cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ba5a5t
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is HRV",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Carabus intricatus Linnaeus, 1760"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002767-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ak6gc8
title: Occurrence Download

description: A dataset containing 459854 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swiss National Mammal Databank"
 ]
}

 The dataset includes 459854 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002741-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/6c61effc-9d0c-4246-8a22-ad7618f4f278.v2
title: Data underlying the publication: Sensitivity analysis of the Substance Emission Model v2.1.2 component of the Greenhouse Emission Model

description: In the analysis ensembles of 7-year SEM simulations were performed for 100 assessments for different scenarios and substances. For each assessment, an ensemble of 365 simulations was performed with varying dates of substance application, covering every day of the year. For each simulation the following postprocessing was performed on the daily substance emission (g.m-2.d-1) from the greenhouse and its 10-day moving average:* Determine the of the annual maximum for each of the 7 simulation years.* Calculate the 50th and 90th percentiles over the 7 annual maxima (referred to as PEC50 and the PEC90, respectively).<br>This results in four PEC values (PEC50--daily, PEC90--daily, PEC50--10-day-average, PEC90--10-day-average) for each of the 100x365 simulations. Next, for each of the 100 assessments, the results of the 365 simulations were processed as follows:* Calculate the 90th percentile over 365 values for the four PEC values--this is referred to as the "true" 90th percentile.* Remove 5 simulations for application dates 7-Feb, 21-Apr, 3-Jul, 14-Sep and 26-Nov, resulting in a set of 360 simulations. This is done because 360 has more divisors than 365.<br>Subsequently, processing was performed on subsamples of different sizes N, taken from the 360 simulations. The following subsample sizes were considered: 12, 15, 18, 20, 24, 30, 36, 40, 45, and 60. For each subsample size N, M_N = 360/N sets of subsamples were taken with application date evenly spread over the year. For example, for N=12, M_12=30 sets of application dates were selected, with each set one day offset to the next. This results in 10 sets of subsamples of varying size. For each set N, the following processing was performed:* For each M_N values for the four PECs, calculate the relative difference compared to the true 90th percentile (based on the full 365 set of simulations; see above) as follows: RD = (PEC_est-PEC_365)/PEC_365.* Calculate the 10th percentile over the M_N relative differences for each of the four PECs; this is referred to as the 90th percentile underestimation* For each M_N values for the four PECs, calculate the multiplication factor relative to the true 90th percentile as follows: MF = PEC_est/PEC_365.* Calculate the 90th percentile over the M_N multiplication factors for each of the four PECs.<br>This results in 4000 values for the relative difference and multiplication factor for each combination of assessment (100), subsample size N (10), and PEC quantity (4). The relative underestimations form the data underlying Figure 13.3 in Braakhekke et al. (2024). The multiplication factors for N=12 form the data underlying table 13.1 in Braakhekke et al. (2024).<br>
DOI: 10.15468/dl.t97be6
title: Occurrence Download

description: A dataset containing 2149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Caprimulgus macrurus Horsfield, 1821",
 "Year 2004-2024"
 ]
}

 The dataset includes 2149 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002769-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ga9wwx
title: Occurrence Download

description: A dataset containing 7198 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fimbristylis littoralis Gaudich."
 ]
}

 The dataset includes 7198 records from 283 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002768-241107131044228/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/11308826
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.5281/zenodo.13628516
title: Toxicological evaluation of Vanillin Flavor in E-Liquid Aerosols on Endothelial Cell Function: Findings from the Replica Project

