cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2x647m
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala floribunda (Wight) Koehne"
 ]
}

 The dataset includes 34 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014648-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e43e9r
title: Occurrence Download

description: A dataset containing 20380 species occurrences available in GBIF matching the query:
{
 "and" : [
 "FamilyKey is Magnoliaceae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen",
 "Continent is Asia"
 ]
}

 The dataset includes 20380 records from 144 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014649-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c4fyk7
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala hexandra Koehne"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014651-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nchxyu
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Dominican Republic",
 "TaxonKey is Pereskia quisqueyana Alain"
 ]
}

 The dataset includes 11 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014650-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vp484q
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala illecebroides (Arn. ex C.B.Clarke) Koehne"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014653-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b2dscx
title: Occurrence Download

description: A dataset containing 5785 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Simarouba amara Aubl., Simarouba opaca (Engl.) Radlk. ex F.Boas, Zwingera amara (Aubl.) Willd., Simaruba amara Aubl.)"
 ]
}

 The dataset includes 5785 records from 319 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014652-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xqt3ma
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala lucalensis A.Fern. & Diniz"
 ]
}

 The dataset includes 16 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014657-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bzf5uj
title: Occurrence Download

description: A dataset containing 5327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pavo muticus Linnaeus, 1766"
 ]
}

 The dataset includes 5327 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014656-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.95je6a
title: Occurrence Download

description: A dataset containing 5286677 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)"
 ]
 }
 }
 ]
 },
 "DatasetKey is Florabank1 - A grid-based database on vascular plant distribution in the northern part of Belgium (Flanders and the Brussels Capital region)"
 ]
}

 The dataset includes 5286677 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014629-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gnw8vp
title: Occurrence Download

description: A dataset containing 2095 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleurotus ostreatus (Jacq.) P.Kumm.",
 "Country is Germany",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 2095 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014659-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.23m2vn
title: Occurrence Download

description: A dataset containing 2226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "TaxonKey is Meles meles (Linnaeus, 1758)"
 ]
}

 The dataset includes 2226 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014658-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4vr65
title: Occurrence Download

description: A dataset listing the 7661 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is The birds collection (ZO) of the Muséum national d'Histoire Naturelle (MNHN - Paris)"
 ]
}

 The dataset's 7661 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014627-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rmmeen
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala macrandra Koehne"
 ]
}

 The dataset includes 27 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014662-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.chzhmv
title: Occurrence Download

description: A dataset containing 100 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Dominican Republic",
 "TaxonKey is Consolea moniliformis (L.) A.Berger"
 ]
}

 The dataset includes 100 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014661-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.enh8jp
title: Occurrence Download

description: A dataset containing 13652 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Meles meles (Linnaeus, 1758)"
 ]
}

 The dataset includes 13652 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014660-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84sk52
title: Occurrence Download

description: A dataset containing 12648 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Sweden",
 "OccurrenceStatus is Present",
 "TaxonKey is Canidae",
 "Year 2020-2024"
 ]
}

 The dataset includes 12648 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014663-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.vaapbnxk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (856 records)
DOI: 10.15468/dl.a7bkz6
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala malabarica Pradeep, K.T.Joseph & Sivar."
 ]
}

 The dataset includes 7 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014664-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17903/fk2/xcd9n8
title: Resarching educational needs in small enterprises and the impact of educational programs

description: This study deals with the investigation of future training needs of Greek small businesses and the effects of actions of lifelong learning in the personal, social and professional progress of trainees. Towards this direction we conducted an overview of Greek and European SMEs, the role of human capital and lifelong learning in SMEs and the literature investigating the training needs and effects of lifelong education in participants' lives. Additional fieldwork was conducted to determine the training needs and related effects. The methodological approach that we adopted includes a quantitative field survey based on questionnaire for the investigation of the needs and effects of lifelong learning programs as well as qualitative field survey based on focus groups and personal interviews. Both surveys took place in six major cities following specific instructions and after training of the staff implementing them. For the analysis we used special software processing and the approach of structural equations (Structural Equation Modelling - SEM). The strategy of triangulation which was used to further support the findings of the survey revealed a strong convergence of the results of quantitative - qualitative surveys. The results highlighted the importance and the preference for specifications regarding space, time, methods, training subjects, and the effects at various levels, their relationship with incentives for participation and the role of skills development in understanding the effects. Finally we made recommendations that address the whole range of lifelong education programs as well as policy guides for the next programming period of IME GSEVEE.
DOI: 10.15468/dl.fu8h5q
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mammillaria columbiana subsp. yucatanensis (Britton & Rose) D.R.Hunt"
 ]
}

