Malaysia

MYS Glottolog Language Catalog MYS-GLOTTOLOG Language

393 rows · 1 table(s) Glottolog Language Catalog 0 1 2 3 4 SEL 12 CCL ▶

0 Admin 0 — 1 table(s)

MYS glottolog - languages — 131 rows, 16 columns

Standards-Aligned Fields (16)

Field Name	Type	Schema	Nulls	Unique
`glottocode`	string	CCL	0%	100
`name`	string	SEL	0%	100
`iso639_3`	string	CCL	1%	99
`level`	string	SEL	0%	1
`family_name`	string	CCL	100%	-
`family_glottocode`	string	CCL	1%	5
`parent_name`	string	SEL	100%	-
`parent_glottocode`	string	CCL	1%	68
`endangerment_status`	string	CCL	100%	-
`latitude`	float	CCL	0%	100
`longitude`	float	CCL	0%	99
`country_codes`	string	SEL+	0%	10
`classification`	string	CCL	0%	1
`child_family_count`	integer	CCL	0%	1
`child_language_count`	integer	CCL	0%	1
`child_dialect_count`	integer	CCL	0%	16

MYS UNHCR Refugee Data Finder MYS-UNHCR Migration

450 rows · 2 table(s) UNHCR Refugee Data Finder 0 1 2 3 48 CCL ▶

0 Admin 0 — 2 table(s)

MYS unhcr - hosted_populations — 75 rows, 24 columns

Standards-Aligned Fields (24)

Field Name	Type	Schema	Nulls	Unique
`year`	integer	CCL	0%	75
`country_of_origin`	string	CCL	100%	-
`country_of_origin_iso`	string	CCL	0%	1
`country_of_asylum`	string	CCL	100%	-
`country_of_asylum_iso`	string	CCL	0%	1
`population_type`	string	CCL	100%	-
`refugees`	integer	CCL	0%	75
`asylum_seekers`	integer	CCL	0%	34
`idps`	integer	CCL	0%	34
`stateless`	integer	CCL	0%	23
`others_of_concern`	integer	CCL	0%	30
`total_population`	string	CCL	100%	-
`female_total`	string	CCL	100%	-
`male_total`	string	CCL	100%	-
`female_0_4`	string	CCL	100%	-
`female_5_11`	string	CCL	100%	-
`female_12_17`	string	CCL	100%	-
`female_18_59`	string	CCL	100%	-
`female_60_plus`	string	CCL	100%	-
`male_0_4`	string	CCL	100%	-
`male_5_11`	string	CCL	100%	-
`male_12_17`	string	CCL	100%	-
`male_18_59`	string	CCL	100%	-
`male_60_plus`	string	CCL	100%	-

MYS unhcr - origin_populations — 75 rows, 24 columns

Standards-Aligned Fields (24)

Field Name	Type	Schema	Nulls	Unique
`year`	integer	CCL	0%	75
`country_of_origin`	string	CCL	100%	-
`country_of_origin_iso`	string	CCL	0%	1
`country_of_asylum`	string	CCL	100%	-
`country_of_asylum_iso`	string	CCL	0%	1
`population_type`	string	CCL	100%	-
`refugees`	integer	CCL	0%	75
`asylum_seekers`	integer	CCL	0%	34
`idps`	integer	CCL	0%	34
`stateless`	integer	CCL	0%	23
`others_of_concern`	integer	CCL	0%	30
`total_population`	string	CCL	100%	-
`female_total`	string	CCL	100%	-
`male_total`	string	CCL	100%	-
`female_0_4`	string	CCL	100%	-
`female_5_11`	string	CCL	100%	-
`female_12_17`	string	CCL	100%	-
`female_18_59`	string	CCL	100%	-
`female_60_plus`	string	CCL	100%	-
`male_0_4`	string	CCL	100%	-
`male_5_11`	string	CCL	100%	-
`male_12_17`	string	CCL	100%	-
`male_18_59`	string	CCL	100%	-
`male_60_plus`	string	CCL	100%	-