description: Background: There are challenges that require collaboration among researchers to ensure that tobacco harm reduction strategies are evidence-based. One key challenge is evaluating the safety of flavors used in electronic cigarettes (e-cigarettes). While many flavorings are approved as food additives or deemed “generally recognized as safe” (GRAS) for ingestion, this does not guarantee their safety when inhaled. In this context, the international research group Replica replicated a study conducted by Fetterman and colleagues in 2018, investigating the effects of aerosolized vanillin - one of the most popular flavors in vaping - on vascular endothelium when vaporized by an electronic cigarette. Methods: We used Aspire Zelos 3 e-cigarette and prepared e-liquids containing propylene glycol, vegetable glycerin and vanillin. The e-liquids were vaporized under two settings - regular (1 ohm coil using wattage control mode at 14 watts) and sub-ohm (0.3 ohm coil using temperature control mode at 200 °C) – using a vaping machine, following the standardized puffing regime, ISO20768:2018. The vapor was then collected into a trapping solution to prepare aqueous extracts for the treatment of human aortic endothelial cells. We evaluated cytotoxicity, oxidative stress, nitric oxide bioavailability, and inflammation addressing some gaps reported in the original study. Results: We observed some harmful effects, mostly attributable to ethanol, used to dilute vanillin in the original work by Fetterman, but no harmful effects on cell viability, their ability to produce nitric oxide, or oxidative stress from vanillin. Furthermore, no pro-inflammatory effects of vanillin were observed in terms of ICAM-1 and IL-6 gene expression. Conclusions: Our results confirm the endothelial cell dysfunction observed in the original paper, but clarify that these effects are mainly attributable to ethanol and not to vaporized vanillin. These findings suggest that vanillin could be a safer flavoring agent for e-cigarette, without causing adverse effects on the cardiovascular system.
description: Funding: This investigator-initiated research is sponsored by ECLAT Srl, a spin-off of the University of Catania, through a competitive grant from Global Action to End Smoking (formerly known as Foundation for Smoke-Free World), an independent, U.S. nonprofit 501(c) (3) grantmaking organization, accelerating science-based efforts worldwide to end the smoking epidemic. Global Action played no role in designing, implementing, data analysis, or interpretation of the study results. The contents, selection, and presentation of facts, as well as any opinions expressed, are the sole responsibility of the authors and should not be regarded as reflecting the positions of Global Action to End Smoking. ECLAT Srl is a research-based company that delivers solutions to global health problems with particular emphasis on harm minimization and technological innovation.
DOI: 10.15468/dl.2w7vnf
title: Occurrence Download

description: A dataset containing 77 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tetropium parvulum Casey, 1891"
 ]
}

 The dataset includes 77 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008158-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ra92u7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "GadmGid is DEU.3_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Bacidia friesiana (Hepp) Körb."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008161-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p6m6ux
title: Occurrence Download

description: A dataset containing 4503 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Norway",
 "DatasetKey is Norwegian Species Observation Service",
 "OccurrenceStatus is Present",
 "PublishingOrg is d3978a37-635a-4ae3-bb85-7b4d41bc0b88",
 "TaxonKey is Lemmus lemmus (Linnaeus, 1758)"
 ]
}

 The dataset includes 4503 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008160-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dr4uge
title: Occurrence Download

description: A dataset listing the 4 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "TaxonKey is one of (Iguana iguana (Linnaeus, 1758))"
 ]
}

 The dataset's 4 records were derived from 252 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010974-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b543np
title: Occurrence Download

description: A dataset listing the 4 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "TaxonKey is one of (Iguana iguana (Linnaeus, 1758))"
 ]
}

 The dataset's 4 records were derived from 252 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010975-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/e8nm-we52
title: FIRED Macedonia Nov 2000 - July 2024

description: This is event-level polygons for the fire event delineation (FIRED) product for MACEDONIA from November 2000 to July 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more:

Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498
DOI: 10.5066/p1ym68hb
title: Irrigation water use in Kansas, 2016

description: This dataset describes irrigation water use in Kansas in 2016. Volumes of water used, irrigated area, and irrigation application depths are provided for three sets of subareas: (1) Irrigation water use analysis regions that include Groundwater Management Districts (GMDs) with the areas outside of GMDs divided into eastern, central, and western Kansas; (2) Regional Planning Areas (RPAs), which are 14 areas determined by the Kansas Water Office based on hydrologic and administrative boundaries, each with a set of goals outlined in the Kansas Water Vision (https://kwo.ks.gov/water-vision-water-plan/water-vision); and (3) the 105 Kansas counties. Volumes of water used, irrigated area, and application depths are also presented for the subareas by crop type and by irrigation system type. Volumes of water used, irrigated area, and application depth are also provided for ditch companies and irrigation district conveyances.
DOI: 10.15468/dl.bmvaxa
title: Occurrence Download

description: A dataset containing 2625 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Philortyx fasciatus (Gould, 1844)"
 ]
}

 The dataset includes 2625 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010986-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6wnam3
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-100.46952 25.37498,-100.4559 25.3244,-100.31001 25.30301,-100.00849 25.01705,-99.92387 25.06276,-99.97762 25.12456,-99.97497 25.14847,-100.0219 25.20072,-100.05467 25.23526,-100.04362 25.24829,-100.0598 25.27451,-100.07096 25.32695,-100.11045 25.35997,-100.13109 25.35215,-100.16097 25.36851,-100.16809 25.38986,-100.19513 25.43113,-100.23639 25.46741,-100.18939 25.50599,-100.31094 25.61648,-100.58332 25.6872,-100.73019 25.61717,-100.46952 25.37498))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Asphodelus fistulosus L."
 ]
}

 The dataset includes 52 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010985-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9pc8gd
title: Occurrence Download

description: A dataset containing 28079 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Museo Argentino de Ciencias Naturales \"Bernardino Rivadavia\" (MACN). Mammalogy National Collection (MACNMa)"
 ]
}

 The dataset includes 28079 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010981-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ffgb48
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vriesea hieroglyphica (Carrière) É.Morren"
 ]
}

 The dataset includes 120 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010984-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14104730
title: Dataset de Películas de TMDB: Información sobre títulos, puntuaciones y mucho más.

description: Este dataset contiene información detallada sobre películasextráida de The Movie Database (TMDB). Este conjunto de datos, contiene:



Información general de cada título, como el nombre, el año de lanzamiento, la fecha deestreno junto con las siglas del país donde se estrena por primera vez (país de origen), la edadmínima recomendada, la duración, el idioma original, la URL de la imagen de portada, eleslogan de la película, el resumen de la película y su estado.

 Información de valoración, como la puntuación dada por los usuarios.

Los géneros a los que pertenece cada película.

Métricas económicas, como el presupuesto que tuvo la película y los ingresos que ha obtenidohasta la fecha.

Reparto y equipo de producción, como el nombre de los actores principales y el nombre y lafunción de los principales miembros del equipo de producción.
DOI: 10.5281/zenodo.14104731
title: Dataset de Películas de TMDB: Información sobre títulos, puntuaciones y mucho más.

description: Este dataset contiene información detallada sobre películasextráida de The Movie Database (TMDB). Este conjunto de datos, contiene:



Información general de cada título, como el nombre, el año de lanzamiento, la fecha deestreno junto con las siglas del país donde se estrena por primera vez (país de origen), la edadmínima recomendada, la duración, el idioma original, la URL de la imagen de portada, eleslogan de la película, el resumen de la película y su estado.

 Información de valoración, como la puntuación dada por los usuarios.

Los géneros a los que pertenece cada película.

Métricas económicas, como el presupuesto que tuvo la película y los ingresos que ha obtenidohasta la fecha.

Reparto y equipo de producción, como el nombre de los actores principales y el nombre y lafunción de los principales miembros del equipo de producción.
DOI: 10.15468/dl.gzfach
title: Occurrence Download

description: A dataset containing 41526 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Abies cephalonica Loudon, Abies cephalonica Link, 1842, Acacia dealbata Link, Acacia dealbata A.Cunn.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 41526 records from 310 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010987-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11438498
title: VHAKG: Multi-modal Knowledge Graphs with Multi-view Videos of Daily Activities

description: Outline



This dataset is a multimodal knowledge graph (MMKG) of daily activity videos.

