datasets
Data license: CC-BY
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id ▲ | name | description | createdAt | updatedAt | namespace | isPrivate | createdByUserId | metadataEditedAt | metadataEditedByUserId | dataEditedAt | dataEditedByUserId | nonRedistributable | isArchived | sourceChecksum | shortName | version | updatePeriodDays |
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6652 | COVID-19, decoupling of indicators | 2024-07-31 15:42:15 | 2024-07-31 15:42:16 | covid | 0 | ETL 74 | 2024-07-31 15:42:17 | ETL 74 | 2024-07-31 15:42:17 | ETL 74 | 0 | 0 | 06601e33ab6ea9439d12d6bdecead6fb | decoupling | latest | 0 | |
6651 | Long run homicide rates (1250-2022; Eisner, WHO, UNODC) | 2024-07-31 12:15:49 | 2024-07-31 12:15:49 | homicide | 0 | ETL 74 | 2024-07-31 12:15:50 | ETL 74 | 2024-07-31 12:15:50 | ETL 74 | 0 | 0 | 6a033264aad7fcb3fec97d570f537e96 | homicide_long_run_omm | 2024-07-30 | ||
6650 | World Bank's income classification | 2024-07-31 09:04:31 | 2024-07-31 09:04:32 | wb | 0 | ETL 74 | 2024-07-31 09:04:32 | ETL 74 | 2024-07-31 09:04:32 | ETL 74 | 0 | 0 | 8a8539e4be0976b620652a22bd35ea9b | income_groups | 2024-07-29 | 365 | |
6649 | WHO Mortality Database | 2024-07-30 17:20:39 | 2024-07-30 17:20:52 | homicide | 0 | ETL 74 | 2024-07-30 17:20:52 | ETL 74 | 2024-07-30 17:20:52 | ETL 74 | 0 | 0 | cb0e295e2b05243dbf525e3d77902f48 | who_mort_db | 2024-07-30 | ||
6648 | COVID-19, sequencing | 2024-07-30 16:30:51 | 2024-07-31 15:42:27 | covid | 1 | ETL 74 | 2024-07-31 15:42:27 | ETL 74 | 2024-07-31 15:42:27 | ETL 74 | 1 | 0 | cbe7f431de5a8b0f276d73aafeaca919 | sequence | latest | 14 | |
6647 | Global Military Spending Dataset | 2024-07-30 12:02:33 | 2024-07-30 12:02:36 | harvard | 0 | ETL 74 | 2024-07-30 12:02:37 | ETL 74 | 2024-07-30 12:02:37 | ETL 74 | 0 | 0 | 3795d8b929aab45a966880b1d0112ca3 | global_military_spending_dataset | 2024-07-22 | 365 | |
6646 | SIPRI Military Expenditure Database | 2024-07-30 12:02:09 | 2024-07-30 12:02:11 | sipri | 0 | ETL 74 | 2024-07-30 12:02:11 | ETL 74 | 2024-07-30 12:02:11 | ETL 74 | 0 | 0 | c68fe4a79605a62e7d11d6ffab521702 | military_expenditure | 2024-07-08 | 365 | |
6645 | National Material Capabilities | 2024-07-30 12:02:08 | 2024-07-30 12:02:11 | cow | 0 | ETL 74 | 2024-07-30 12:02:11 | ETL 74 | 2024-07-30 12:02:11 | ETL 74 | 0 | 0 | 772b81e9c7a807bc10ec3842085f6535 | national_material_capabilities | 2024-07-26 | 365 | |
6644 | AI Index Report | 2024-07-29 17:27:33 | 2024-07-29 17:27:35 | artificial_intelligence | 0 | ETL 74 | 2024-07-29 17:27:35 | ETL 74 | 2024-07-29 17:27:35 | ETL 74 | 0 | 0 | dffff120722f2e2ffdf0e02877ed43cd | ai_adoption | 2024-06-28 | 365 | |
6643 | Maternal mortality (OWID based on UN MMEIG & other sources) (1751-2020) | 2024-07-29 15:05:54 | 2024-07-31 12:58:56 | maternal_mortality | 0 | ETL 74 | 2024-07-31 12:58:57 | ETL 74 | 2024-07-31 12:58:57 | ETL 74 | 0 | 0 | db20d6d776be42677ac7874dfef0d83e | maternal_mortality | 2024-07-08 | 365 | |
6642 | Trends in maternal mortality | 2024-07-29 15:05:37 | 2024-07-29 15:05:39 | un | 0 | ETL 74 | 2024-07-29 15:05:40 | ETL 74 | 2024-07-29 15:05:40 | ETL 74 | 0 | 0 | 232190f26808f8d40de67d8f0bea9154 | maternal_mortality | 2024-07-08 | 365 | |
6641 | ICD Codes | 2024-07-29 12:47:23 | 2024-07-29 12:47:24 | who | 0 | ETL 74 | 2024-07-29 12:47:24 | ETL 74 | 2024-07-29 12:47:24 | ETL 74 | 0 | 0 | 661bf489ff17feb9807f80af5caa7dc5 | icd_codes | 2024-07-29 | 365 | |
