owid
Data license: CC-BY
id | name | description | createdAt | updatedAt | namespace | isPrivate | createdByUserId | metadataEditedAt | metadataEditedByUserId | dataEditedAt | dataEditedByUserId | nonRedistributable | isArchived | sourceChecksum | shortName | version | updatePeriodDays |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6652 | COVID-19, decoupling of indicators | 2024-07-31 15:42:15 | 2024-07-31 15:42:16 | covid | 0 | 74 | 2024-07-31 15:42:17 | 74 | 2024-07-31 15:42:17 | 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 | 74 | 2024-07-31 12:15:50 | 74 | 2024-07-31 12:15:50 | 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 | 74 | 2024-07-31 09:04:32 | 74 | 2024-07-31 09:04:32 | 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 | 74 | 2024-07-30 17:20:52 | 74 | 2024-07-30 17:20:52 | 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 | 74 | 2024-07-31 15:42:27 | 74 | 2024-07-31 15:42:27 | 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 | 74 | 2024-07-30 12:02:37 | 74 | 2024-07-30 12:02:37 | 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 | 74 | 2024-07-30 12:02:11 | 74 | 2024-07-30 12:02:11 | 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 | 74 | 2024-07-30 12:02:11 | 74 | 2024-07-30 12:02:11 | 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 | 74 | 2024-07-29 17:27:35 | 74 | 2024-07-29 17:27:35 | 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 | 74 | 2024-07-31 12:58:57 | 74 | 2024-07-31 12:58:57 | 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 | 74 | 2024-07-29 15:05:40 | 74 | 2024-07-29 15:05:40 | 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 | 74 | 2024-07-29 12:47:24 | 74 | 2024-07-29 12:47:24 | 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 | 74 | 2024-07-29 11:40:04 | 74 | 2024-07-29 11:40:04 | 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 | 74 | 2024-07-29 10:21:55 | 74 | 2024-07-29 10:21:55 | 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 | 74 | 2024-07-28 15:37:23 | 74 | 2024-07-28 15:37:23 | 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 | 74 | 2024-07-31 15:43:12 | 74 | 2024-07-31 15:43:12 | 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 | 74 | 2024-07-26 14:48:57 | 74 | 2024-07-26 14:48:57 | 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 | 74 | 2024-07-26 14:39:40 | 74 | 2024-07-26 14:39:40 | 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 | 74 | 2024-07-28 12:50:16 | 74 | 2024-07-28 12:50:16 | 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 | 74 | 2024-07-30 06:18:31 | 74 | 2024-07-30 06:18:31 | 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 | 74 | 2024-07-25 12:44:35 | 74 | 2024-07-25 12:44:35 | 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 | 74 | 2024-07-25 12:17:10 | 74 | 2024-07-25 12:17:10 | 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 | 74 | 2024-07-25 12:17:10 | 74 | 2024-07-25 12:17:10 | 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 | 74 | 2024-07-25 12:17:08 | 74 | 2024-07-25 12:17:08 | 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 | 74 | 2024-07-31 07:50:10 | 74 | 2024-07-31 07:50:10 | 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 | 74 | 2024-07-31 07:49:59 | 74 | 2024-07-31 07:49:59 | 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 | 74 | 2024-07-30 06:18:12 | 74 | 2024-07-30 06:18:12 | 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 | 74 | 2024-07-19 10:07:36 | 74 | 2024-07-19 10:07:36 | 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 | 74 | 2024-07-17 16:46:31 | 74 | 2024-07-17 16:46:31 | 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 | 74 | 2024-07-17 16:46:30 | 74 | 2024-07-17 16:46:30 | 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 | 74 | 2024-07-17 21:21:38 | 74 | 2024-07-17 21:21:38 | 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 | 74 | 2024-07-30 06:18:04 | 74 | 2024-07-30 06:18:04 | 