This dataset integrates a KG with embedded multi-view videos created by VirtualHome-AIST, an extended version of the VirtualHome simulator, and an event-centric KG generated by VirtualHome2KG.

We named this dataset VHAKG (VirtualHome-AIST-KG).


Details



VHAKG describes 2D bounding boxes of objects every five frames, compositional activities, primitive actions, target objects, object states, 3D bounding boxes, and their time-series changes.

The videos are encoded in base64 and embedded as a literal value.

VHAKG consists of 706 daily activity scenarios (e.g., clean desk, cook fried bread, and relax on sofa) and 3,530 videos captured by five synchronized cameras per scenario.

The file format is RDF (Turtle), which can be loaded into various Triplestores.

VHAKG's vocabularies are defined as an ontology and can be found in vh2kg_schema_v2.0.0.ttl.


Contents



vh2kg_video_base64.tar.gz



{activity name}{scene}_{camera}_2dbbox.ttl: KG with video embedded in base64 format, including 2D bounding box data every 5 frames.



To learn more about {scene}, check here.

To learn more about {camera}, check here.





vh2kg_event.tar.gz



{activity name}_{scene}.ttl: Event-centric KGs representing video content as sequences of events.

vh2kg_schema_v2.0.0.ttl: The ontology file of this dataset.

affordance.ttl: The affordance data of objects that were created by crowdsourcing.



Please see Section III.B of this paper for more information.



add_places.ttl: Events in which agents moved from one room to another.




Tools



A set of tools for searching and extracting videos from VHAKG is available.
DOI: 10.5281/zenodo.11438499
title: VHAKG: Multi-modal Knowledge Graphs with Multi-view Videos of Daily Activities

description: Outline



This dataset is a multimodal knowledge graph (MMKG) of daily activity videos.

This dataset integrates a KG with embedded multi-view videos created by VirtualHome-AIST, an extended version of the VirtualHome simulator, and an event-centric KG generated by VirtualHome2KG.

We named this dataset VHAKG (VirtualHome-AIST-KG).


Details



VHAKG describes 2D bounding boxes of objects every five frames, compositional activities, primitive actions, target objects, object states, 3D bounding boxes, and their time-series changes.

The videos are encoded in base64 and embedded as a literal value.

VHAKG consists of 706 daily activity scenarios (e.g., clean desk, cook fried bread, and relax on sofa) and 3,530 videos captured by five synchronized cameras per scenario.

The file format is RDF (Turtle), which can be loaded into various Triplestores.

VHAKG's vocabularies are defined as an ontology and can be found in vh2kg_schema_v2.0.0.ttl.


Contents



vh2kg_video_base64.tar.gz



{activity name}{scene}_{camera}_2dbbox.ttl: KG with video embedded in base64 format, including 2D bounding box data every 5 frames.



To learn more about {scene}, check here.

To learn more about {camera}, check here.





vh2kg_event.tar.gz



{activity name}_{scene}.ttl: Event-centric KGs representing video content as sequences of events.

vh2kg_schema_v2.0.0.ttl: The ontology file of this dataset.

affordance.ttl: The affordance data of objects that were created by crowdsourcing.



Please see Section III.B of this paper for more information.



add_places.ttl: Events in which agents moved from one room to another.




Tools



A set of tools for searching and extracting videos from VHAKG is available.
DOI: 10.15468/dl.mt3u87
title: Occurrence Download

description: A dataset containing 16599 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plethodon jordani Blatchley, 1901"
 ]
}

 The dataset includes 16599 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010989-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2k949b
title: CCDC 2362271: Experimental Crystal Structure Determination

description: Related Article: Tianhong Chen, Yu-Juan Ma, Guowei Xiao, Xiaoyu Fang, Yumin Liu, Kangjing Li, Dongpeng Yan|2024|Materials Horizons|11|4951|doi:10.1039/D4MH00771A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.