6640 | Trends in Machine Learning Hardware | 2024-07-29 11:40:02 | 2024-07-29 11:40:03 | artificial_intelligence | 0 | ETL 74 | 2024-07-29 11:40:04 | ETL 74 | 2024-07-29 11:40:04 | ETL 74 | 0 | 0 | f774340130f8c11359d443ee3b71558b | epoch_gpus | 2024-07-11 | 365 | |
6639 | WHO Mortality Database | 2024-07-29 10:13:40 | 2024-07-29 10:21:55 | who | 0 | ETL 74 | 2024-07-29 10:21:55 | ETL 74 | 2024-07-29 10:21:55 | ETL 74 | 0 | 0 | 567ced30224e9ba526dca94182ad30f5 | mortality_database | 2024-07-26 | 365 | |
6638 | HDI per capita land use (UNDP Project) | 2024-07-28 15:37:22 | 2024-07-28 15:37:22 | fasttrack | 0 | ETL 74 | 2024-07-28 15:37:23 | ETL 74 | 2024-07-28 15:37:23 | ETL 74 | 0 | 0 | d66529ae8cf2da035165387310f70d6b | hdi_per_land_use | latest | ||
6637 | COVID-19, confirmed cases and deaths | 2024-07-26 15:16:56 | 2024-07-31 15:43:12 | covid | 0 | ETL 74 | 2024-07-31 15:43:12 | ETL 74 | 2024-07-31 15:43:12 | ETL 74 | 0 | 0 | 149ac16d95a19d9b91111ded3a752aae | cases_deaths | latest | 31 | |
6636 | Tree Cover Loss by Dominant Driver | 2024-07-26 14:48:55 | 2024-07-26 14:48:57 | forests | 0 | ETL 74 | 2024-07-26 14:48:57 | ETL 74 | 2024-07-26 14:48:57 | ETL 74 | 0 | 0 | a2a5f60212ff2b951bdaa2f40a0fe4a5 | tree_cover_loss_by_driver | 2024-07-10 | 0 | |
6635 | Anthromes | 2024-07-26 14:39:27 | 2024-07-26 14:39:39 | papers | 0 | ETL 74 | 2024-07-26 14:39:40 | ETL 74 | 2024-07-26 14:39:40 | ETL 74 | 0 | 0 | 1f5b22e66978f8a897572ac22ae0faa3 | anthromes | 2024-01-05 | ||
6634 | HDI per capita CO2 (UNDP Project) | 2024-07-26 14:02:23 | 2024-07-28 12:50:15 | fasttrack | 0 | ETL 74 | 2024-07-28 12:50:16 | ETL 74 | 2024-07-28 12:50:16 | ETL 74 | 0 | 0 | e7ab2b5df826f9e01c9e1e33abdc97f7 | hdi_per_co2 | latest | ||
6633 | Country Activity Tracker: Artificial Intelligence | 2024-07-25 13:03:47 | 2024-07-30 06:18:30 | artificial_intelligence | 0 | ETL 74 | 2024-07-30 06:18:31 | ETL 74 | 2024-07-30 06:18:31 | ETL 74 | 0 | 0 | 177bde1cdd4709b76be7174c8e32f758 | cset | 2024-07-16 | 365 | |
6632 | International Migrant Stock | 2024-07-25 12:44:19 | 2024-07-25 12:44:34 | un | 0 | ETL 74 | 2024-07-25 12:44:35 | ETL 74 | 2024-07-25 12:44:35 | ETL 74 | 0 | 0 | 3af5b039f6b23dd34cc22df7dcc1335d | migrant_stock | 2024-07-16 | 730 | |
6631 | Robot intelligence survey | 2024-07-25 12:17:08 | 2024-07-25 12:17:09 | artificial_intelligence | 0 | ETL 74 | 2024-07-25 12:17:10 | ETL 74 | 2024-07-25 12:17:10 | ETL 74 | 0 | 0 | c9e8187433ce3681f1df1e65f752fc7e | yougov_robots | 2024-07-23 | 180 | |
6630 | How worried are Americans about being automated out of a job? | 2024-07-25 12:17:08 | 2024-07-25 12:17:09 | artificial_intelligence | 0 | ETL 74 | 2024-07-25 12:17:10 | ETL 74 | 2024-07-25 12:17:10 | ETL 74 | 0 | 0 | a80c0f8ec0f6e37345b983756d91f21f | yougov_job_automation | 2024-07-23 | 180 | |
6629 | AI Performance on Imagenet | 2024-07-25 11:21:52 | 2024-07-25 12:17:07 | artificial_intelligence | 0 | ETL 74 | 2024-07-25 12:17:08 | ETL 74 | 2024-07-25 12:17:08 | ETL 74 | 0 | 0 | 3994b97eac65be0b1864633daf7677c3 | papers_with_code_imagenet | 2024-07-23 | ||
6628 | Climate Change Impacts - Monthly | 2024-07-23 10:09:46 | 2024-07-31 07:50:09 | climate | 0 | ETL 74 | 2024-07-31 07:50:10 | ETL 74 | 2024-07-31 07:50:10 | ETL 74 | 0 | 0 | 9a645151da184c3053e2f989a5cc08b7 | climate_change_impacts_monthly | 2024-07-23 | 60 | |
6627 | Climate Change Impacts - Annual | 2024-07-23 10:09:46 | 2024-07-31 07:49:59 | climate | 0 | ETL 74 | 2024-07-31 07:49:59 | ETL 74 | 2024-07-31 07:49:59 | ETL 74 | 0 | 0 | 95c0acaa5df6f16d48b939bae375d912 | climate_change_impacts_annual | 2024-07-23 | 60 | |
