cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e244384
title: Medicare Fee for Service (FFS) claims (100%) – Vision and Eye Health Surveillance

description: 2014-2022. This dataset is a de-identified summary table of vision and eye health data indicators from Medicare claims, stratified by all available combinations of age group, race/ethnicity, sex, and state. Medicare claims for VEHSS includes beneficiaries who were fully enrolled in Medicare Part B Fee-for-Service (FFS) for the duration of the year. Medicare claims provide a convenience sample that includes approximately 30 million individuals annually, which represents nearly 89% of the US population aged 65 and older and 3.3% of the US population younger than 65, including persons disabled due to blindness. Medicare data for VEHSS include Service Utilization and Medical Diagnoses indicators. Data were suppressed for de-identification to ensure protection of patient privacy. Data will be updated as it becomes available. Detailed information on VEHSS Medicare analyses can be found on the VEHSS Medicare webpage (cdc.gov/visionhealth/vehss/data/claims/medicare.html). Information on available Medicare claims data can be found on the ResDac website (www.resdac.org). The VEHSS Medicare dataset was last updated August 2025.
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description: (Downloaded 1/16/2026)
DOI: 10.3886/e244384v1
title: Medicare Fee for Service (FFS) claims (100%) – Vision and Eye Health Surveillance

description: 2014-2022. This dataset is a de-identified summary table of vision and eye health data indicators from Medicare claims, stratified by all available combinations of age group, race/ethnicity, sex, and state. Medicare claims for VEHSS includes beneficiaries who were fully enrolled in Medicare Part B Fee-for-Service (FFS) for the duration of the year. Medicare claims provide a convenience sample that includes approximately 30 million individuals annually, which represents nearly 89% of the US population aged 65 and older and 3.3% of the US population younger than 65, including persons disabled due to blindness. Medicare data for VEHSS include Service Utilization and Medical Diagnoses indicators. Data were suppressed for de-identification to ensure protection of patient privacy. Data will be updated as it becomes available. Detailed information on VEHSS Medicare analyses can be found on the VEHSS Medicare webpage (cdc.gov/visionhealth/vehss/data/claims/medicare.html). Information on available Medicare claims data can be found on the ResDac website (www.resdac.org). The VEHSS Medicare dataset was last updated August 2025.
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description: (Downloaded 1/16/2026)
DOI: 10.15468/dl.rgykkb
title: Occurrence Download

description: A dataset containing 3376 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Larix kaempferi",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3376 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018840-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18294255
title: Paspalum pyramidale Nees. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.5281/zenodo.18294256
title: Paspalum pyramidale Nees. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.15468/dl.hqwhcb
title: Occurrence Download

description: A dataset containing 440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Larix kaempferi",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 440 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018842-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18294257
title: Paspalum quadrifarium  Lam. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.5281/zenodo.18294258
title: Paspalum quadrifarium  Lam. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.15468/dl.uykkvk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dicranomyia tabashii",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018843-260108223611665/datasets/export for details.
DOI: 10.3886/e244388
title: Rates and Trends in Heart Disease and Stroke Mortality Among US Adults (35+) by County, Age Group, Race/Ethnicity, and Sex – 2000-2019

description: This dataset documents rates and trends in heart disease and stroke mortality. Specifically, this report presents county (or county equivalent) estimates of heart disease and stroke death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (women, men). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.
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description: (Downloaded 1/16/2026)
DOI: 10.3886/e244388v1
title: Rates and Trends in Heart Disease and Stroke Mortality Among US Adults (35+) by County, Age Group, Race/Ethnicity, and Sex – 2000-2019

description: This dataset documents rates and trends in heart disease and stroke mortality. Specifically, this report presents county (or county equivalent) estimates of heart disease and stroke death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (women, men). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.
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description: (Downloaded 1/16/2026)
DOI: 10.5281/zenodo.18290945
title: SuperDARN data in netCDF format (2001-Jan)

description: 2001-Jan SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6800005
title: SuperDARN data in netCDF format (2001-Jan)

description: 2001-Jan SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.3886/e244387
title: U.S. State and Territorial Orders Closing and Reopening Restaurants Issued from March 11, 2020 through May 31, 2021 by County by Day

description: State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.
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description: (Downloaded 1/16/2026)
DOI: 10.3886/e244387v1
title: U.S. State and Territorial Orders Closing and Reopening Restaurants Issued from March 11, 2020 through May 31, 2021 by County by Day

description: State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.
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description: (Downloaded 1/16/2026)
DOI: 10.15468/dl.sktckx
title: Occurrence Download

description: A dataset listing the 204 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((43.07409 -11.15803,43.13243 -12.26488,43.8836 -11.8655,43.4752 -11.07932,43.07409 -11.15803))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Arthropoda, Aves, Mammalia, Squamata)"
 ]
}

