cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18248204
title: Malicious Telegram channel selectio from Spain and Lithuania

description: This dataset contains a collection of messages extracted from public Telegram channels from Spain and Lithuania, which were identified as potentially involved in the dissemination of malicious, harmful, or misleading content. The dataset includes both textual content and rich engagement metadata. For each message, it provides information about the publishing channel, associated country and thematic label, publication date, message text, and interaction indicators such as number of views, forwards, and replies. In addition, the dataset includes details about embedded media, extracted external links, referenced domains and top-level domains, emoji usage, and whether the message was forwarded from another channel.

Data spans from 2018-05-03 1to 2024-05-18 

The data contains the following tabular information:





country: Country associated with the channel where the message was published.




channel: Name of the Telegram channel where the message was posted.




study: Label indicating the study or thematic category associated with the channel/message (e.g., AntiVAX). Missing values indicate that no study label was assigned.




domains: Domain name of the website(s) referenced in the message (if any).




topLevelDomains: Top-level domain (TLD) extracted from the referenced links (e.g., com, org, me, co.nz).




_id: Internal identifier used to group or index records (not the original Telegram message ID).




date: Date and time when the message was published (UTC, ISO 8601 format).




forwards: Number of times the message was forwarded.




mentioned: Boolean value indicating whether the message contains mentions (e.g., tagged users or channels).




message: Full textual content of the message.




replies: Number of replies received by the message.




mediaType: Type of media attached to the message, if any (e.g., photo, video, link, none).




views: Number of views of the message.




emoji_counts: Serialized representation of emojis appearing in the message and their frequencies.




mediaWebpageSiteName: Name of the website associated with the embedded media or link preview (if available).




extractedLinks: List of URLs extracted from the message.




extractedLinks_len: Number of links extracted from the message.




fwd_from_ch_id: Identifier of the original channel if the message was forwarded from another channel.
DOI: 10.3886/e244175v1
title: PLACES: Local Data for Better Health, ZCTA Data 2020 release

description: This dataset contains model-based ZIP Code tabulation Areas (ZCTA) level estimates for the PLACES project 2020 release. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 27 measures: 5 chronic disease-related unhealthy behaviors, 13 health outcomes, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.
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description: (Downloaded 1/12/2026)
DOI: 10.15468/dl.6a4xr9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.29.7_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009591-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z2k6ct
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.37.24_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 68 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009593-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13012/b2idb-2908614_v1
title: Data for Brachypodium SPEECHLESS2 promoter drives expression of a synthetic EPF to reduce stomatal density in sugarcane without pleiotropic effects

description: Datasheets relating to the article "Brachypodium SPEECHLESS2 promoter drives expression of a synthetic EPF to reduce stomatal density in sugarcane without pleiotropic effects" published in Plant Biotechnology Journal.
DOI: 10.5281/zenodo.18208113
title: Notas de leitura do processo "Proyecto de 40 Viviendas y Urbanización correspondiente al Grupo 29 de Octubre, Benavente [1955-1976]"

description: Notas de leitura do processo “Proyecto de 40 Viviendas y Urbanización correspondiente al Grupo 29 de Octubre, Benavente [1955-1976]” existente no Archivo Histórico Provincial de Zamora, em Zamora. 

Registo efetuado em março de 2025 no âmbito do projeto de investigação ReARQ.IB – Built Environment Knowledge for Resilient, Sustainable Communities: Understanding Everyday Modern Architecture and Urban Design in the Iberian Peninsula (1939-1985) (ERC GA949686) e publicado online em https://arquitecturaaqui.eu/es/documentacion/expedientes/61261/proyecto-de-40-viviendas-y-urbanizacion-correspondiente-al-grupo-29-de-octubre-benavente-1955-1976. 

Dados exportados da plataforma Arquitectura Aqui (https://arquitecturaaqui.eu), repositório do referido projeto, em janeiro de 2026.
DOI: 10.5281/zenodo.18208114
title: Notas de leitura do processo "Proyecto de 40 Viviendas y Urbanización correspondiente al Grupo 29 de Octubre, Benavente [1955-1976]"

description: Notas de leitura do processo “Proyecto de 40 Viviendas y Urbanización correspondiente al Grupo 29 de Octubre, Benavente [1955-1976]” existente no Archivo Histórico Provincial de Zamora, em Zamora. 