6626 | Population doubling times | 2024-07-22 15:00:52 | 2024-07-30 06:18:11 | demography | 0 | ETL 74 | 2024-07-30 06:18:12 | ETL 74 | 2024-07-30 06:18:12 | ETL 74 | 0 | 0 | 6b8a73b193408d84ae06a937941e7a69 | population_doubling_times | 2024-07-18 | 730 | |
6625 | Natural Earth - Large scale data (1:10m Cultural Vectors) | 2024-07-19 08:03:32 | 2024-07-19 10:07:35 | geography | 0 | ETL 74 | 2024-07-19 10:07:36 | ETL 74 | 2024-07-19 10:07:36 | ETL 74 | 0 | 0 | b7f648c81c47daf0fa527620dd47ca05 | latitude | 2024-07-18 | 0 | |
6624 | Notable AI systems by researcher affiliation | 2024-07-17 16:46:29 | 2024-07-17 16:46:31 | artificial_intelligence | 0 | ETL 74 | 2024-07-17 16:46:31 | ETL 74 | 2024-07-17 16:46:31 | ETL 74 | 0 | 0 | 0ca234f23014e08c78c1c99cf3d55bb8 | epoch_aggregates_affiliation | 2024-07-10 | 31 | |
6623 | Parameter, Compute and Data Trends in Machine Learning | 2024-07-17 16:46:28 | 2024-07-17 16:46:30 | artificial_intelligence | 0 | ETL 74 | 2024-07-17 16:46:30 | ETL 74 | 2024-07-17 16:46:30 | ETL 74 | 0 | 0 | 097c404197d3953b357d48a9b2b3f97d | epoch | 2024-07-10 | 31 | |
6622 | Notable AI systems by domain type | 2024-07-17 16:46:28 | 2024-07-17 21:21:38 | artificial_intelligence | 0 | ETL 74 | 2024-07-17 21:21:38 | ETL 74 | 2024-07-17 21:21:38 | ETL 74 | 0 | 0 | ad3f29e8f6c432a5b9265377addd8e30 | epoch_aggregates_domain | 2024-07-10 | 31 | |
6621 | Population | 2024-07-17 09:27:08 | 2024-07-30 06:18:03 | demography | 0 | ETL 74 | 2024-07-30 06:18:04 | ETL 74 | 2024-07-30 06:18:04 | ETL 74 | 0 | 0 | 5d507a8fb89ccc8f44acf9dc580abd6f | population | 2024-07-15 | 730 | |
6620 | Rock-to-metal mining ratio (Nassar et al. 2022 and Wang et al. 2024) | 2024-07-16 08:49:21 | 2024-07-16 08:49:21 | fasttrack | 0 | ETL 74 | 2024-07-16 08:49:22 | ETL 74 | 2024-07-16 08:49:22 | ETL 74 | 0 | 0 | 7e7f25560fa36f67e011efa98060321a | rock_metal_ratio_nassar_wang | latest | ||
6619 | Historical World Population Prospects | 2024-07-12 17:57:23 | 2024-07-15 12:51:34 | demography | 0 | ETL 74 | 2024-07-15 12:51:34 | ETL 74 | 2024-07-15 12:51:34 | ETL 74 | 0 | 0 | 94bccbe8d3c318f970bd9a23d25ca835 | un_wpp_historical | 2024-07-12 | 740 | |
6618 | World Population Prospects (projections full timeseries) | 2024-07-12 03:19:48 | 2024-07-15 13:00:13 | un | 0 | ETL 74 | 2024-07-15 13:00:14 | ETL 74 | 2024-07-15 13:00:14 | ETL 74 | 0 | 0 | 1d60785e408c1948c4cd307bc40ff9b7 | un_wpp_full | 2024-07-12 | ||
6617 | World Population Prospects | 2024-07-12 03:18:25 | 2024-07-15 12:56:26 | un | 0 | ETL 74 | 2024-07-15 12:56:26 | ETL 74 | 2024-07-15 12:56:26 | ETL 74 | 0 | 0 | bf2c33e4dfdb590098e9b99e52631789 | un_wpp | 2024-07-12 | ||
6616 | World Population Prospects (projections full timeseries) | 2024-07-11 17:26:52 | 2024-07-15 09:57:33 | un | 1 | ETL 74 | 2024-07-11 17:28:27 | ETL 74 | 2024-07-11 17:28:27 | ETL 74 | 0 | 1 | de0fd180660dbfa95b44b62b38597d00 | un_wpp_full | 2024-07-11 | ||
6615 | World Population Prospects | 2024-07-11 17:26:51 | 2024-07-15 09:45:30 | un | 1 | ETL 74 | 2024-07-11 17:29:11 | ETL 74 | 2024-07-11 17:29:11 | ETL 74 | 0 | 1 | b6e7eae1f20b7d0402d3ffbe93a70296 | un_wpp | 2024-07-11 | ||
6614 | AI Index Report | 2024-07-10 09:35:46 | 2024-07-10 09:35:49 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:49 | ETL 74 | 2024-07-10 09:35:49 | ETL 74 | 0 | 0 | 4defd7e3dca39c9f613e1d9b937091a1 | ai_phds | 2024-06-28 | 365 | |
6613 | AI Index Report | 2024-07-10 09:35:46 | 2024-07-25 22:50:45 | artificial_intelligence | 0 | ETL 74 | 2024-07-25 22:50:46 | ETL 74 | 2024-07-25 22:50:46 | ETL 74 | 0 | 0 | 5117851dd34bc2802e26714be86a95a2 | ai_strategies | 2024-06-28 | 365 | |
