cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25420/britishmuseum.28203842.v1
title: Ngalakano Masweunyane Consent Form

description: Ngalakano Masweunyane Consent Form
DOI: 10.25420/britishmuseum.28203851.v1
title: Nichodimas Cooper Consent Form

description: Nichodimas Cooper Consent form
DOI: 10.25420/britishmuseum.28203830
title: Leema Antony Hiri Consent Form

description: Leema Antony Hiri Consent Form
DOI: 10.25420/britishmuseum.28203827.v1
title: Greine Jordan Consent Form

description: Greine Jordan Consent Form
DOI: 10.7483/opendata.cms.srtj.drn5
title: /XtoAAto4G_X1000A400_TuneCP5_13TeV-madgraphMLM-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.25420/britishmuseum.28203824
title: Chris Wingfield Consent Form

description: Chris Wingfield Consent Form
DOI: 10.15468/dl.s76s7g
title: Occurrence Download

description: A dataset containing 11499 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Crotophaga major Gmelin, 1788",
 "Year 2010-2025"
 ]
}

 The dataset includes 11499 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072808-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f8ke53
title: Occurrence Download

description: A dataset containing 1879 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thryonomyidae"
 ]
}

 The dataset includes 1879 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072807-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p1rbmdut
title: Monthly ensemble outputs from the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system for the conterminous United States, Alaska, Hawaii, and Puerto Rico for water years 2010–2020

description: The Integrated Water Availability Assessment uses an ensemble of outputs from two hydrologic models to assess water supply conditions. Results from the two models, the National Hydrologic Model Precipitation-Runoff Modeling System (NHM-PRMS) and Weather Research and Forecasting model hydrologic modeling system (WRF-Hydro) were averaged to create a single model ensemble. A unique instance of each model was developed specifically for this application (see the following data releases listed in the related external resources below: Sampson et al., 2024; Foks et al., 2025; Foks et al., 2024a-c). Each model was run at its native spatiotemporal resolution and converted to the subwatershed (12-digit hydrologic unit code; HUC12) spatial resolution and year-month temporal resolution for ensembling and assessment purposes. For NHM, the native spatiotemporal resolution is hydrologic response units (HRU), which have an average area of about 75 m2 at a daily time step. For WRF-Hydro, the native spatiotemporal resolution is a 250-m grid at an hourly timestep. The data in this release represent the mean between the results from of each model, by variable (hydrologic state or flux), at the HUC12, year-month resolution. The methods are described in the related primary publication (Gorski et al., 2025) and source code (Martinez et al., 2024), both listed in the related external resources below.
DOI: 10.17632/4x4d2c6pgp.1
title: Combustion Characteristics of Diisopropoxymethane a Low-Reactivity Oxymethylene Ether - RCM Spark Ignition 1

description: First set of RCM laser spark ignition data for "Combustion characteristics of diisopropoxymethane, a low-reactivity oxymethylene ether" in Fuel, DOI: 10.1016/j.fuel.2023.130727. Dataset has been divided into multiple instances due to size limitations. Some data instances have been excluded due to laser misfire (this is why some case numbers appear skipped).

This dataset includes raw RCM pressure and piston position data, and the corresponding images of the ignition event.
DOI: 10.17632/28dyw2ws7j
title: LDHU3_20.1220

description: mt-SAF12 | KRIPP18
Leishmania donovani (HU3 strain)
DOI: 10.17632/28dyw2ws7j.1
title: LDHU3_20.1220

description: mt-SAF12 | KRIPP18
Leishmania donovani (HU3 strain)
DOI: 10.17632/5rfd33344f.1
title: Focus Group Study to Design a Chatbot Intervention to Ameliorate Disparities in Breast Cancer Screening

description: What the dataset is about: this dataset includes aggregated responses from 3 focus groups giving feedback on an early prototype of a chatbot for breast cancer screening outreach 

When the data were collected: May 2021 

How many participants provided data: 3 focus group, 10 total participants. 