Registo efetuado em março de 2025 no âmbito do projeto de investigação ReARQ.IB – Built Environment Knowledge for Resilient, Sustainable Communities: Understanding Everyday Modern Architecture and Urban Design in the Iberian Peninsula (1939-1985) (ERC GA949686) e publicado online em https://arquitecturaaqui.eu/es/documentacion/expedientes/61261/proyecto-de-40-viviendas-y-urbanizacion-correspondiente-al-grupo-29-de-octubre-benavente-1955-1976. 

Dados exportados da plataforma Arquitectura Aqui (https://arquitecturaaqui.eu), repositório do referido projeto, em janeiro de 2026.
DOI: 10.15468/dl.mxbues
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.29.8_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 126 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009594-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6cpfs2
title: Occurrence Download

description: A dataset containing 212919 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-59.8039 3.50725,-59.35364 3.50305,-59.28037 3.36873,-59.14599 3.44829,-59.14012 3.59987,-59.05835 3.60777,-58.95717 3.5508,-58.81474 3.57349,-58.72247 3.66207,-58.38597 3.78216,-58.36828 3.83176,-58.44354 4.02548,-58.57306 4.02892,-58.52028 4.09576,-58.61264 4.15631,-58.69506 4.13952,-58.74641 4.20353,-58.83795 4.16422,-58.89755 4.19279,-58.96795 4.13891,-59.06286 4.18614,-59.73036 4.1941,-59.61898 4.13254,-59.65436 4.06959,-59.52694 3.96938,-59.59078 3.88878,-59.58495 3.82341,-59.66661 3.78073,-59.66856 3.70296,-59.76551 3.62525,-59.85051 3.60462,-59.8039 3.50725))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 212919 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009568-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ug8ffv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.37.25_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009596-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/7532
title: my-wonderful-dataset
DOI: 10.57967/hf/5054
title: my-wonderful-dataset
DOI: 10.3886/e244176
title: 500 Cities: Local Data for Better Health, 2017 release

description: This is the complete dataset for the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.
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description: (Downloaded 1/12/2026)
DOI: 10.3886/e244176v1
title: 500 Cities: Local Data for Better Health, 2017 release

description: This is the complete dataset for the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.
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description: (Downloaded 1/12/2026)
DOI: 10.5519/qd.yfyod1al
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (96 records)
DOI: 10.15468/dl.ftnhqc
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is one of (Viet Nam, Lao People’s Democratic Republic, Cambodia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pyrenaria"
 ]
}

 The dataset includes 9 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009598-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sezcn4
title: Occurrence Download

description: A dataset containing 27444 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "GadmGid is one of (COL.15.82_2)"
 ]
}

 The dataset includes 27444 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009597-260108223611665/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.30983515
title: Data for submitted manuscript <i>Characterizing bee (Hymenoptera: Apoidea: Anthophila) roadkill across Texas, United States of America </i>by James L. Tracy, Shelby K. Kilpatrick, Karen Wright, Elise V. Voltura, Anna-Capri Perez, Jasper Klein, Adrienne Brundage, and Robert Coulson

description: ABSTRACT1. Roadkill is an often unrecognized significant contributor to bee pollinator decline. Additional surveys can further reveal how roadkill impacts bee populations, especially for declining species.2. We conducted 100 m roadside transect surveys across Texas, USA during spring and autumn 2020 and spring 2021, identifying roadkill bees to the lowest feasible taxon to map roadkill distribution and hotspots and estimate regional roadkill and community metrics.3. We also compared our results with data newly extracted from other bee roadkill studies, including a Utah vehicle-mounted sticky trap survey and a Tennessee year-round roadside transect study. We correlated and compared bee genera median body lengths and their relative abundance among Texas and Utah bee roadkill surveys and iNaturalist occurrence data. 4. Roadkill was extremely highly skewed towards hotspots. Approximately 4.6–11.6 million bees were killed on Texas roads in 2020, based on boot strapped accelerated bias-corrected 95% CI. These included mean estimates of 336,213 Bombus pensylvanicus and 45,847 B. sonorus, both species of conservation concern. Non-lethal roadside transect methods commonly detected larger-bodied Bombus and Xylocopa bees absent in lethal Utah vehicle-mounted sticky trap surveys. Conversely, Utah sticky trap surveys detected abundant smaller-sized Perdita and Lasioglossum bees that were rare or absent from roadside transect studies.5. Roadkill hotspots for bees of conservation concern can be better identified through combining multi-seasonal roadside transect replicates with data from vehicle-mounted foam-backed sticky traps or non-lethal vehicular bee sweepers. Accounting for the adjacent habitat and bee community can facilitate identifying and mitigating bee roadkill susceptibility.<br>
DOI: 10.6084/m9.figshare.30983515.v3
title: Data for submitted manuscript <i>Characterizing bee (Hymenoptera: Apoidea: Anthophila) roadkill across Texas, United States of America </i>by James L. Tracy, Shelby K. Kilpatrick, Karen Wright, Elise V. Voltura, Anna-Capri Perez, Jasper Klein, Adrienne Brundage, and Robert Coulson