MYS Joshua Project MYS-JOSHUA_PROJECT Ethnolinguistic

564 rows · 2 table(s) Joshua Project 0 1 2 3 4 SEL 28 CCL ▶

0 Admin 0 — 2 table(s)

MYS joshua_project - languages — 99 rows, 7 columns

Standards-Aligned Fields (7)

Field Name	Type	Schema	Nulls	Unique
`language_code`	string	CCL	0%	99
`language_name`	string	SEL	0%	99
`iso639_3`	string	CCL	100%	-
`country_code`	string	SEL+	0%	2
`population`	string	CCL	100%	-
`primary_religion`	string	CCL	0%	5
`people_groups_count`	string	CCL	100%	-

MYS joshua_project - people_groups — 183 rows, 25 columns

Standards-Aligned Fields (25)

Field Name	Type	Schema	Nulls	Unique
`people_id`	integer	CCL	0%	100
`rop3_code`	string	CCL	0%	1
`people_name`	string	SEL	0%	100
`people_name_global`	string	CCL	0%	100
`country_code`	string	SEL+	0%	1
`country_name`	string	CCL	0%	1
`continent`	string	CCL	0%	1
`region`	string	CCL	0%	1
`population`	integer	CCL	0%	74
`population_global`	string	CCL	100%	-
`primary_religion`	string	CCL	0%	6
`religion_pct_christianity`	string	CCL	100%	-
`religion_pct_islam`	string	CCL	100%	-
`religion_pct_hinduism`	string	CCL	100%	-
`religion_pct_buddhism`	string	CCL	100%	-
`religion_pct_ethnic`	string	CCL	100%	-
`religion_pct_other`	string	CCL	100%	-
`primary_language`	string	CCL	0%	80
`language_code`	string	CCL	0%	80
`language_iso`	string	CCL	0%	1
`people_cluster`	string	CCL	0%	20
`affinity_bloc`	string	CCL	0%	5
`ethnicity_family`	string	CCL	100%	-
`latitude`	float	CCL	0%	100
`longitude`	float	CCL	0%	99

MYS World Bank Open Data MYS-WORLD_BANK Development Indicators

264 rows · 2 table(s) World Bank Open Data 0 1 2 3 23 SEL ▶

0 Admin 0 — 2 table(s)

MYS world_bank - development_indicators — 66 rows, 9 columns

Standards-Aligned Fields (9)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	SEL+	0%	1
`country_name`	string	SEL	0%	1
`year`	integer	SEL	0%	66
`population_count`	float	SEL	1.5%	65
`life_expectancy`	float	SEL	3%	64
`gdp_per_capita_usd`	float	SEL	1.5%	65
`literacy_rate_pct`	string	SEL	86.4%	9
`under5_mortality_per_1000`	float	SEL	3%	49
`poverty_headcount_pct`	string	SEL	92.4%	5

MYS world_bank - health_indicators — 66 rows, 14 columns

Standards-Aligned Fields (14)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	SEL+	0%	1
`country_name`	string	SEL	0%	1
`year`	integer	SEL	0%	66
`life_expectancy`	float	SEL	3%	64
`infant_mortality_per_1000`	float	SEL	3%	46
`under5_mortality_per_1000`	float	SEL	3%	49
`maternal_mortality_per_100k`	string	SEL	40.9%	24
`fertility_rate`	float	SEL	3%	63
`birth_rate_per_1000`	float	SEL	3%	64
`death_rate_per_1000`	float	SEL	3%	64
`physicians_per_1000`	float	SEL	31.8%	43
`hospital_beds_per_1000`	float	SEL	42.4%	27
`vaccination_rate_pct`	string	SEL	31.8%	20
`health_expenditure_pct_gdp`	string	SEL	63.6%	24