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 | 74 | 2024-07-16 08:49:22 | 74 | 2024-07-16 08:49:22 | 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 | 74 | 2024-07-15 12:51:34 | 74 | 2024-07-15 12:51:34 | 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 | 74 | 2024-07-15 13:00:14 | 74 | 2024-07-15 13:00:14 | 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 | 74 | 2024-07-15 12:56:26 | 74 | 2024-07-15 12:56:26 | 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 | 74 | 2024-07-11 17:28:27 | 74 | 2024-07-11 17:28:27 | 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 | 74 | 2024-07-11 17:29:11 | 74 | 2024-07-11 17:29:11 | 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 | 74 | 2024-07-10 09:35:49 | 74 | 2024-07-10 09:35:49 | 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 | 74 | 2024-07-25 22:50:46 | 74 | 2024-07-25 22:50:46 | 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 | 74 | 2024-07-10 09:35:48 | 74 | 2024-07-10 09:35:48 | 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 | 74 | 2024-07-09 16:21:15 | 74 | 2024-07-09 16:21:15 | 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 | 74 | 2024-07-22 14:46:04 | 74 | 2024-07-22 14:46:04 | 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 | 74 | 2024-07-25 23:10:20 | 74 | 2024-07-25 23:10:20 | 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 | 74 | 2024-07-10 09:35:48 | 74 | 2024-07-10 09:35:48 | 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 | 74 | 2024-07-17 12:26:43 | 74 | 2024-07-17 12:26:43 | 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 | 74 | 2024-07-17 12:26:40 | 74 | 2024-07-17 12:26:40 | 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 | 74 | 2024-07-22 08:46:11 | 74 | 2024-07-22 08:46:11 | 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 | 74 | 2024-07-10 11:55:25 | 74 | 2024-07-10 11:55:25 | 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 | 74 | 2024-07-10 09:35:46 | 74 | 2024-07-10 09:35:46 | 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 | 74 | 2024-07-10 09:35:46 | 74 | 2024-07-10 09:35:46 | 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 | 74 | 2024-07-22 08:46:11 | 74 | 2024-07-22 08:46:11 | 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 | 74 | 2024-07-10 09:35:47 | 74 | 2024-07-10 09:35:47 | 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 | 74 | 2024-07-02 16:03:22 | 74 | 2024-07-02 16:03:22 | 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 | 74 | 2024-07-08 18:01:50 | 74 | 2024-07-08 18:01:50 | 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 | 74 | 2024-07-01 16:11:55 | 74 | 2024-07-01 16:11:55 | 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 | 74 | 2024-07-24 11:36:38 | 74 | 2024-07-24 11:36:38 | 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 | 74 | 2024-07-24 11:36:41 | 74 | 2024-07-24 11:36:41 | 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 | 74 | 2024-07-08 18:06:14 | 74 | 2024-07-08 18:06:14 | 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 | 74 | 2024-07-25 23:25:34 | 74 | 2024-07-25 23:25:34 | 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 | 74 | 2024-06-26 09:44:12 | 74 | 2024-06-26 09:44:12 | 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 | 74 | 2024-07-25 23:15:34 | 74 | 2024-07-25 23:15:34 | 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 | 74 | 2024-07-25 23:09:02 | 74 | 2024-07-25 23:09:02 | 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 | 74 | 2024-07-25 23:15:33 | 74 | 2024-07-25 23:15:33 | 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 | 74 | 2024-07-25 23:20:11 | 74 | 2024-07-25 23:20:11 | 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 | 74 | 2024-07-25 23:07:09 | 74 | 2024-07-25 23:07:09 | 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 | 74 | 2024-07-25 22:54:44 | 74 | 2024-07-25 22:54:44 | 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 | 74 | 2024-07-25 