description: ABSTRACT1. Roadkill is an often unrecognized significant contributor to bee pollinator decline. Additional surveys can further reveal how roadkill impacts bee populations, especially for declining species.2. We conducted 100 m roadside transect surveys across Texas, USA during spring and autumn 2020 and spring 2021, identifying roadkill bees to the lowest feasible taxon to map roadkill distribution and hotspots and estimate regional roadkill and community metrics.3. We also compared our results with data newly extracted from other bee roadkill studies, including a Utah vehicle-mounted sticky trap survey and a Tennessee year-round roadside transect study. We correlated and compared bee genera median body lengths and their relative abundance among Texas and Utah bee roadkill surveys and iNaturalist occurrence data. 4. Roadkill was extremely highly skewed towards hotspots. Approximately 4.6–11.6 million bees were killed on Texas roads in 2020, based on boot strapped accelerated bias-corrected 95% CI. These included mean estimates of 336,213 Bombus pensylvanicus and 45,847 B. sonorus, both species of conservation concern. Non-lethal roadside transect methods commonly detected larger-bodied Bombus and Xylocopa bees absent in lethal Utah vehicle-mounted sticky trap surveys. Conversely, Utah sticky trap surveys detected abundant smaller-sized Perdita and Lasioglossum bees that were rare or absent from roadside transect studies.5. Roadkill hotspots for bees of conservation concern can be better identified through combining multi-seasonal roadside transect replicates with data from vehicle-mounted foam-backed sticky traps or non-lethal vehicular bee sweepers. Accounting for the adjacent habitat and bee community can facilitate identifying and mitigating bee roadkill susceptibility.<br>
DOI: 10.6084/m9.figshare.30983515.v2
title: Data for submitted manuscript <i>Characterizing bee (Hymenoptera: Apoidea: Anthophila) roadkill across Texas, United States of America </i>by James L. Tracy, Shelby K. Kilpatrick, Karen Wright, Elise V. Voltura, Anna-Capri Perez, Jasper Klein, Adrienne Brundage, and Robert Coulson

description: ABSTRACT1. Roadkill is an often unrecognized significant contributor to bee pollinator decline. Additional surveys can further reveal how roadkill impacts bee populations, especially for declining species.2. We conducted 100 m roadside transect surveys across Texas, USA during spring and autumn 2020 and spring 2021, identifying roadkill bees to the lowest feasible taxon to map roadkill distribution and hotspots and estimate regional roadkill and community metrics.3. We also compared our results with data newly extracted from other bee roadkill studies, including a Utah vehicle-mounted sticky trap survey and a Tennessee year-round roadside transect study. We correlated and compared bee genera median body lengths and their relative abundance among Texas and Utah bee roadkill surveys and iNaturalist occurrence data. 4. Roadkill was extremely highly skewed towards hotspots. Approximately 4.6–11.6 million bees were killed on Texas roads in 2020, based on boot strapped accelerated bias-corrected 95% CI. These included mean estimates of 336,213 Bombus pensylvanicus and 45,847 B. sonorus, both species of conservation concern. Non-lethal roadside transect methods commonly detected larger-bodied Bombus and Xylocopa bees absent in lethal Utah vehicle-mounted sticky trap surveys. Conversely, Utah sticky trap surveys detected abundant smaller-sized Perdita and Lasioglossum bees that were rare or absent from roadside transect studies.5. Roadkill hotspots for bees of conservation concern can be better identified through combining multi-seasonal roadside transect replicates with data from vehicle-mounted foam-backed sticky traps or non-lethal vehicular bee sweepers. Accounting for the adjacent habitat and bee community can facilitate identifying and mitigating bee roadkill susceptibility.<br>
DOI: 10.5683/sp3/4aghgu
title: Data for figure 2 in "Habitat-selecting life history"

description: Contains data used in Figure 2 of "Habitat-selecting life history"
description: Data include generation number = "Generation"; the number of individuals following an ideal free distribution in a constant environment = "Constant"; the number when habitat A is more variable than is habitat B = "A more variable"; and the number when habitat B is more variable than habitat A = "B more variable".