cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xchm2j
title: Occurrence Download

description: A dataset containing 2182 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((36.2109375 62.91523303947614, 29.53125 65.6582745198266, 28.4765625 69.65708627301174, 26.015625 73.40835658394874, 43.59375 83.35137500176401, 135 83.18655855039928, 192.65625 71.94360551376778, 189.140625 58.04067576238911, 162.421875 49.79261028398753, 150.46875 48.41169887928219, 149.765625 55.737005273532624, 143.08593749999997 59.17592824927136, 135.35156249999997 60.75915950226991, 129.0234375 61.270232790000634, 120.58593749999999 61.77312286453146, 111.4453125 62.431074232920906, 102.65625 62.2679226294176, 88.59374999999999 62.235183800894056, 65.390625 61.23641478311559, 44.29687499999999 61.10078883158897, 36.2109375 62.91523303947614))",
 "TaxonKey is Araneae"
 ]
}

 The dataset includes 2182 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014622-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hhhike
title: Occurrence Download

description: A dataset containing 39446 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Physeter macrocephalus Linnaeus, 1758"
 ]
}

 The dataset includes 39446 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014287-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kn0h68
title: Occurrence Download

description: A dataset containing 182790 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Base de datos de plantas vasculares del País Vasco: ARAN-EH"
 ]
}

 The dataset includes 182790 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013993-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nl1jsf
title: Occurrence Download

description: A dataset containing 222 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Symplocos coccinea Bonpl."
 ]
}

 The dataset includes 222 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013828-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a8twkf
title: Occurrence Download

description: A dataset containing 453 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Haemagogus leucocelaenus (Dyar & Shannon, 1924)"
 ]
}

 The dataset includes 453 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013682-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26213552
title: Functional annotation from GO and KEGG databases

description: Functional annotation of genes from A. porri Apn-Nashik based on GO and KEGG analysis
DOI: 10.6084/m9.figshare.26213552.v1
title: Functional annotation from GO and KEGG databases

description: Functional annotation of genes from A. porri Apn-Nashik based on GO and KEGG analysis
DOI: 10.6084/m9.figshare.24573874
title: Common bean pan-genome

description: The common bean pan-genome assembly and its annotation plus the four genome assemblies used for its construction (and their annotation).
DOI: 10.6084/m9.figshare.24573874.v2
title: Common bean pan-genome

description: The common bean pan-genome assembly and its annotation plus the four genome assemblies used for its construction (and their annotation).
DOI: 10.15468/dl.s6j7nn
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ourapteryx kantalaria (Felder & Rogenhofer, 1875)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018043-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/8914055
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.25337/t7/ptycho.v2.0/al.840539006
title: Counts of COVID-19 reported in ALBANIA: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.5518/998
title: Data associated with 'Effects of oral lubrication on satiety, satiation and salivary biomarkers in model foods: A pilot study'

description: Raw data for all figures in the associated paper 'Effects of oral lubrication on satiety, satiation and salivary biomarkers in model foods: A pilot study'
DOI: 10.25337/t7/ptycho.v2.0/zw.840539006
title: Counts of COVID-19 reported in ZIMBABWE: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/za.840539006
title: Counts of COVID-19 reported in SOUTH AFRICA: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/zm.840539006
title: Counts of COVID-19 reported in ZAMBIA: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/yt.840539006
title: Counts of COVID-19 reported in MAYOTTE: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/ye.840539006
title: Counts of COVID-19 reported in YEMEN: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/ws.840539006
title: Counts of COVID-19 reported in SAMOA: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/xk.840539006
title: Counts of COVID-19 reported in KOSOVO: 2020-2021
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
DOI: 10.25337/t7/ptycho.v2.0/ws.38362002
title: Counts of Dengue reported in SAMOA: 1979-2008
title: Project Tycho dataset

description: Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format.Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:- Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported.- Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".