MYS Global Data Lab MYS-GDL Development Indices

1088 rows · 1 table(s) Global Data Lab 0 1 2 3 11 SEL ▶

1 Admin 1 — 1 table(s)

MYS gdl - subnational_indices — 544 rows, 11 columns

Standards-Aligned Fields (11)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	SEL+	0%	1
`region_code`	string	SEL	100%	-
`region_name`	string	SEL	0%	16
`year`	integer	SEL	0%	7
`level`	string	SEL	0%	2
`human_development_index`	float	SEL	0%	72
`health_index`	float	SEL	0%	7
`education_index`	float	SEL	0%	73
`income_index`	float	SEL	0%	73
`life_expectancy`	float	SEL	0%	7
`mean_years_schooling`	float	SEL	0%	87

MYS World Values Survey MYS-WVS Attitudes Values

1 rows · 1 table(s) World Values Survey 0 1 2 3 26 CCL ▶

0 Admin 0 — 1 table(s)

MYS wvs - country_aggregates — 1 rows, 26 columns

Standards-Aligned Fields (26)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	CCL	0%	1
`wave`	integer	CCL	0%	1
`wave_years`	string	CCL	0%	1
`source`	string	CCL	0%	1
`importance_religion`	integer	CCL	0%	1
`importance_family`	integer	CCL	0%	1
`importance_friends`	integer	CCL	0%	1
`trust_people`	integer	CCL	0%	1
`trust_family`	integer	CCL	0%	1
`life_satisfaction`	integer	CCL	0%	1
`happiness`	integer	CCL	0%	1
`freedom_choice`	integer	CCL	0%	1
`gender_jobs_scarce`	integer	CCL	0%	1
`gender_political_leaders`	integer	CCL	0%	1
`gender_university`	integer	CCL	0%	1
`justifiable_divorce`	integer	CCL	0%	1
`justifiable_homosexuality`	integer	CCL	0%	1
`immigration_policy`	integer	CCL	0%	1
`immigrants_jobs`	integer	CCL	0%	1
`immigrants_culture`	integer	CCL	0%	1
`confidence_government`	integer	CCL	0%	1
`confidence_parliament`	integer	CCL	0%	1
`confidence_police`	integer	CCL	0%	1
`confidence_courts`	integer	CCL	0%	1
`confidence_press`	integer	CCL	0%	1
`democracy_importance`	integer	CCL	0%	1

MYS Ethnic Power Relations Dataset MYS-EPR Political Ethnicity

6 rows · 1 table(s) Ethnic Power Relations Dataset 0 1 2 3 8 CCL ▶

0 Admin 0 — 1 table(s)

MYS epr - groups — 6 rows, 8 columns

Standards-Aligned Fields (8)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	CCL	0%	1
`year`	integer	CCL	0%	1
`ethnic_group_name`	string	CCL	0%	6
`ethnic_power_status`	string	CCL	0%	3
`ethnic_population_share`	float	CCL	0%	6
`ethnic_group_id`	float	CCL	0%	6
`group_relevance`	string	CCL	0%	1
`regional_autonomy`	string	CCL	0%	1

MYS D-PLACE MYS-DPLACE Ethnographic Societies

7 rows · 1 table(s) D-PLACE 0 1 2 3 18 CCL ▶

0 Admin 0 — 1 table(s)

MYS dplace - dplace_ea_societies — 7 rows, 18 columns

Standards-Aligned Fields (18)

Field Name	Type	Schema	Nulls	Unique
`country_code`	string	CCL	0%	1
`country_name`	string	CCL	0%	1
`society_id`	string	CCL	0%	7
`society_name`	string	CCL	0%	7
`dataset`	string	CCL	0%	1
`region`	string	CCL	0%	1
`latitude`	float	CCL	0%	6
`longitude`	float	CCL	0%	7
`language_glottocode`	string	CCL	0%	7
`language_name`	string	CCL	0%	1
`assignment_method`	string	CCL	0%	1
`assignment_confidence`	string	CCL	0%	1
`kinship_system`	string	CCL	0%	6
`marriage_pattern`	string	CCL	0%	7
`subsistence_pattern`	string	CCL	0%	7
`political_complexity`	string	CCL	0%	7
`religion_importance`	string	CCL	0%	7
`residence_pattern`	string	CCL	0%	6