6612 | AI Index Report | 2024-07-10 09:35:45 | 2024-07-10 09:35:47 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:48 | ETL 74 | 2024-07-10 09:35:48 | ETL 74 | 0 | 0 | 6dbd6ba8c017d67bd012fe1414a003a9 | ai_bills | 2024-06-28 | 365 | |
6611 | UNESCO Institute for Statistics (UIS) - Education | 2024-07-09 16:17:39 | 2024-07-09 16:21:15 | unesco | 0 | ETL 74 | 2024-07-09 16:21:15 | ETL 74 | 2024-07-09 16:21:15 | ETL 74 | 0 | 0 | 493b1248cfb9ff30df4dafaaf93fc5db | education_sdgs | 2024-06-25 | 365 | |
6610 | Homelessness - Better Data Project | 2024-07-08 16:14:04 | 2024-07-22 14:46:04 | igh | 0 | ETL 74 | 2024-07-22 14:46:04 | ETL 74 | 2024-07-22 14:46:04 | ETL 74 | 0 | 0 | 98689908cc375b9dc67e2b0c1336e0bf | better_data_homelessness | 2024-07-05 | 365 | |
6609 | Annual road fatalities, injured, injury crashes | 2024-07-05 10:47:01 | 2024-07-25 23:10:19 | oecd | 0 | ETL 74 | 2024-07-25 23:10:20 | ETL 74 | 2024-07-25 23:10:20 | ETL 74 | 0 | 0 | d07bbfeb7cbb5466578a84c972c3e512 | road_accidents | 2024-07-01 | 365 | |
6608 | AI Index Report | 2024-07-03 10:48:31 | 2024-07-10 09:35:48 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:48 | ETL 74 | 2024-07-10 09:35:48 | ETL 74 | 0 | 0 | a233a943d228b8b6e4100619b2d53c66 | ai_robots | 2024-06-28 | 365 | |
6607 | Country level monthly temperature anomalies | 2024-07-03 09:35:54 | 2024-07-17 12:26:42 | climate | 0 | ETL 74 | 2024-07-17 12:26:43 | ETL 74 | 2024-07-17 12:26:43 | ETL 74 | 0 | 0 | 8d8acbd11cd09db63c41dc1d442905d6 | surface_country_level_monthly_anomaly | 2023-12-20 | ||
6606 | Global monthly temperature anomalies for all countries | 2024-07-03 09:35:54 | 2024-07-17 12:26:40 | climate | 0 | ETL 74 | 2024-07-17 12:26:40 | ETL 74 | 2024-07-17 12:26:40 | ETL 74 | 0 | 0 | 4532c863637b17cb0d3c560cca471abb | surface_global_monthly_anomaly_all_countries | 2023-12-20 | ||
6605 | AI Index Report | 2024-07-02 19:13:37 | 2024-07-22 08:46:10 | artificial_intelligence | 0 | ETL 74 | 2024-07-22 08:46:11 | ETL 74 | 2024-07-22 08:46:11 | ETL 74 | 0 | 0 | 78ce9fe5dda33ad31e15799586b18d80 | ai_private_investment | 2024-06-28 | 365 | |
6604 | AI Index Report | 2024-07-02 19:13:37 | 2024-07-10 11:55:24 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 11:55:25 | ETL 74 | 2024-07-10 11:55:25 | ETL 74 | 0 | 0 | 2e65b3f23908e0b1231985c5f9f21710 | ai_corporate_investment | 2024-06-28 | 365 | |
6603 | AI Index Report | 2024-07-02 19:13:36 | 2024-07-10 09:35:46 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:46 | ETL 74 | 2024-07-10 09:35:46 | ETL 74 | 0 | 0 | 9cb8f9d01372d83c921b2ed56b4c1fc4 | ai_conferences | 2024-06-28 | 365 | |
6602 | AI Index Report | 2024-07-02 19:13:36 | 2024-07-10 09:35:46 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:46 | ETL 74 | 2024-07-10 09:35:46 | ETL 74 | 0 | 0 | 95c6c3d444d50cd19494ed55195ea41f | ai_jobs | 2024-06-28 | 365 | |
6601 | AI Index Report | 2024-07-02 19:13:36 | 2024-07-22 08:46:10 | artificial_intelligence | 0 | ETL 74 | 2024-07-22 08:46:11 | ETL 74 | 2024-07-22 08:46:11 | ETL 74 | 0 | 0 | 725a6fd128dbea3ff9d9d21b2a4e2f61 | ai_investment_generative_companies | 2024-06-28 | 365 | |
6600 | AI Index Report | 2024-07-02 19:13:36 | 2024-07-10 09:35:46 | artificial_intelligence | 0 | ETL 74 | 2024-07-10 09:35:47 | ETL 74 | 2024-07-10 09:35:47 | ETL 74 | 0 | 0 | 2fb14ff4a85da4078222833bf972a127 | ai_incidents | 2024-06-28 | 365 | |