What data are included:

Domains 
Motivation to screen
Engagement with chatbot
Reactions to media 
Reactions to content 
Perception of chatbot
Comfortability
Trust
Usefulness
Relatability 
Desired content 
Desired features/function
Usability
DOI: 10.15468/dl.38kfpf
title: Occurrence Download

description: A dataset containing 1242748 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lathyrus nissolia L., Lathyrus palustris L., Lathyrus vernus (L.) Bernh., Lathyrus niger (L.) Bernh., Lathyrus pratensis L., Lathyrus ochrus (L.) DC., Lathyrus linifolius (Reichard) Bässler, Lathyrus gorgoni Parl., Lathyrus clymenum L., Vicia faba L.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1242748 records from 3025 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072802-241126133413365/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.29067764
title: SpaceTrack-TimeSeries: Time Series Dataset towards Satellite Orbit Analysis

description: With advancements in aerospace technology and the widespread deployment of low Earth orbit constellations, challenges to astronomical observation and deep space exploration have intensified. The need for accurate orbital data on space targets, as well as the analysis of satellite positioning, constellation configurations, and deep space satellite behavior, has grown more critical. However, there is a significant gap in publicly available, real-world datasets to support research on space target maneuver prediction and anomaly detection. This paper addresses this gap by collecting and organizing representative maneuver data from the Starlink satellites, which includes precise star-tracking predictions and Two-Line Element (TLE) catalog orbital data. This dataset offers a more realistic and multi-dimensional scenario for modeling space target behavior. It provides valuable insights into practical deployment of maneuver detection and anomaly detection approaches.
DOI: 10.6084/m9.figshare.29067764.v2
title: SpaceTrack-TimeSeries: Time Series Dataset towards Satellite Orbit Analysis

description: With advancements in aerospace technology and the widespread deployment of low Earth orbit constellations, challenges to astronomical observation and deep space exploration have intensified. The need for accurate orbital data on space targets, as well as the analysis of satellite positioning, constellation configurations, and deep space satellite behavior, has grown more critical. However, there is a significant gap in publicly available, real-world datasets to support research on space target maneuver prediction and anomaly detection. This paper addresses this gap by collecting and organizing representative maneuver data from the Starlink satellites, which includes precise star-tracking predictions and Two-Line Element (TLE) catalog orbital data. This dataset offers a more realistic and multi-dimensional scenario for modeling space target behavior. It provides valuable insights into practical deployment of maneuver detection and anomaly detection approaches.
DOI: 10.6084/m9.figshare.29067764.v1
title: SpaceTrack-TimeSeries: Time Series Dataset towards Satellite Orbit Analysis

description: With advancements in aerospace technology and the widespread deployment of low Earth orbit constellations, challenges to astronomical observation and deep space exploration have intensified. The need for accurate orbital data on space targets, as well as the analysis of satellite positioning, constellation configurations, and deep space satellite behavior, has grown more critical. However, there is a significant gap in publicly available, real-world datasets to support research on space target maneuver prediction and anomaly detection. This paper addresses this gap by collecting and organizing representative maneuver data from the Starlink satellites, which includes precise star-tracking predictions and Two-Line Element (TLE) catalog orbital data. This dataset offers a more realistic and multi-dimensional scenario for modeling space target behavior. It provides valuable insights into practical deployment of maneuver detection and anomaly detection approaches.
DOI: 10.15468/dl.7kqhff
title: Occurrence Download

description: A dataset containing 4473 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Halictus maculatus Smith, 1848"
 ]
}

 The dataset includes 4473 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039003-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zh5kfn
title: Occurrence Download

description: A dataset containing 317 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Halictus pollinosus Sichel, 1860"
 ]
}

 The dataset includes 317 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039005-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zcsc99
title: Occurrence Download

description: A dataset containing 310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Coenonympha gardetta darwiniana"
 ]
}

 The dataset includes 310 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039004-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3796ys
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is University of Cincinnati, Margaret H. Fulford Herbarium - Lichens",
 "Country is Croatia"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039006-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xaxkkw
title: Occurrence Download

description: A dataset containing 3804 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Halictus quadricinctus (Fabricius, 1776)"
 ]
}

 The dataset includes 3804 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039007-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wwjdrp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ammatoidea West & G.S.West, 1897",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039008-250525065834625/datasets/export for details.
DOI: 10.21947/2569228
title: Lidar / Standardized Data

description: This dataset contains standardized data from the 10-minute averaged STA files from NREL's profiling lidar (Windcube v2.1) at the WFIP3 BARG site.