 The dataset includes 129 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014666-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rhe4bp
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rotala malampuzhensis R.V.Nair"
 ]
}

 The dataset includes 13 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014668-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/oxkehn
title: data diatomées sites de la source de Ceix (Gimeaux) étudiés pour le suivi à long terme entre janvier 2020 et mars 2021 Beauger et al. 2024 Botany Letters

description: Durant la campagne, les diatomées ont été collectées en fonction du substrat dominant observé pour chaque point d'échantillonnage (P1 et P2: sédiments; P3 et P4: travertin). Les comptages ont été réalisés en microscopie optique. Au minimum 400 individus ont été identifiés et comptés. Beauger_data-diatoms i.e. the community data table gathering the information about the abundance (counts) of each species for each of the 4 sampling sites of Ceix spring studied
DOI: 10.48579/pro/oxkehn/ea7xyx
title: Beauger_data-diatoms.tab

description: :unav
DOI: 10.15468/dl.b4e4m3
title: Occurrence Download

description: A dataset listing the 22492 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Ghana",
 "BasisOfRecord is one of (Human Observation, Specimen)"
 ]
}

 The dataset's 22492 records were derived from 651 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014640-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5255/ukda-sn-857460
title: SPIRIT and CONSORT Surrogate Development Surveys: Delphi Survey, Consensus Meeting, PPIE Feedback Surveys, 2022-2023

description: Randomised controlled trials commonly use surrogate endpoints to substitute for a target outcome (outcome of direct interest and relevance to trial participants, clinicians, and other stakeholders, e.g., all-cause mortality) to improve their efficiency, (through shorter trial duration, reduced sample size, and thus lower research costs), ethical or practical reasons. However, a consequence of reliance on surrogate endpoints is the increase of the uncertainty of an intervention’s treatment effect and potential failure to provide adequate information on intervention harms. This has led to calls for improved reporting of trials using surrogate endpoints. This project aimed to develop consensus-driven reporting guidelines for protocols and trial reports using surrogate endpoints as the primary outcome(s): SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) extension checklist: SPIRIT-Surrogate; and CONSORT (Consolidated Standards of Reporting Trials) extension checklist: CONSORT-Surrogate. The extensions were developed using four phases: literature reviews to identify potential items for reporting (searches up to May 27th 2022); Delphi survey (to rate potential items by a multidisciplinary group of stakeholders) conducted between August 24th to December 11th 2022; consensus meeting (to finalise checklist items) held on March 13-14th , 2023; and knowledge translation (piloting of checklist). The SPIRIT-Surrogate extension includes nine items modified from the SPIRIT 2013 checklist. The extension includes nine items modified from the CONSORT 2010 checklist and two new items.
DOI: 10.15468/dl.p959ru
title: Occurrence Download

description: A dataset containing 11457 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY-NC 4.0)",
 "TaxonKey is Meles meles (Linnaeus, 1758)"
 ]
}

 The dataset includes 11457 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014667-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/5lgzeq
title: data physico-chimie sites de la source de Ceix (Gimeaux) étudiés pour le suivi à long terme entre janvier 2020 et mars 2021 Beauger et al. 2024 Botany Letters

description: Fichier comprenant la date, les ions majeurs:Li Na K Mg2 Ca Cl Br NO3 SO42 Les carbonates: HCO3 La conductivité: Cond µs/cm le pH: pH l'oxygène dissous dans l'eau en % : O2 % La température de l'eau: T_eau °C Les coordonnées en Lambert 93: E; N; alt pour chaque site d'échantillonnage à la source de Ceix (Gimeaux)
DOI: 10.48579/pro/5lgzeq/ai7voz
title: Beauger_chimie.tab

description: :unav
DOI: 10.15468/dl.78pt2k
title: Occurrence Download

description: A dataset containing 85829 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is da86174a-a605-43a4-a5e8-53d484152cd3",
 "TaxonKey is Corylus avellana L."
 ]
}

 The dataset includes 85829 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014665-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bh9pdh
title: Occurrence Download

description: A dataset containing 2226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "TaxonKey is Meles meles (Linnaeus, 1758)"
 ]
}

 The dataset includes 2226 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014669-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10462470
title: Code and partial data used in "Vertically recurrent neural networks for sub-grid parameterization"

description: This repository contains the RNN training and evaluation code used in the paper Vertically recurrent neural networks for sub-grid parameterization

 



 The radiative transfer emulation data can be accessed with through a Climetlab plugin (Climetlab-maelstrom-radiation). 

