cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5885/45780ce-5b08a469e16041d5
title: Soil surface heat flux and temperature data, Tasiapik Valley, Nunavik, Canada (2014-2021)
title: Données de flux de chaleur et de température à la surface du sol, vallée Tasiapik, Nunavik, Canada (2014-2021)

description: This dataset includes heat flux and soil surface temperature data from a permafrost mound (i.e., lithalsa) located within the Tasiapik Valley, near the village of Umiujaq, Nunavik, Quebec, Canada. The data come from two different sample locations, one at the top and one at the side of the permafrost mound. At both locations, heat flux plates are buried at a depth of 8 cm, while two thermistors per location are buried at à depth of 2 and 6 cm. Data were collected from 1 November 2014 – 27 June 2021 using heat flux plates (model HFP01SC self-calibrating heat flux sensor™) and thermistors. These data support the article Fortier et al. (2023).
description: Ces données sur le flux de chaleur et la température à la surface du sol ont été obtenues pour une butte de pergélisol (lithalse) située dans la vallée de Tasiapik, près du village d'Umiujaq, Nunavik, Québec, Canada. Les données proviennent de deux emplacements différents, soit le sommet et le côté de la butte de pergélisol. Aux deux emplacements, les plaques à flux de chaleur ont été enfouies à une profondeur de 8 cm, tandis que deux thermistances par emplacement ont été enfouies à des profondeurs de 2 et 6 cm. Les données ont été collectées du 1 novembre 2014 au 27 juin 2021 à l'aide de plaques à flux de chaleur Hukseflux (modèle HFP01SC self-calibrating heat flux sensor™) et de thermistances. Ces données viennent en complément de l'article Fortier et al. (2023).
DOI: 10.15468/dl.bbnyr2
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paradoxornis bakeri",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043061-250811113504898/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.29906423.v1
title: Who are the female myrmecologists in Brazil?.pdf

description: This research documents women's contributions to Brazilian myrmecology, analyzing their academic trajectories, gender-related challenges, and scientific impact. By highlighting their diverse stories and achievements, we aim to celebrate their legacy, inspire new generations of researchers, and ensure the continued visibility of women in this field.
DOI: 10.15468/dl.p8qmkj
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Canadian Museum of Nature Herbarium",
 "Geometry POLYGON((-89.97942 79.10669,-87.11761 79.10669,-87.11761 80.7145,-89.97942 80.7145,-89.97942 79.10669))",
 "HasCoordinate is true",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 82 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043063-250811113504898/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/12866254
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.15468/dl.4x7app
title: Occurrence Download

description: A dataset containing 20868 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Fouquieria splendens",
 "Country is United States of America",
 "Geometry POLYGON ((-124.762779 24.520416, -124.762779 49.383297, -66.948891 49.383297, -66.948891 24.520416, -124.762779 24.520416))",
 "CoordinateUncertaintyInMeters is less than 5000"
 ]
}

 The dataset includes 20868 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043062-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15485/2350816
title: L0 Data from the 2018 NGEE Arctic LiDAR Unoccupied Aerial System Campaign at the Kougarok 64 Field Site, Seward Peninsula, Alaska

description: Airborne remote sensing data collected from Los Alamos National Laboratory’s (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 64 along the Kougarok road (Nome-Taylor Highway) between Nome, Alaska and Taylor, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data at regular intervals along 15 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths (*.kml) and raw lidar data files (KG_*__2018_07_*_cmbd.zip or *.lpd). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and .rtcm3 files), as well as ground control point locations used during the campaign (.shp).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
DOI: 10.15485/2370315
title: Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2019-2021

description: Time lapse camera images from Kougarok mile marker (MM) 64 and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2019 to August 2021. Thirty three Wingscape Timelapse Pro cameras were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from were recorded at hourly intervals from 11 AM to 2 PM, continuously for 25 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
DOI: 10.15468/dl.byq3k3
title: Occurrence Download

description: A dataset containing 404 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 404 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043066-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jdaayg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Austria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043068-250811113504898/datasets/export for details.
DOI: 10.15468/dl.8rk85f
title: Occurrence Download

description: A dataset containing 134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 134 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043065-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.das52d
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Suthora przewalskii",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043069-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/7zsa1b
title: regions_Explore2.tab