Note: these data have NOT been corrected for the motion of the barge.
DOI: 10.5281/zenodo.15650197
title: Table 1 in Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus

description: Table 1. Growth, grazing and carbon acquisition of Bigelowiella natans on Synechococcus strains CC9311 and CC9605. Parameters are for numerical and/ or functional response from Equations 2 and 3 as presented in Figs 7–10. MGR, maximum growth rate (data given as means ± standard error, d –1); MIR; maximum ingestion rate (cells predator –1 h –1); K: prey concentration sustaining IR ½ × MIR (cells ml –1); CA, carbon acquired from prey by Bigelowiella natans per day (pg C predator –1 d –1); MCR, maximum clearance rate (nl predator –1 h –1).
PreyMGRMIRKIRCAMCRNo added Synechococcus cells0.20 (±0.031)Synechococcus CC 93110.38 (±0.075)2.779,78316.6197.2Synechococcus CC 96050.28 (±0.065)2.1816,04013.1331.5
description: Published as part of Yoo, Yeong Du & Palenik, Brian, 2021, Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus, pp. 376 in Phycologia 60 (4) on page 376, DOI: 10.1080/00318884.2021.1941567, http://zenodo.org/record/15520204
DOI: 10.5281/zenodo.15650198
title: Table 1 in Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus

description: Table 1. Growth, grazing and carbon acquisition of Bigelowiella natans on Synechococcus strains CC9311 and CC9605. Parameters are for numerical and/ or functional response from Equations 2 and 3 as presented in Figs 7–10. MGR, maximum growth rate (data given as means ± standard error, d –1); MIR; maximum ingestion rate (cells predator –1 h –1); K: prey concentration sustaining IR ½ × MIR (cells ml –1); CA, carbon acquired from prey by Bigelowiella natans per day (pg C predator –1 d –1); MCR, maximum clearance rate (nl predator –1 h –1).
PreyMGRMIRKIRCAMCRNo added Synechococcus cells0.20 (±0.031)Synechococcus CC 93110.38 (±0.075)2.779,78316.6197.2Synechococcus CC 96050.28 (±0.065)2.1816,04013.1331.5
description: Published as part of Yoo, Yeong Du & Palenik, Brian, 2021, Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus, pp. 376 in Phycologia 60 (4) on page 376, DOI: 10.1080/00318884.2021.1941567, http://zenodo.org/record/15520204
DOI: 10.5281/zenodo.15650199
title: Table 2 in Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus

description: Table 2. Comparison of maximum growth and ingestion rates of protistan grazers on Synechococcus strains CC9311 and CC9605. NM, nutrition mode; ESD, estimated spherical diameter (μm); MGR, maximum growth rate of predator (d –1); MIR, maximum ingestion rate (cells predator –1 h –1); % BC, acquired carbon as percentage of predator species carbon; MGGE, maximum gross growth efficiency (%), negative value not reported. CHL, chlorarachniophyte; CIL, ciliate; CRY, cryptophyte; DIN, dinoflagellate; CM, constitutive mixotrophy; HT, heterotroph.
Synechococcus sp. CC9311MGRPredator speciesTaxonNMESDNo preyAdded preyMIR% BCMGGERef.Bigelowiella natansCHLCM5.00.180.382.7715217This studyGoniomonas pacificaCRYHT7.0−0.080.200.6911.945Apple et al. (2011)Oxyrrhis marinaDINHT14.5−0.07−0.209.62451Apple et al. (2011)Eutintinnuis sp.CILHT68.0−1.40−0.1816012.4-Apple et al. (2011)Syncechococcus sp. CC9605MGRPredator speciesTaxonNMESDNo preyAdded preyMIR% BCMGGERef.Bigelowiella natansCHLCM5.00.200.282.181198This studyGoniomonas pacificaCRYHT7.0−0.080.080.6310.917Apple et al. (2011)Oxyrrhis marinaDINHT14.5−0.070.1356.01419Apple et al. (2011)Eutintinnuis sp.CILHT68.0−1.40−0.241,21394-Apple et al. (2011)
description: Published as part of Yoo, Yeong Du & Palenik, Brian, 2021, Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus, pp. 380 in Phycologia 60 (4) on page 380, DOI: 10.1080/00318884.2021.1941567, http://zenodo.org/record/15520204
DOI: 10.5281/zenodo.15650200
title: Table 2 in Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus

description: Table 2. Comparison of maximum growth and ingestion rates of protistan grazers on Synechococcus strains CC9311 and CC9605. NM, nutrition mode; ESD, estimated spherical diameter (μm); MGR, maximum growth rate of predator (d –1); MIR, maximum ingestion rate (cells predator –1 h –1); % BC, acquired carbon as percentage of predator species carbon; MGGE, maximum gross growth efficiency (%), negative value not reported. CHL, chlorarachniophyte; CIL, ciliate; CRY, cryptophyte; DIN, dinoflagellate; CM, constitutive mixotrophy; HT, heterotroph.
Synechococcus sp. CC9311MGRPredator speciesTaxonNMESDNo preyAdded preyMIR% BCMGGERef.Bigelowiella natansCHLCM5.00.180.382.7715217This studyGoniomonas pacificaCRYHT7.0−0.080.200.6911.945Apple et al. (2011)Oxyrrhis marinaDINHT14.5−0.07−0.209.62451Apple et al. (2011)Eutintinnuis sp.CILHT68.0−1.40−0.1816012.4-Apple et al. (2011)Syncechococcus sp. CC9605MGRPredator speciesTaxonNMESDNo preyAdded preyMIR% BCMGGERef.Bigelowiella natansCHLCM5.00.200.282.181198This studyGoniomonas pacificaCRYHT7.0−0.080.080.6310.917Apple et al. (2011)Oxyrrhis marinaDINHT14.5−0.070.1356.01419Apple et al. (2011)Eutintinnuis sp.CILHT68.0−1.40−0.241,21394-Apple et al. (2011)
description: Published as part of Yoo, Yeong Du & Palenik, Brian, 2021, Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus, pp. 380 in Phycologia 60 (4) on page 380, DOI: 10.1080/00318884.2021.1941567, http://zenodo.org/record/15520204
DOI: 10.5281/zenodo.15650201
title: Table 3 in Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus

description: Table 3. Comparison of ingestion rates and carbon acquisition of mixotrophic and heterotrophic nanoflagellates on diverse Synechococcus strains in the literature. NM, nutrition mode; ESD, estimated spherical diameter (μm); BC, body carbon (pg C cell –1); T, temperature (°C); LI, light intensity (µmol photons m –2 s –1); Nut, nutrient condition; IR, ingestion rates (cells predator –1 h –1) are corrected to 20°C using Q = 2.8 (Hansen et al. 1997); CR, clearance rate (nl predator –1 h –1); CA, 10 carbon acquired from prey by predator per day (pg C predator –1 d –1); % BC: acquired carbon as percentage of predator’s carbon.CHL, chlorarachniophyte; CIL, ciliate; CRY, cryptophyte; EUG, euglenophyte, HNF: heterotrophic nanoflagellate. DIN: dinoflagellate. Och: ochrophyte, RAP, raphidophyte; CM, constitutive mixotrophy; HT, heterotroph.
Predator speciesTaxonNMESDBCTLINutIRCRCA% BCRef.Bigelowiella natans aCHLCM5.011.02020f/22.8197.216.61521Teleaulax amphioxeiaCRYCM5.617.02020f/20.24.62.48.62Heterosigma akashiwo*RAPCM11.01012020f/23.930018.718.53Effrenium voratumDINCM11.11882020f/25.3165.425.413.64Prorocentrum donghaienseDINCM13.22742020f/27.72,60037.013.55Eutreptiella eupharyngeaEUGCM13.61302020f/20.7129.04.43.46Heterocapsa triquetraDINCM15.03642020f/24.4NA21.15.85Alexandrium minutumDINCM16.74622020f/23.2NA15.43.35Gymnodinium impudicumDINCM17.85322020f/214.5NA94.817.85Picophagus flagellatusOchHT2.50.81915PCR-S110.82.54.75757Pseudobodo sp.HNFHT3.02.61815PCR-S113.310.919.07728Cafeteria roenbergensisHNFHT3.43.617NANA18.5NA24.07189Bodo saltansHNFHT4.47.722NANA2.0NA2.329.610Spumella sp.HNFHT5.212.517NANA48.1NA73.55879Ochromonas sp.HNFHT6.825.817NANA176NA30112019Gonimonas pacificaCRYHT7.028.32215SN0.44.62.48.611Uronema sp.CILHT11.71712015NA31.014856.733.212Oxyrrhis marina bDINHT14.51941515SN4.542.226.913.811Oxyrrhis marina bDINHT14.51942030SN8.0NA48.024.713
* The maximum value among the ingestion rates measured at given prey concentrations.
a Synechococcus strain CC9311 as prey
b Synechococcus strain WH8102 as prey
References: 1, this study; 2, Yoo et al. (2017); 3, Jeong et al. (2010); 4, Jeong et al. (2012); 5, Jeong et al. (2005); 6, Yoo et al. (2018); 7, Guillou et al. (2001); 8, Christaki et al. (2002); 9, Boenigk et al. (2001); 10, Dolan & Simek (1998); 11, Apple et al. (2011); 12, Christaki et al. (1999); 13, Strom et al. (2012).
description: Published as part of Yoo, Yeong Du & Palenik, Brian, 2021, Growth and grazing of the chlorarachniophyte Bigelowiella natans (Chlorarachniophyceae) on the marine cyanobacterium Synechococcus, pp. 380 in Phycologia 60 (4) on page 380, DOI: 10.1080/00318884.2021.1941567, http://zenodo.org/record/15520204