6599 | Global Burden of Disease - Health-adjusted life expectancy | 2024-07-02 16:03:20 | 2024-07-02 16:03:21 | ihme_gbd | 1 | ETL 74 | 2024-07-02 16:03:22 | ETL 74 | 2024-07-02 16:03:22 | ETL 74 | 1 | 0 | f9a57693d27e705d2f6c42dcf9d59326 | gbd_healthy_life_expectancy | 2024-07-02 | ||
6598 | Extreme poverty projections up to 2030 | 2024-07-02 16:03:20 | 2024-07-08 18:01:50 | wb | 0 | ETL 74 | 2024-07-08 18:01:50 | ETL 74 | 2024-07-08 18:01:50 | ETL 74 | 0 | 0 | d9d4b31fc5256e47cb212f273daf111f | poverty_projections | 2024-06-26 | 365 | |
6597 | Global Burden of Disease - Mental Health Burden | 2024-07-01 16:11:41 | 2024-07-01 16:11:55 | ihme_gbd | 1 | ETL 74 | 2024-07-01 16:11:55 | ETL 74 | 2024-07-01 16:11:55 | ETL 74 | 1 | 0 | 63fa26117ae65b1decad4db6c498a621 | gbd_mental_health_burden_dalys | 2024-05-20 | 1460 | |
6596 | Breakdown of material footprint of electricity (Wang et al. 2024) | 2024-07-01 13:39:32 | 2024-07-24 11:36:37 | fasttrack | 0 | ETL 74 | 2024-07-24 11:36:38 | ETL 74 | 2024-07-24 11:36:38 | ETL 74 | 0 | 0 | 85df786b96aad8ba2f199e332d090335 | breakdown_material_footprint_wang | latest | ||
6595 | Material footprint of electricity (Wang et al. 2024) | 2024-07-01 13:30:46 | 2024-07-24 11:36:40 | fasttrack | 0 | ETL 74 | 2024-07-24 11:36:41 | ETL 74 | 2024-07-24 11:36:41 | ETL 74 | 0 | 0 | 5c77e598f3cc907ad06173d0ca2c1348 | electricity_material_footprint_wang | latest | ||
6594 | Rock-to-metal mining ratio (Nassar et al. 2022) | 2024-07-01 11:50:31 | 2024-07-08 18:06:14 | fasttrack | 0 | ETL 74 | 2024-07-08 18:06:14 | ETL 74 | 2024-07-08 18:06:14 | ETL 74 | 0 | 0 | 83376a09eb035b5c73fff4ea517eef8c | rock_metal_ratio_nassar | latest | ||
6593 | Global Burden of Disease - Child Mortality | 2024-06-28 16:35:07 | 2024-07-25 23:25:34 | ihme_gbd | 1 | ETL 74 | 2024-07-25 23:25:34 | ETL 74 | 2024-07-25 23:25:34 | ETL 74 | 1 | 0 | f866f94158f256cb16ebb395c97ca3af | gbd_child_mortality | 2024-05-20 | 1460 | |
6592 | DRAFT Voter turnout by age - Sheet1 | 2024-06-25 15:45:14 | 2024-06-26 09:44:11 | fasttrack | 1 | ETL 74 | 2024-06-26 09:44:12 | ETL 74 | 2024-06-26 09:44:12 | ETL 74 | 0 | 0 | 91600f0f07d61c6c096196b8d8cdb8db | voter_turnout_by_age__sheet1 | latest | ||
6591 | Global Carbon Budget | 2024-06-25 14:50:41 | 2024-07-25 23:15:33 | gcp | 0 | ETL 74 | 2024-07-25 23:15:34 | ETL 74 | 2024-07-25 23:15:34 | ETL 74 | 0 | 0 | 458acf1025183ccba501835e05639745 | global_carbon_budget | 2024-06-20 | 365 | |
6590 | Energy mix | 2024-06-25 14:50:29 | 2024-07-25 23:09:01 | energy | 0 | ETL 74 | 2024-07-25 23:09:02 | ETL 74 | 2024-07-25 23:09:02 | ETL 74 | 0 | 0 | ad67a06d0cc70c0953315de4ae2ecf7d | energy_mix | 2024-06-20 | 365 | |
6589 | Electricity mix | 2024-06-25 14:50:26 | 2024-07-25 23:15:33 | energy | 0 | ETL 74 | 2024-07-25 23:15:33 | ETL 74 | 2024-07-25 23:15:33 | ETL 74 | 0 | 0 | e2bcffe7f7bfd26ad748f193bc2d7df8 | electricity_mix | 2024-06-20 | 365 | |
6588 | UK historical electricity | 2024-06-25 14:50:26 | 2024-07-25 23:20:11 | energy | 0 | ETL 74 | 2024-07-25 23:20:11 | ETL 74 | 2024-07-25 23:20:11 | ETL 74 | 0 | 0 | 3b8f8db6da2250085096e61ada26d821 | uk_historical_electricity | 2024-06-20 | 365 | |
6587 | Global Primary Energy | 2024-06-25 14:50:26 | 2024-07-25 23:07:09 | energy | 0 | ETL 74 | 2024-07-25 23:07:09 | ETL 74 | 2024-07-25 23:07:09 | ETL 74 | 0 | 0 | 763c2509de75fd37b6ee215a60a5e80f | global_primary_energy | 2024-06-20 | 365 | |
6586 | Statistical Review of World Energy | 2024-06-25 14:50:25 | 2024-07-25 22:54:44 | energy_institute | 0 | ETL 74 | 2024-07-25 22:54:44 | ETL 74 | 2024-07-25 22:54:44 | ETL 74 | 0 | 0 | ec180a36fc9a5a668e77b2a959ff0e2f | statistical_review_of_world_energy | 2024-06-20 | 365 | |
