OECD terms (commercial use allowed with attribution)
`oecd_na_coicop1999`	all	OECD terms (commercial use allowed with attribution)
`oecd_na_coicop2018`	all	OECD terms (commercial use allowed with attribution)
`oecd_regions`	all	OECD terms (commercial use allowed with attribution)
`derived`	all	Follows the terms of its inputs
`dhs`	all	DHS API terms (attribution required)
`wikipedia`	all	CC0
`estat_kakei`	all	Japanese Government Standard Terms of Use v2.0
`eurostat_hbs`	all	CC BY 4.0
`nso_ses`	all	Open Government Licence Thailand
`nso_tha`	all	Open Government Licence Thailand
`pdh_hies`	all	CC BY 4.0
`psa_fies`	all	PSA terms (reuse allowed with attribution)
`singstat_hes`	all	Singapore Open Data Licence
`census`	all	Public domain
`dosm`	all	CC BY 4.0
`ons`	all	Open Government Licence v3.0
`hdx_codps`	all	CC BY-IGO (CC BY for Myanmar)
`hdx_cod_ps`	all	CC BY-IGO (CC BY for Myanmar)
`ghsl_ucdb`	all	CC BY 4.0
`overture_places`	all	CDLA Permissive 2.0
`abs_retail_hsi`	all	CC BY 4.0
`aus_abs_erp_state_age_sex`	all	CC BY 4.0
`aus_abs_hes2016_state_expenditure`	all	CC BY 4.0
`brn_deps_population_district`	all	DEPS terms (use allowed with attribution)
`csd_retail_sales`	all	DATA.GOV.HK terms (commercial use allowed with attribution)
`dosm_hes2024`	all	CC BY 4.0
`dosm_iowrt_3d`	all	CC BY 4.0
`dosm_population_state`	all	CC BY 4.0
`estat_census2025`	all	Japanese Government Standard Terms of Use v2.0
`estat_dashboard`	all	Japanese Government Standard Terms of Use v2.0
`estat_economic_census_2021`	all	Japanese Government Standard Terms of Use v2.0
`estat_kakei_annual_total_single`	all	Japanese Government Standard Terms of Use v2.0
`estat_population_estimates_2024`	all	Japanese Government Standard Terms of Use v2.0
`hkg_csd_lbnp_district`	all	DATA.GOV.HK terms (commercial use allowed with attribution)
`ind_fill_mospi_hces`	all	Government Open Data License - India
`jpn_nfis2019_pref_expenditure`	all	Japanese Government Standard Terms of Use v2.0
`kor_mois_resident_register_dong`	all	Korea Public Data Portal: no restriction on permitted use
`mdv_mbs_projection_atoll`	all	Free to reproduce with attribution (stated in the report)
`mng_nso_population_aimag`	all	CC BY 4.0
`nso_population_by_age_sex_province_monthly`	all	Open Government Licence Thailand
`nso_ses_avg_monthly_expenditure_2024`	all	Open Government Licence Thailand
`nso_ses_os_22`	all	Open Government Licence Thailand
`nzl_statsnz_hes2023_region_expenditure`	all	CC BY 4.0
`nzl_statsnz_subnational_2025`	all	CC BY 4.0
`ons_family_spending_workbook1`	all	Open Government Licence v3.0
`pak_census2023_age_sex_province`	all	PBS terms (commercial use allowed with attribution)
`pak_pbs_hies2025_province_expenditure`	all	PBS terms (commercial use allowed with attribution)
`pdh_df_hhexp`	all	CC BY 4.0
`pdh_hhcounts_subnational`	all	CC BY 4.0
`pdh_hies_income_region`	all	CC BY 4.0
`phl_popcen2024_province`	all	PSA terms (reuse allowed with attribution)
`psa_aspbi_2022`	all	PSA terms (reuse allowed with attribution)
`psa_fies2023_t1_income_expenditure_region`	all	PSA terms (reuse allowed with attribution)
`psa_fies2023_t7_expenditure_by_group_decile`	all	PSA terms (reuse allowed with attribution)
`sgp_singstat_resident_region_age_sex`	all	Singapore Open Data Licence
`singstat_D10072_multi_dimensional_data_cube_monthly_household_expenditure_a`	all	Singapore Open Data Licence
`singstat_M601481_full`	all	Singapore Open Data Licence
`singstat_M602171_retail_sales_value_based_on_2025_100_index_estimated_monthly`	all	Singapore Open Data Licence
`singstat_M602181_value_of_food_beverage_sales_based_on_2025_100_index_estimat`	all	Singapore Open Data Licence
`twn_dgbas_fies2025_county_expenditure`	all	Open Government Data License, version 1.0 (Taiwan; commercial use allowed with attribution)
`twn_ris_county_age_monthly`	all	Open Government Data License, version 1.0 (Taiwan; commercial use allowed with attribution)
`usa_fill_census_marts`	all	Public domain