Datasets are downloaded and explained in the demo notebook here https://git.ecmwf.int/projects/MLFET/repos/maelstrom-radiation/browse/notebooks/demo_radiation.ipynb
In addition the full training and testing code used in the paper is uploaded here (pu-maelstrom-radiation.tar.gz).

 


Three parameterization problems from earlier studies are also included (we have modified the code from these papers to incorporate RNNs): 



non-orographic gravity wave drag (Chantry et al. 2021) 



Based on TensorFlow

This repository uses the CliMetLab plugin and downloads the data from the European Weather Cloud



non-local parameterization (Wang et al. 2022)



The new code is based on TensorFlow, so you'll need both PyTorch and TensorFlow to run everything

See original paper for data access



moist physics (Han et al. 2023, 2020) 



Based on TensorFlow and PyTorch. This one has the most additions, e.g. code to generate a TensorFlow TFRecord dataset from the raw netCDF data archived in the original paper, autoregressive training and experimental model architectures in PyTorch

See original paper for data access




Each of the code repos (unpack the tars) have an updated README.

References:






Chantry, M., Hatfield, S., Dueben, P., Polichtchouk, I., & Palmer, T. (2021). Machine learning emulation of gravity wave drag in numerical weather forecasting. Journal of Advances in Modeling Earth Systems, 13(7), e2021MS002477

 



Han, Y., Zhang, G. J., Huang, X., & Wang, Y. (2020). A moist physics parameterization based on deep learning. Journal of Advances in Modeling Earth Systems, 12(9), e2020MS002076.


 

Han, Y., Zhang, G. J., & Wang, Y. (2023). An ensemble of neural networks for moist physics processes, its generalizability and stable integration. Journal of Advances in Modeling Earth Systems, 15(10), e2022MS003508

 

Wang, P., Yuval, J., & O’Gorman, P. A. (2022). Non‐local parameterization of atmospheric subgrid processes with neural networks. Journal of Advances in Modeling Earth Systems, 14(10), e2022MS002984.
DOI: 10.5281/zenodo.10462471
title: Code and partial data for "Representing sub-grid processes in weather and climate models via sequence learning"

description: This repository contains the RNN training and evaluation code used in the paper for all three parameterization problems:



non-orographic gravity wave drag (NOGWD)

non-local parameterization (Wang et al. 2022)

moist physics (Han et al. 2023, 2022) 


Data is included only for the first one as the data for the others came from other studies which already archived the data.
DOI: 10.5281/zenodo.10527369
title: Code and partial data for "Representing sub-grid processes in weather and climate models via sequence learning"

description: This repository contains the RNN training and evaluation code used in the paper Representing sub-grid processes in weather and climate models via sequence learning. Three parameterization problems from earlier studies are included (we have modified the code from these papers to incorporate RNNs): 



non-orographic gravity wave drag (Chantry et al. 2021) 



Based on TensorFlow

This repository uses the CliMetLab plugin and downloads the data from the European Weather Cloud



non-local parameterization (Wang et al. 2022)



The new code is based on TensorFlow, so you'll need both PyTorch and TensorFlow to run everything

See original paper for data access



moist physics (Han et al. 2023, 2020) 



Based on TensorFlow. This one has the most additions, e.g. code to generate a TensorFlow TFRecord dataset from the raw netCDF data archived in the original paper

See original paper for data access




Each of the code repos (unpack the tars) have an updated README.

References:






Chantry, M., Hatfield, S., Dueben, P., Polichtchouk, I., & Palmer, T. (2021). Machine learning emulation of gravity wave drag in numerical weather forecasting. Journal of Advances in Modeling Earth Systems, 13(7), e2021MS002477

 



Han, Y., Zhang, G. J., Huang, X., & Wang, Y. (2020). A moist physics parameterization based on deep learning. Journal of Advances in Modeling Earth Systems, 12(9), e2020MS002076.


 

Han, Y., Zhang, G. J., & Wang, Y. (2023). An ensemble of neural networks for moist physics processes, its generalizability and stable integration. Journal of Advances in Modeling Earth Systems, 15(10), e2022MS003508

 

Wang, P., Yuval, J., & O’Gorman, P. A. (2022). Non‐local parameterization of atmospheric subgrid processes with neural networks. Journal of Advances in Modeling Earth Systems, 14(10), e2022MS002984.