variables

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

2 rows where datasetId = 6573 sorted by id descending

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id ▲ name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
935641 Annual number of large-scale AI systems by country AI systems   2024-06-19 14:36:00 2024-07-08 16:47:58     2017-2024 Large-scale AI systems by country 6573     
{
    "unit": "AI systems"
}
 0     yearly_count grapher/artificial_intelligence/2024-06-19/epoch_compute_intensive_countries/epoch_compute_intensive_countries#yearly_count   2 major           Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. An AI system can have multiple authors, each potentially affiliated with different institutions, thus contributing to the count for multiple countries. The 2024 data is incomplete and was last updated 20 June 2024.   
[]
 The number of large-scale AI systems by country is determined by tallying the number of machine learning models that are associated with the geographical location of the researchers' affiliated institutions. It's important to note that a single model can have multiple authors, each potentially affiliated with different institutions, thus contributing to the count for multiple countries.     
{
    "note": "Confirmed large-scale AI models are those where the training compute exceeds 10\u00b2\u00b3 floating-point operations (FLOP)."
}
 int 
[]
 58772afe385f5bc711e60164da345395 1ac16fad70cf07b7de7f55e05ce17fc8
935640 Cumulative number of large-scale AI systems by country AI systems   2024-06-19 14:36:00 2024-07-08 16:47:56     2017-2024 Large-scale AI systems by country 6573     
{
    "unit": "AI systems"
}
 0     cumulative_count grapher/artificial_intelligence/2024-06-19/epoch_compute_intensive_countries/epoch_compute_intensive_countries#cumulative_count   2 major           Refers to the location of the primary organization with which the authors of a large-scale AI systems are affiliated. An AI system can have multiple authors, each potentially affiliated with different institutions, thus contributing to the count for multiple countries. The 2024 data is incomplete and was last updated 20 June 2024.   
[]
 The number of large-scale AI systems by country is determined by tallying the number of machine learning models that are associated with the geographical location of the researchers' affiliated institutions. It's important to note that a single model can have multiple authors, each potentially affiliated with different institutions, thus contributing to the count for multiple countries.     
{
    "note": "Confirmed large-scale AI models are those where the training compute exceeds 10\u00b2\u00b3 floating-point operations (FLOP)."
}
 int 
[]
 e2a186d9d2cd74b1d25e915a0ec89f83 68f77d259e8ab2634db1b8a8fbcaa9d2

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CREATE TABLE "variables" (
	"id" INTEGER PRIMARY KEY AUTOINCREMENT,
	"name" VARCHAR(750) NULL  ,
	"unit" VARCHAR(255) NOT NULL  ,
	"description" TEXT NULL  ,
	"createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP ,
	"updatedAt" DATETIME NULL  ,
	"code" VARCHAR(255) NULL  ,
	"coverage" VARCHAR(255) NOT NULL  ,
	"timespan" VARCHAR(255) NOT NULL  ,
	"datasetId" INTEGER NOT NULL  ,
	"sourceId" INTEGER NULL  ,
	"shortUnit" VARCHAR(255) NULL  ,
	"display" TEXT NOT NULL  ,
	"columnOrder" INTEGER NOT NULL DEFAULT '0' ,
	"originalMetadata" TEXT NULL  ,
	"grapherConfigAdmin" TEXT NULL  ,
	"shortName" VARCHAR(255) NULL  ,
	"catalogPath" VARCHAR(767) NULL  ,
	"dimensions" TEXT NULL  ,
	"schemaVersion" INTEGER NOT NULL DEFAULT '1' ,
	"processingLevel" VARCHAR(30) NULL  ,
	"processingLog" TEXT NULL  ,
	"titlePublic" VARCHAR(512) NULL  ,
	"titleVariant" VARCHAR(255) NULL  ,
	"attributionShort" VARCHAR(512) NULL  ,
	"attribution" TEXT NULL  ,
	"descriptionShort" TEXT NULL  ,
	"descriptionFromProducer" TEXT NULL  ,
	"descriptionKey" TEXT NULL  ,
	"descriptionProcessing" TEXT NULL  ,
	"licenses" TEXT NULL  ,
	"license" TEXT NULL  ,
	"grapherConfigETL" TEXT NULL  ,
	"type" TEXT NULL  ,
	"sort" TEXT NULL  ,
	"dataChecksum" VARCHAR(64) NULL  ,
	"metadataChecksum" VARCHAR(64) NULL,
	FOREIGN KEY("datasetId") REFERENCES "datasets" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT,
	FOREIGN KEY("sourceId") REFERENCES "sources" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT
);
CREATE UNIQUE INDEX "idx_catalogPath" ON "variables" ("catalogPath");
CREATE UNIQUE INDEX "unique_short_name_per_dataset" ON "variables" ("shortName", "datasetId");
CREATE UNIQUE INDEX "variables_code_fk_dst_id_7bde8c2a_uniq" ON "variables" ("code", "datasetId");
CREATE INDEX "variables_datasetId_50a98bfd_fk_datasets_id" ON "variables" ("datasetId");
CREATE UNIQUE INDEX "variables_name_fk_dst_id_f7453c33_uniq" ON "variables" ("name", "datasetId");
CREATE INDEX "variables_sourceId_31fce80a_fk_sources_id" ON "variables" ("sourceId");