 The dataset's 204 records were derived from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018827-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wuakes
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Limothrips cerealium",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 81 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018845-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18294244
title: The Indus Script: Preliminary Lexical and Functional Decipherment

description: This dataset presents the first integrated lexical and functional framework for deciphering the Indus script, covering 417 standardized glyphs (G001–G417). It proposes consistent semantic groupings across economic, administrative, and ritual domains, grounded in contextual frequency and functional morphology.

The release includes three core components:





Phase 1 High-Frequency Function Matrix (Top 25): a quantitative study of the most recurrent signs and their syntactic co-occurrence.




Phase 2 Clause Typology and Grammar Rules: a structural outline of clause formation, relational markers, and compositional syntax.




Indus Script Master Catalogue (G001–G417): a complete lexicon detailing each glyph’s proposed meaning, form, usage context, and confidence level.



Together these files establish a reproducible foundation for future validation, peer commentary, and comparative epigraphic study.All material is original and released for scholarly use under the CC BY-NC 4.0 license.
DOI: 10.3886/e244196
title: Daily Census Tract-Level PM2.5 Concentrations, 2001-2005

description: This dataset provides modeled predictions of PM2.5 levels from the EPA's Downscaler model. Data are at the census tract level for 2001-2005. These data are used by the CDC's National Environmental Public Health Tracking Network to generate air quality measures. Census tract-level datasets contain estimates of the mean predicted concentration and associated standard error. Please refer to the metadata attachment for more information.

Learn more about outdoor air quality on the Tracking Network's website: https://ephtracking.cdc.gov/showAirLanding.action.

By using these data, you signify your agreement to comply with the following requirements:
1. Use the data for statistical reporting and analysis only.
2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals.
3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov.
4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating.
5. Acknowledge, in all reports or presentations based on these data, the original source of the data and CDC.
6. Suggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking.
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description: (Downloaded 1/12/2026)
DOI: 10.3886/e244196v1
title: Daily Census Tract-Level PM2.5 Concentrations, 2001-2005

description: This dataset provides modeled predictions of PM2.5 levels from the EPA's Downscaler model. Data are at the census tract level for 2001-2005. These data are used by the CDC's National Environmental Public Health Tracking Network to generate air quality measures. Census tract-level datasets contain estimates of the mean predicted concentration and associated standard error. Please refer to the metadata attachment for more information.

Learn more about outdoor air quality on the Tracking Network's website: https://ephtracking.cdc.gov/showAirLanding.action.

By using these data, you signify your agreement to comply with the following requirements:
1. Use the data for statistical reporting and analysis only.
2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals.
3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov.
4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating.
5. Acknowledge, in all reports or presentations based on these data, the original source of the data and CDC.
6. Suggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking.
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description: (Downloaded 1/12/2026)
DOI: 10.15468/dl.7fxz5w
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "NetworkKey is 99d66b6c-9087-452f-a9d4-f15f2c2d0e7e",
 "TaxonKey is Chordata"
 ]
 },
 "TaxonKey is one of (Scytalopus affinis [GBIF Backbone Taxonomy])"
 ]
}

 The dataset includes 15 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018847-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7zv6n3
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dicranomyia tristis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 110 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018846-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18294265
title: Paspalum quarinii Morrone & Zuloaga. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.5281/zenodo.18294266
title: Paspalum quarinii Morrone & Zuloaga. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:51
DOI: 10.5281/zenodo.18294269
title: Paspalum repens  P.J.Bergius. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:52
DOI: 10.5281/zenodo.18294270
title: Paspalum repens  P.J.Bergius. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:52
DOI: 10.15468/dl.xs7ga5
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Meloidogyne incognita",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018848-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18294271
title: Paspalum reticulatum Hack. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:52
DOI: 10.5281/zenodo.18294272
title: Paspalum reticulatum Hack. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:52