description: :unav
DOI: 10.57745/dyjwrh
title: regionHydro.zip

description: :unav
DOI: 10.57745/axvd3i
title: secteurs_Explore2.tab

description: :unav
DOI: 10.57745/ehrnoj
title: secteurHydro.zip

description: :unav
DOI: 10.57745/vpiiyj
title: Régions et secteurs hydrographiques associés aux points de simulation des modèles d'hydrologie de surface du projet Explore2

description: Regroupe des métadonnées textuelles et spatiales sur les régions et secteurs hydrographiques associés aux 3991 points de simulation retenus pour l'hydrologie de surface. Ce dépôt regroupe : Pour les régions hydrographiques, un fichier regions_Explore2.csv contenant les métadonnées textuelles et un shapefile zippé regionHydro.zip regroupant le SIG associé, et pour les secteurs hydrographiques, un fichier secteurs_Explore2.csv contenant les métadonnées textuelles et un shapefile zippé secteurHydro.zip regroupant le SIG associé.
DOI: 10.15468/dl.p33ybg
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Chile",
 "HasCoordinate is true"
 ]
}

 The dataset includes 37 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043071-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zuehd8
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Belgium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043070-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4r9pcx
title: Occurrence Download

description: A dataset containing 363 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Suthora davidiana",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 363 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043073-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkznps
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Denmark",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043072-250811113504898/datasets/export for details.
DOI: 10.15468/dl.eqfxtp
title: Occurrence Download

description: A dataset listing the 10813 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is IBGE herbarium - Herbário IBGE - Herbário Virtual REFLORA"
 ]
}

 The dataset's 10813 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043059-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7byu2a
title: Occurrence Download

description: A dataset containing 1741 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "Geometry POLYGON((-79.7 4.3,-77.9 4.3,-77.9 6.3,-79.7 6.3,-79.7 4.3))"
 ]
}

 The dataset includes 1741 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043075-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b9nh9p
title: Occurrence Download

description: A dataset containing 421 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-89.97942 79.10669,-87.11761 79.10669,-87.11761 80.7145,-89.97942 80.7145,-89.97942 79.10669))",
 "HasCoordinate is true",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 421 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043074-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15485/2561511
title: Data and scripts from: “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”

description: This data package includes data and scripts from the manuscript “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”.The study addressed common challenges faced in environmental sensing and modeling, including uncertain input data, missing sensor observations, and high-dimensional datasets with interrelated but redundant variables. Point-scaled meteorological and soil sensor observations were perturbed with noises and missing values, and denoising autoencoder (DAE) neural networks were developed to reconstruct the perturbed data and further predict evapotranspiration. This study concluded that (1) the reconstruction quality of each variable depends on its cross-correlation and alignment to the underlying data structure, (2) uncertainties from the models were overall stronger than those from the data corruption, and (3) there was a tradeoff between reducing bias and reducing variance when evaluating the uncertainty of the machine learning models.This package includes:(1)	Four ipython scripts (.ipynb): “DAE_train.ipynb” trains and evaluates DAE neural networks, “DAE_predict.ipynb” makes predictions from the trained DAE models, “ET_train.ipynb” trains and evaluates ET prediction neural networks, and “ET_predict.ipynb” makes predictions from trained ET models.(2)	One python file (.py): “methods.py” includes all user-defined functions and python codes used in the ipython scripts.(3)	A “sub_models” folder that includes five trained DAE neural networks (in pytorch format, .pt), which could be used to ingest input data before being fed to the downstream ET models in ‘ET_train.ipynb” or ‘ET_predict.ipynb’.(4)	Two data files (.csv). Daily meteorological, vegetation, and soil data is in “df_data.csv”, where “df_meta.csv” contains the location and time information of “df_data.csv”. Each row (index) in “df_meta.csv” corresponds to each row in “df_data.csv”. These data files are formatted to follow the data structure requirements and be directly used in the ipython scripts, and they have been shuffled chronologically to train machine learning models. The meteorological and soil data was collected using point sensors between 2019-2023 at(4.a) Three shrub-dominated field sites in East River, Colorado (named “ph1”, “ph2” and “sg5” in “df_meta.csv”, where “ph1” and “ph2” were located at PumpHouse Hillslopes, and “sg5” was at Snodgrass Mountain meadow) and(4.b) One outdoor, mesoscale, and herbaceous-dominated experiment in Berkeley, California (named “tb” in “df_meta.csv”, short for Smartsoils Testbed at Lawrence Berkeley National Lab).- See "df_data_dd.csv" and "df_meta_dd.csv" for variable descriptions and the Methods section for additional data processing steps. See "flmd.csv" and "README.txt" for brief file descriptions.- All ipython scripts and python files are written in and require PYTHON language software.
DOI: 10.11578/endf/2571019
title: ENDF/B-VIII.1