MYS Global Organized Crime Index MYS-OCINDEX Crime Index

1 rows · 1 table(s) GI-TOC / ENACT 0 1 2 3 1 SEL 34 ext ▶

0 Admin 0 — 1 table(s)

MYS Organized Crime Scores 2025 — 1 rows, 35 columns

Standards-Aligned Fields (1)

Field Name	Type	Schema	Nulls	Unique
`oc_non_state_actors`	numeric	SEL	0%	1

Extension Fields (34) — supplemental data preserved outside core SEL/CCL schema

Field Name	Type	Nulls	Unique
`oc_anti_money_laundering`	numeric	0%	1
`oc_arms_trafficking`	numeric	0%	1
`oc_cannabis_trade`	numeric	0%	1
`oc_cocaine_trade`	numeric	0%	1
`oc_criminal_actors`	numeric	0%	1
`oc_criminal_markets`	numeric	0%	1
`oc_criminal_networks`	numeric	0%	1
`oc_criminality`	numeric	0%	1
`oc_cyber_dependent_crimes`	numeric	0%	1
`oc_economic_regulatory_capacity`	numeric	0%	1
`oc_extortion_and_protection_racketeering`	numeric	0%	1
`oc_fauna_crimes`	numeric	0%	1
`oc_financial_crimes`	numeric	0%	1
`oc_flora_crimes`	numeric	0%	1
`oc_foreign_actors`	numeric	0%	1
`oc_government_transparency_and_accountability`	numeric	0%	1
`oc_heroin_trade`	numeric	0%	1
`oc_human_smuggling`	numeric	0%	1
`oc_human_trafficking`	numeric	0%	1
`oc_illicit_trade_in_excisable_goods`	numeric	0%	1
`oc_international_cooperation`	numeric	0%	1
`oc_judicial_system_and_detention`	numeric	0%	1
`oc_law_enforcement`	numeric	0%	1
`oc_mafia_style_groups`	numeric	0%	1
`oc_national_policies_and_laws`	numeric	0%	1
`oc_non_renewable_resource_crimes`	numeric	0%	1
`oc_political_leadership_and_governance`	numeric	0%	1
`oc_prevention`	numeric	0%	1
`oc_private_sector_actors`	numeric	0%	1
`oc_resilience`	numeric	0%	1
`oc_state_embedded_actors`	numeric	0%	1
`oc_synthetic_drug_trade`	numeric	0%	1
`oc_territorial_integrity`	numeric	0%	1
`oc_trade_in_counterfeit_goods`	numeric	0%	1

MYS Google Community Mobility (2020-2022) MYS-GOOGLE-MOBILITY Mobility

16 rows · 1 table(s) Google 0 1 2 3 ▶

MYS Malaysia - Demographic, Health, Education and Tran MYS-HDX-Malaysia_-_Demographic,_Health,_Edu Indicators

319 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Economic, Social, Environmental, Health MYS-HDX-Malaysia_-_Economic,_Social,_Enviro Indicators

83035 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Education MYS-HDX-Malaysia_-_Education Indicators

16666 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Gender MYS-HDX-Malaysia_-_Gender Indicators

4793 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Health Indicators MYS-HDX-Malaysia_-_Health_Indicators Indicators

21755 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Human Development Indicators MYS-HDX-Malaysia_-_Human_Development_Indica Indicators

926 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Risk Assessment Indicators MYS-HDX-Malaysia_-_Risk_Assessment_Indicato Indicators

144 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Social Protection and Labor MYS-HDX-Malaysia_-_Social_Protection_and_La Indicators

6525 rows · 1 table(s) HDX 0 1 2 3 ▶

MYS Malaysia - Urban Development MYS-HDX-Malaysia_-_Urban_Development Indicators

621 rows · 1 table(s) HDX 0 1 2 3 ▶

HERA · Human Entity Reference Atlas by Masego Inc

SEL (34 mappings)

CCL (23 mappings)