Excluded data (29)

We excluded data whose licence says “humanitarian use only” or “non-commercial”, and data with no stated licence.

Show the list

Table	Source	Decision	Rows
`city_panel`	`ookla_speedtest`	excluded (licence forbids)	162,992
`market_size_retail`	`dsec_retail`	excluded (licence unclear)	26
`market_size_retail`	`nso_trade_turnover`	excluded (licence unclear)	9
`region_household_spending`	`brn_deps_hes2024_district_expenditure`	excluded (licence unclear)	4
`region_household_spending`	`btn_blss2022_expenditure_dzongkhag`	excluded (licence unclear)	60
`region_household_spending`	`chn_nbs_yb2021_consumption_province`	excluded (licence unclear)	279
`region_household_spending`	`khm_nis_cses2023_zone_expenditure`	excluded (licence unclear)	12
`region_household_spending`	`lka_hies2019_expenditure_province`	excluded (licence unclear)	144
`region_household_spending`	`mng_nso_hses_region_expenditure`	excluded (licence unclear)	6
`region_household_spending`	`npl_nso_nlss4_province_expenditure`	excluded (licence unclear)	35
`region_panel`	`hdx_codps`	excluded (licence forbids)	548
`region_population_age`	`hdx_codps`	excluded (licence forbids)	26,852
`region_population_latest`	`chn_census2020_province`	excluded (licence unclear)	775
`region_population_latest`	`fsm_census2023_state`	excluded (licence unclear)	80
`region_population_latest`	`hdx_cod_ps`	excluded (licence forbids)	578
`region_population_latest`	`idn_kemkes_profil2025_province`	excluded (licence unclear)	114
`region_population_latest`	`ind_tgpp_projection_state`	excluded (licence unclear)	507
`region_population_latest`	`lka_census2024_district`	excluded (licence unclear)	125
`region_population_latest`	`lka_dcs_midyear_district`	excluded (licence unclear)	75
`region_population_latest`	`mmr_census2024_state`	excluded (licence unclear)	437
`region_population_latest`	`npl_nso_projection_province`	excluded (licence unclear)	315
`region_population_latest`	`pak_planning_projection_province`	excluded (licence unclear)	15
`region_population_latest`	`plw_bbp_census2020_state`	excluded (licence unclear)	16
`region_population_latest`	`png_census2024_province`	excluded (licence unclear)	66
`region_population_latest`	`prk_census2008_province`	excluded (licence unclear)	171
`region_population_latest`	`slb_census2019_province`	excluded (licence unclear)	220
`region_population_latest`	`vnm_nso_pxweb_population_province`	excluded (licence unclear)	189
`region_population_latest`	`vut_census2020_province`	excluded (licence unclear)	152
`regions`	`hdx_codps`	excluded (licence forbids)	548