description: The ENDF/B-VIII.1 release is the newest evaluated nuclear data library produced, distributed, and recommended by CSEWG for use in nuclear science and technology applications. Among the many key advances, relative to the previous version ENDF/B-VIII.0, are: re-evaluation of 239Pu file by a joint international effort; updated 16,18O, 19F, 28-30Si, 50-54Cr, 55Mn, 54,56,57Fe, 63,65Cu, 139La, 233,235,238U, and 240,241Pu neutron nuclear data by the IAEA-coordinated INDEN collaboration; significant changes for 3He, 6Li, 9Be, 51V, 88Sr, 103Rh, 140,142Ce, Dy, 181Ta, Pt, 206-208Pb, and 234,236U neutron data; new nuclear data for the photo-nuclear, being 196 adopted from the IAEA2019 Photonuclear Data Library and one new file from JENDL-5; and new evaluations for the charged-particle and atomic sublibraries. Numerous thermal neutron scattering kernels were re-evaluated or provided for the very first time. Additionally, new covariance testing was implemented. ENDF/B-VIII.1 reduced bias in the simulations of many integral experiments with particular progress noted for fluorine, copper and stainless steel containing benchmarks. Data issues which had hindered the deployment of ENDF/B-VIII.0 for commercial nuclear power applications in high burn-up situations, were addressed. ENDF/B-VIII.1 data are distributed in both ENDF-6 and GNDS formats.
DOI: 10.15468/dl.hc87vd
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043079-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfv3v7
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043077-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6urqc6
title: Occurrence Download

description: A dataset containing 368 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Suthora fulvifrons",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 368 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043080-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k5hz6k
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erodium malacoides",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043078-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5885/45783ce-851e81ae50cf419b
title: Subsurface ground temperature data, Tasiapik Valley, Nunavik, Canada (2001-2021)
title: Données de température du sol, vallée Tasiapik, Nunavik, Canada (2001-2021)

description: This dataset includes ground temperature data from a permafrost mound (i.e., lithalsa) located within the Tasiapik Valley, near the village of Umiujaq, Nunavik, Quebec, Canada. The data come from three different thermistor arrays located on the permafrost mound. The maximum depth of investigation is 17 meters. Data were collected from 28 June 2001 – 14 October 2021 using thermistors. These data support the article Fortier et al. (2023).
description: Ces données sur la température du sol ont été obtenues pour une butte de pergélisol (lithalse) située dans la vallée de Tasiapik, près du village d'Umiujaq, Nunavik, Québec, Canada. Les données proviennent de trois chaînes de thermistances situées sur la butte de pergélisol. La profondeur maximale d'investigation est de 17 mètres. Les données ont été collectées du 28 juin 2001 au 14 octobre 2021 à l'aide de thermistances. Ces données viennent en complément de l'article Fortier et al. (2023).
DOI: 10.11578/endf/2571016
title: ENDF/B-VIII.1: Electron Reaction Sublibrary

description: The electrons sublibrary aims to describe electron-atomic cross section data, corresponding to the interaction between electrons and the different atoms. For ENDF/B-VIII.1 we adopted the EPICS2023 EEDL evaluations.
DOI: 10.15468/dl.jcxzjv
title: Occurrence Download

description: A dataset containing 401116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-91.01633 33.70092,-84.31111 33.82235,-81.63006 35.37547,-75.9157 40.74231,-74.74121 42.95556,-76.00898 43.53324,-76.07654 43.57536,-78.83032 42.55633,-82.387 41.38047,-84.77756 41.25457,-88.80069 41.21072,-91.01633 33.70092))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Caudata"
 ]
}

 The dataset includes 401116 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043034-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11578/endf/2571015
title: ENDF/B-VIII.1: Deuteron Reaction Sublibrary

description: The deuterons sublibrary aims to describe nuclear reactions between incident deuteron particles and different nuclei. For ENDF/B-VIII.1, we adopted additions and corrections to the ENDF/B-VIII.0 d+t file, as well as new LANL evaluation updates for <sup>3</sup>He and <sup>6</sup>Li.