6585 | Fossil fuel production | 2024-06-25 14:50:24 | 2024-07-25 23:09:03 | energy | 0 | ETL 74 | 2024-07-25 23:09:03 | ETL 74 | 2024-07-25 23:09:03 | ETL 74 | 0 | 0 | a62ca1ef6e233c704c7e78c8e55a8627 | fossil_fuel_production | 2024-06-20 | 365 | |
6584 | Fossil fuel reserves/production ratio | 2024-06-25 14:50:23 | 2024-07-25 23:06:58 | energy | 0 | ETL 74 | 2024-07-25 23:06:58 | ETL 74 | 2024-07-25 23:06:58 | ETL 74 | 0 | 0 | 0f3cead34b959e78824b0ea7c04d9e70 | fossil_fuel_reserves_production_ratio | 2024-06-20 | 365 | |
6583 | Primary energy consumption | 2024-06-25 14:50:22 | 2024-07-25 23:09:03 | energy | 0 | ETL 74 | 2024-07-25 23:09:04 | ETL 74 | 2024-07-25 23:09:04 | ETL 74 | 0 | 0 | 743b81cd328a7faa659f5c3be7f1f381 | primary_energy_consumption | 2024-06-20 | 365 | |
6582 | Luxembourg Income Study (LIS) | 2024-06-25 14:16:15 | 2024-07-25 22:56:13 | lis | 0 | ETL 74 | 2024-07-25 22:56:13 | ETL 74 | 2024-07-25 22:56:13 | ETL 74 | 0 | 0 | d8a3298a485b9af1908396691a7e4cdf | luxembourg_income_study | 2024-06-13 | 365 | |
6581 | Guinea worm reported cases and certification (WHO) | 2024-06-25 09:06:35 | 2024-07-08 16:38:18 | who | 0 | ETL 74 | 2024-07-08 16:38:19 | ETL 74 | 2024-07-08 16:38:19 | ETL 74 | 0 | 0 | 98d7e1e402c5b584cc3510c26ec5edaf | guinea_worm | 2024-06-17 | 365 | |
6580 | Guinea worm cases (WHO, 2024) | 2024-06-25 09:06:28 | 2024-07-08 16:38:17 | fasttrack | 0 | ETL 74 | 2024-07-08 16:38:18 | ETL 74 | 2024-07-08 16:38:18 | ETL 74 | 0 | 0 | 2e67451df240fb18e36f8b171d1fbe3e | guinea_worm | 2024-06-17 | ||
6579 | UNESCO Institute for Statistics (UIS) - Education | 2024-06-25 08:11:24 | 2024-07-09 16:16:53 | unesco | 0 | ETL 74 | 2024-07-09 16:16:53 | ETL 74 | 2024-07-09 16:16:53 | ETL 74 | 0 | 0 | 2309423a8373f07c8484fe6c01fa043f | education_opri | 2024-06-16 | 365 | |
6578 | Standard country or area codes for statistical use (M49) | 2024-06-24 10:15:49 | 2024-07-08 17:24:45 | un | 0 | ETL 74 | 2024-07-08 17:24:45 | ETL 74 | 2024-07-08 17:24:45 | ETL 74 | 0 | 0 | e66e081f0cb6d21baac348faeb8e0cdb | sdg_regions | 2024-06-24 | 365 | |
6577 | Global Burden of Disease - Risk Factors | 2024-06-21 17:24:29 | 2024-07-25 23:34:38 | ihme_gbd | 1 | ETL 74 | 2024-07-25 23:34:38 | ETL 74 | 2024-07-25 23:34:38 | ETL 74 | 1 | 0 | 565125284f09ae76fec8422091fb5148 | gbd_risk | 2024-05-20 | 1460 | |
6576 | Emissions and energy demand from cooling and heating (IEA, 2023) | 2024-06-21 13:55:37 | 2024-07-08 17:24:04 | fasttrack | 0 | ETL 74 | 2024-07-08 17:24:05 | ETL 74 | 2024-07-08 17:24:05 | ETL 74 | 0 | 0 | fc79164768b0c77df72b958d4ad586d4 | emissions_energy_heating_cooling_iea | latest | ||
6575 | World Happiness Report | 2024-06-20 15:49:57 | 2024-07-25 23:07:59 | happiness | 0 | ETL 74 | 2024-07-25 23:08:00 | ETL 74 | 2024-07-25 23:08:00 | ETL 74 | 0 | 0 | 552fc45c05bc72e08f9556c289d5530b | happiness | 2024-06-09 | 365 | |
6574 | Large-scale AI systems by domain type | 2024-06-19 14:36:00 | 2024-07-08 16:32:09 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 16:32:09 | ETL 74 | 2024-07-08 16:32:09 | ETL 74 | 0 | 0 | 2225f650ebbf53a12faf92cdadf4da8a | epoch_compute_intensive_domain | 2024-06-19 | 180 | |
6573 | Large-scale AI systems by country | 2024-06-19 14:36:00 | 2024-07-08 16:47:58 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 16:47:58 | ETL 74 | 2024-07-08 16:47:58 | ETL 74 | 0 | 0 | 012349fa04ec5c76355a661d9ea0423c | epoch_compute_intensive_countries | 2024-06-19 | 180 | |