All tables

Show 24 tables

Table	Rows	Description
`countries`	49	iso3, name_ja, name_en, region_ja, is_core, in_apac, un_m49, wb_code, adb_code, income_group, capital
`indicators`	53	id, name_ja, explain_ja, unit, kind, source_priority, caution
`country_panel`	131,872	iso3, year, indicator, value, source, source_code, name_ja
`country_panel_all_sources`	187,780	iso3, year, indicator, value, source, source_code, name_ja
`country_latest`	2,299	iso3, name_ja, indicator, indicator_ja, year, value, unit, source, source_code, is_projection
`source_agreement`	58	indicator, source_a, source_b, pairs, how_far, median_ratio_a_over_b, verdict
`population_age`	108,720	iso3, name_ja, year, age_band, pop_total, pop_male, pop_female, is_projection
`spending_structure`	3,648	iso3, year, source, basis, coicop, coicop_ja, group6, share_pct, amount, currency, note, name_ja
`spending_group6`	1,842	iso3, name_ja, year, source, basis, group6, share_pct
`regions`	7,724	iso3, level, region_code, region_name, parent_name, level_name_local, source, country_ja
`region_population_age`	557,631	iso3, level, region_code, year, sex, age_band, population, source
`region_panel`	26,473	iso3, level, region_code, year, source, pop_total, pop_0_14_pct, pop_15_34_pct, pop_35_64_pct, pop_65p_pct, region_name, parent_name, country_ja
`category_master`	57	category_id, category_ja, group_ja, icp_series, dhs_indicators, findex_series, wiki_articles
`category_involvement`	32,033	iso3, category_id, measure, year, value, source, breakdown, note, category_ja, group_ja, country_ja
`category_involvement_latest`	4,101	iso3, category_id, measure, year, value, source, breakdown, note, category_ja, group_ja, country_ja
`category_interest_monthly`	93,336	lang, category_id, yyyymm, views, vpm
`language_market_map`	26	lang, market, lang_ja
`cities`	11,422	city_id, city_name, city_names_all, country_name, area_km2, pop_2025, income_group_wb, world_region, is_capital, iso3, lon, lat, in_apac, country_ja, pop_2030, pop_2015, pop_growth_2015_2025_pct, gdp_ppp_per_capita, hdi, pop_young_pct, pop_older_pct, places_total, source
`city_panel`	889,315	city_id, year, indicator, value, iso3, city_name, source
`region_population_latest`	27,692	iso3, adm1_id, measure, sign, source_dataset, level, region_name_source, age_group, sex, value, unit, src_file, src_loc, src_value, source
`region_household_spending`	4,748	iso3, adm1_id, adm1_name, region_name_source, match_how, survey, year, area, household_type, measure, currency, price_basis, group_level, group_code, group_codes_covered, group_match, group_name_coicop, group_name_source, value, share_pct, share_basis, total_value, comparable_across_countries, comparability_note, source_dataset, src_file, src_loc, src_value, note, source
`market_size_household`	9,679	layer, iso3, year, period_label, survey, source_dataset, source_table, household_scope, item_code, item_name, item_level, item_path, coicop2018_code, coicop2018_name_ja, coicop2018_match, value_lc, currency, value_usd, fx_lc_per_usd, formula, inputs, input_years, year_gap_note, comparable_across_countries, approx, approx_reason, note, source
`market_size_icp`	1,860	layer, iso3, year, icp_series, icp_series_name, scope, coicop2018_code, coicop2018_name_ja, coicop2018_match, value_ppp_intl_usd, value_usd, value_lc_icp_published, currency, population_used, formula, inputs, input_years, year_gap_note, comparable_across_countries, approx, approx_reason, note, source
`market_size_retail`	1,139	layer, iso3, year, source_dataset, measure, classification, industry_code, industry_name, isic4_code, isic4_match, sector, value_lc, currency, value_usd, fx_lc_per_usd, periods_summed, formula, inputs, input_years, year_gap_note, comparable_across_countries, approx, approx_reason, note, source

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