23:09:03 | 74 | 2024-07-25 23:09:03 | 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 | 74 | 2024-07-25 23:06:58 | 74 | 2024-07-25 23:06:58 | 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 | 74 | 2024-07-25 23:09:04 | 74 | 2024-07-25 23:09:04 | 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 | 74 | 2024-07-25 22:56:13 | 74 | 2024-07-25 22:56:13 | 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 | 74 | 2024-07-08 16:38:19 | 74 | 2024-07-08 16:38:19 | 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 | 74 | 2024-07-08 16:38:18 | 74 | 2024-07-08 16:38:18 | 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 | 74 | 2024-07-09 16:16:53 | 74 | 2024-07-09 16:16:53 | 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 | 74 | 2024-07-08 17:24:45 | 74 | 2024-07-08 17:24:45 | 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 | 74 | 2024-07-25 23:34:38 | 74 | 2024-07-25 23:34:38 | 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 | 74 | 2024-07-08 17:24:05 | 74 | 2024-07-08 17:24:05 | 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 | 74 | 2024-07-25 23:08:00 | 74 | 2024-07-25 23:08:00 | 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 | 74 | 2024-07-08 16:32:09 | 74 | 2024-07-08 16:32:09 | 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 | 74 | 2024-07-08 16:47:58 | 74 | 2024-07-08 16:47:58 | 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 | 74 | 2024-06-19 14:36:01 | 74 | 2024-06-19 14:36:01 | 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 | 74 | 2024-07-08 16:38:43 | 74 | 2024-07-08 16:38:43 | 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 | 74 | 2024-07-08 16:38:04 | 74 | 2024-07-08 16:38:04 | 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 | 74 | 2024-07-25 23:08:49 | 74 | 2024-07-25 23:08:49 | 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 | 74 | 2024-06-15 11:19:34 | 74 | 2024-06-15 11:19:34 | 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 | 74 | 2024-06-17 12:19:29 | 74 | 2024-06-17 12:19:29 | 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 | 74 | 2024-06-17 12:19:29 | 74 | 2024-06-17 12:19:29 | 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 | 74 | 2024-07-25 23:08:50 | 74 | 2024-07-25 23:08:50 | 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 | 74 | 2024-06-16 06:41:52 | 74 | 2024-06-16 06:41:52 | 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 | 74 | 2024-07-08 16:30:42 | 74 | 2024-07-08 16:30:42 | 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 | 74 | 2024-07-25 23:35:36 | 74 | 2024-07-25 23:35:36 | 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 | 74 | 2024-07-08 16:31:12 | 74 | 2024-07-08 16:31:12 | 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 | 74 | 2024-06-13 09:20:51 | 74 | 2024-06-13 09:20:51 | 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 | 74 | 2024-06-13 09:20:52 | 74 | 2024-06-13 09:20:52 | 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 | 74 | 2024-07-08 16:31:08 | 74 | 2024-07-08 16:31:08 | 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 | 74 | 2024-07-08 17:29:30 | 74 | 2024-07-08 17:29:30 | 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 | 74 | 2024-07-25 23:14:46 | 74 | 2024-07-25 23:14:46 | 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 | 74 | 2024-07-25 23:11:33 | 74 | 2024-07-25 23:11:33 | 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 | 74 | 2024-07-08 17:30:09 | 74 | 2024-07-08 17:30:09 | 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 | 74 | 2024-07-08 15:47:05 | 74 | 2024-07-08 15:47:05 | 74 | 0 | 0 | 5dfa81a49594e45956e0756ed1a957d4 | epoch_compute_cost | 2024-06-06 | ||
6552 | Draft: Joe – Difference in Gini, 1993-2018, PIP vs WID data | 2024-06-09 16:04:27 | 2024-06-17 11:37:58 | fasttrack | 1 | 74 | 2024-06-17 11:37:58 | 74 | 2024-06-17 11:37:58 | 74 | 0 | 0 | 4a8eec0c9396a6b22cdd4119d9c5a5a2 | draft_joe_gini_diff_1993_2018 | latest |