6572 | Large-scale AI models by organization | 2024-06-19 14:36:00 | 2024-06-20 15:08:13 | artificial_intelligence | 1 | ETL 74 | 2024-06-19 14:36:01 | ETL 74 | 2024-06-19 14:36:01 | ETL 74 | 0 | 1 | 04d909b2020d5ec2a346f3907e91b0d7 | epoch_compute_intensive_organizations | 2024-06-19 | 180 | |
6571 | Tracking Compute-Intensive AI Models | 2024-06-19 14:35:59 | 2024-07-08 16:38:43 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 16:38:43 | ETL 74 | 2024-07-08 16:38:43 | ETL 74 | 0 | 0 | 2ecf9855a8eb26669d58a3964166f7fe | epoch_compute_intensive | 2024-06-19 | 180 | |
6570 | Public Finances in Modern History | 2024-06-17 16:35:31 | 2024-07-08 16:38:04 | imf | 0 | ETL 74 | 2024-07-08 16:38:04 | ETL 74 | 2024-07-08 16:38:04 | ETL 74 | 0 | 0 | 70eb24f3a09b6a5c1df80da9f382a2ac | public_finances_modern_history | 2024-06-12 | 365 | |
6569 | Same-sex marriage around the world - Pew Research Center | 2024-06-17 15:46:03 | 2024-07-25 23:08:49 | pew | 0 | ETL 74 | 2024-07-25 23:08:49 | ETL 74 | 2024-07-25 23:08:49 | ETL 74 | 0 | 0 | a45ae83bd3d79c86057d6d8b0d2a32e7 | same_sex_marriage | 2024-06-03 | 365 | |
6568 | Draft: Joe – Difference in top 1 percent share, 1980-2018, PIP vs WID data (take2) | 2024-06-15 11:19:33 | 2024-06-15 11:19:34 | fasttrack | 1 | ETL 74 | 2024-06-15 11:19:34 | ETL 74 | 2024-06-15 11:19:34 | ETL 74 | 0 | 0 | d48e5569034a32b28d0a3856338f3016 | draft_joe_top1share_diff_1980_2018 | latest | ||
6567 | Draft: Joe – Difference in Gini, 1980-2018, PIP vs WID data (take2) | 2024-06-15 11:03:45 | 2024-06-17 12:19:29 | fasttrack | 1 | ETL 74 | 2024-06-17 12:19:29 | ETL 74 | 2024-06-17 12:19:29 | ETL 74 | 0 | 0 | 8db434faed17c7339573bd66261f0178 | draft_joe_gini_diff_1980_2018_take2 | latest | ||
6566 | Draft: Joe – Difference in Gini, 1980-2018, PIP vs WID data | 2024-06-15 10:58:15 | 2024-06-17 12:19:28 | fasttrack | 1 | ETL 74 | 2024-06-17 12:19:29 | ETL 74 | 2024-06-17 12:19:29 | ETL 74 | 0 | 0 | 346f55d075c7c6168f301b0f960f6d41 | draft_joe_gini_diff_1980_2018 | latest | ||
6565 | Homosexuality criminalization data from Mignot | 2024-06-14 15:10:41 | 2024-07-25 23:08:49 | lgbt_rights | 0 | ETL 74 | 2024-07-25 23:08:50 | ETL 74 | 2024-07-25 23:08:50 | ETL 74 | 0 | 0 | 1ed6592be54be88717ce8a78318b55bb | criminalization_mignot | 2024-06-11 | 365 | |
6564 | Draft: Joe – Difference in Top 1 percent share, 1993-2018, PIP vs WID data | 2024-06-14 07:52:32 | 2024-06-16 06:41:52 | fasttrack | 1 | ETL 74 | 2024-06-16 06:41:52 | ETL 74 | 2024-06-16 06:41:52 | ETL 74 | 0 | 0 | 19c698c2c28cb2d48eeeccf24fbd9255 | draft_joe_top1_diff_1993_2018 | latest | ||
6563 | ISAPS Global Survey | 2024-06-12 20:42:54 | 2024-07-08 16:30:42 | health | 0 | ETL 74 | 2024-07-08 16:30:42 | ETL 74 | 2024-07-08 16:30:42 | ETL 74 | 0 | 0 | 60e52f1bdd5c205d9cc7e9c9b71e0e86 | isaps_plastic_surgery | 2024-06-11 | 365 | |
6562 | Global Burden of Disease, Cause Hierarchy | 2024-06-12 19:07:37 | 2024-07-25 23:35:36 | ihme_gbd | 1 | ETL 74 | 2024-07-25 23:35:36 | ETL 74 | 2024-07-25 23:35:36 | ETL 74 | 1 | 0 | 34c13d401ba0f084dc49b851d3474ca0 | leading_causes_deaths | 2024-06-10 | 365 | |
6561 | Notable AI systems by domain type | 2024-06-11 19:07:25 | 2024-07-08 16:31:12 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 16:31:12 | ETL 74 | 2024-07-08 16:31:12 | ETL 74 | 0 | 0 | 905d5f4a1c8d05ebe839b68d4104535e | epoch_aggregates_domain | 2024-06-03 | 31 | |
6560 | Notable AI systems by organization | 2024-06-11 19:07:25 | 2024-06-20 15:12:41 | artificial_intelligence | 1 | ETL 74 | 2024-06-13 09:20:51 | ETL 74 | 2024-06-13 09:20:51 | ETL 74 | 0 | 1 | 6361d13a3bcae93281526cf9947bce45 | epoch_aggregates_organizations | 2024-06-03 | 31 | |
6559 | Notable AI systems by country | 2024-06-11 19:07:25 | 2024-06-20 15:12:27 | artificial_intelligence | 1 | ETL 74 | 2024-06-13 09:20:52 | ETL 74 | 2024-06-13 09:20:52 | ETL 74 | 0 | 1 | b2771dc84b08be1bf8585b57909ae472 | epoch_aggregates_countries | 2024-06-03 | 31 | |
6558 | Notable AI systems by researcher affiliation | 2024-06-11 19:07:24 | 2024-07-08 16:31:08 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 16:31:08 | ETL 74 | 2024-07-08 16:31:08 | ETL 74 | 0 | 0 | 6410245d0da2c017a1b0f04d4087eaf7 | epoch_aggregates_affiliation | 2024-06-03 | 31 | |
6557 | Parameter, Compute and Data Trends in Machine Learning | 2024-06-11 19:07:24 | 2024-07-08 17:29:30 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 17:29:30 | ETL 74 | 2024-07-08 17:29:30 | ETL 74 | 0 | 0 | e842f7545f3850c8413479bacccde786 | epoch | 2024-06-03 | 31 | |
6556 | Equaldex | 2024-06-11 18:31:55 | 2024-07-25 23:14:45 | lgbt_rights | 0 | ETL 74 | 2024-07-25 23:14:46 | ETL 74 | 2024-07-25 23:14:46 | ETL 74 | 0 | 0 | ef5aa4c559298d02c544501cdc822327 | equaldex | 2024-06-03 | 365 | |
6555 | International Smoking Statistics | 2024-06-11 18:05:08 | 2024-07-25 23:11:33 | smoking | 0 | ETL 74 | 2024-07-25 23:11:33 | ETL 74 | 2024-07-25 23:11:33 | ETL 74 | 0 | 0 | 97c79763b2c21c51f55704d8f4f223fd | cigarette_sales | 2024-05-30 | 0 | |
6554 | World Bank Gender Statistics | 2024-06-11 17:33:11 | 2024-07-08 17:30:08 | wb | 0 | ETL 74 | 2024-07-08 17:30:09 | ETL 74 | 2024-07-08 17:30:09 | ETL 74 | 0 | 0 | a582d69123dfd06ef455dab08058de14 | gender_statistics | 2024-06-10 | 365 | |
6553 | The rising costs of training frontier AI models | 2024-06-10 11:03:07 | 2024-07-08 15:47:05 | artificial_intelligence | 0 | ETL 74 | 2024-07-08 15:47:05 | ETL 74 | 2024-07-08 15:47:05 | ETL 74 | 0 | 0 | 5dfa81a49594e45956e0756ed1a957d4 | epoch_compute_cost | 2024-06-06 |
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CREATE TABLE "datasets" ( "id" INTEGER PRIMARY KEY AUTOINCREMENT, "name" VARCHAR(512) NOT NULL , "description" TEXT NOT NULL , "createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP , "updatedAt" DATETIME NULL , "namespace" VARCHAR(255) NOT NULL , "isPrivate" TINYINT NOT NULL DEFAULT '0' , "createdByUserId" INTEGER NOT NULL , "metadataEditedAt" DATETIME NOT NULL , "metadataEditedByUserId" INTEGER NOT NULL , "dataEditedAt" DATETIME NOT NULL , "dataEditedByUserId" INTEGER NOT NULL , "nonRedistributable" TINYINT NOT NULL DEFAULT '0' , "isArchived" TINYINT NOT NULL DEFAULT '0' , "sourceChecksum" VARCHAR(64) NULL , "shortName" VARCHAR(255) NULL , "version" VARCHAR(255) NULL , "updatePeriodDays" INTEGER NULL, FOREIGN KEY("createdByUserId") REFERENCES "users" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT, FOREIGN KEY("dataEditedByUserId") REFERENCES "users" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT, FOREIGN KEY("metadataEditedByUserId") REFERENCES "users" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT ); CREATE INDEX "datasets_createdByUserId" ON "datasets" ("createdByUserId"); CREATE INDEX "datasets_dataEditedByUserId" ON "datasets" ("dataEditedByUserId"); CREATE INDEX "datasets_metadataEditedByUserId" ON "datasets" ("metadataEditedByUserId"); CREATE UNIQUE INDEX "unique_short_name_version_namespace" ON "datasets" ("shortName", "version", "namespace");