cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2c7yjk
title: Occurrence Download

description: A dataset containing 956931 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sturnus vulgaris)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 956931 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008309-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/6921
title: OpenTextVault
DOI: 10.5281/zenodo.17557854
title: Recopilación de recetas de Karlos Arguiñano

description: El dataset contiene un registro por cada receta publicada de Karlos Arguiñano en la sección seleccionada del sitio web de Hogarmania.

Cada fila representa una receta única y fue recopilada mediante un proceso automatizado que combina las librerías de Python de Web Scraping: Selenium y BeautifulSoup.

Se extrajeron datos desde la página que explora todas las recetas de Karlos Arguiñano y entrando en la página detalle de cada una de ellas. En ellas se capturaron campos estructurados como el título, ingredientes, número de raciones, coste, dificultad, tiempos de preparación y cocinado, además de una descripción breve de cada elaboración limitada a 150 palabras.

El conjunto de datos resultante permite el uso actualizado de las últimas recetas publicadas y se pueden filtrar y ordenar por múltiples criterios:





Por tiempos y niveles de dificultad.




Análisis entre coste y complejidad.




Filtrado de ingredientes.
DOI: 10.5281/zenodo.17557853
title: Recopilación de recetas de Karlos Arguiñano

description: El dataset contiene un registro por cada receta publicada de Karlos Arguiñano en la sección seleccionada del sitio web de Hogarmania.

Cada fila representa una receta única y fue recopilada mediante un proceso automatizado que combina las librerías de Python de Web Scraping: Selenium y BeautifulSoup.

Se extrajeron datos desde la página que explora todas las recetas de Karlos Arguiñano y entrando en la página detalle de cada una de ellas. En ellas se capturaron campos estructurados como el título, ingredientes, número de raciones, coste, dificultad, tiempos de preparación y cocinado, además de una descripción breve de cada elaboración limitada a 150 palabras.

El conjunto de datos resultante permite el uso actualizado de las últimas recetas publicadas y se pueden filtrar y ordenar por múltiples criterios:





Por tiempos y niveles de dificultad.




Análisis entre coste y complejidad.




Filtrado de ingredientes.
DOI: 10.5281/zenodo.17556884
title: Dataset for breakdown of dynamic alignment and critical balance

description: Dataset for dynamic alignment, critical balance, ring spectra and a field profile
DOI: 10.5281/zenodo.17556885
title: Dataset for breakdown of dynamic alignment and critical balance

description: Dataset for dynamic alignment, critical balance, ring spectra and a field profile
DOI: 10.15468/dl.kzyjes
title: Occurrence Download

description: A dataset containing 31948 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anacamptis laxiflora",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 31948 records from 540 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022957-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xkh64e
title: Occurrence Download

description: A dataset containing 209904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Plantae",
 "BasisOfRecord is one of (Fossil, Material sample, Occurrence evidence)"
 ]
}

 The dataset includes 209904 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022955-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17557759
title: Underwater images collected by a Kite surf in Le-Morne-One-Eye-Manawa, Mauritius - 2019-05-30

description: This dataset was collected by a Kite surf in Le-Morne-One-Eye-Manawa, Mauritius - 2019-05-30. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.15468/dl.4u9htj
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anacamptis longicornu",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 166 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022959-251025141854904/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.30407830
title: <b>EM VS. WM</b>

description: <b>Müller Cell Senesce</b><b>nce</b><b> of EM VS. WM</b>
DOI: 10.6084/m9.figshare.30407830.v1
title: <b>EM VS. WM</b>

description: <b>Müller Cell Senesce</b><b>nce</b><b> of EM VS. WM</b>
DOI: 10.6084/m9.figshare.30407830.v2
title: <b>EM VS. WM</b>

description: <b>Müller Cell Senesce</b><b>nce</b><b> of EM VS. WM</b>
DOI: 10.15468/dl.kv6jb7
title: Occurrence Download

description: A dataset containing 5725 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anacamptis fragrans",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5725 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022960-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17557849
title: Asynchronous functional shifts in moss crusts under long-term nitrogen deposition
DOI: 10.5281/zenodo.17557850
title: Asynchronous functional shifts in moss crusts under long-term nitrogen deposition
DOI: 10.15468/dl.6gjse3
title: Occurrence Download

description: A dataset containing 3495 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Spodoptera frugiperda)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Year is greater than or equal to 1970",
 "Year is less than or equal to 2020"
 ]
}

 The dataset includes 3495 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022961-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ez6ftj
title: Occurrence Download

description: A dataset containing 72346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alysicarpus vaginalis, Chamaecrista mimosoides, Chamaecrista nictitans, Crotalaria incana, Crotalaria quinquefolia, Desmanthus pernambucanus, Desmodium heterophyllum, Grona, Senna surattensis, Pseuderanthemum carruthersii, Orthosiphon aristatus, Lindernia antipoda, Angelonia angustifolia, Pangium edule, Acalypha lanceolata, Euphorbia thymifolia, Phyllanthus debilis, Phyllanthus tenellus, Phyllanthus urinaria, Muntingia calabura)",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 72346 records from 304 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022958-251025141854904/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.28827383
title: <b>Microbial necromass contribution to topsoil organic carbon storage of natural and agricultural ecosystems</b>

description: Microbial necromass is an important component of soil carbon (C). Yet, the relative contribution of microbial necromass in shaping the global C stocks in agricultural and natural ecosystems worldwide remains virtually unknown. Here, we compiled data on fungal and bacterial necromass along with soil organic carbon (SOC) from the 0–20 cm soil layer across 486 study sites (145 agricultural and 341 natural ecosystems) to evaluate the relative contribution of fungal necromass C (FNC) and bacterial necromass C (BNC) to SOC. Our results indicated that, on average, FNC is two times more important than BNC in explaining SOC in both agricultural and natural ecosystems. The contributions of FNC and BNC to SOC were markedly higher in agricultural ecosystems compared with natural ecosystems, with a contrasting trend in the FNC/BNC ratio. Soil physicochemical properties (soil C/N ratio and clay content) were the most important predictors of the contributions of FNC and BNC to SOC in both ecosystems, while geographical factor (elevation) was the most important predictor of the FNC/BNC ratio. Our study enhances the current level of understanding regarding microbially mediated biogeochemical cycling and SOC dynamics, underscoring the critical role of microbial necromass in the global C cycle.
DOI: 10.6084/m9.figshare.28827383.v1
title: <b>Microbial necromass contribution to topsoil organic carbon storage of natural and agricultural ecosystems</b>

description: Microbial necromass is an important component of soil carbon (C). Yet, the relative contribution of microbial necromass in shaping the global C stocks in agricultural and natural ecosystems worldwide remains virtually unknown. Here, we compiled data on fungal and bacterial necromass along with soil organic carbon (SOC) from the 0–20 cm soil layer across 486 study sites (145 agricultural and 341 natural ecosystems) to evaluate the relative contribution of fungal necromass C (FNC) and bacterial necromass C (BNC) to SOC. Our results indicated that, on average, FNC is two times more important than BNC in explaining SOC in both agricultural and natural ecosystems. The contributions of FNC and BNC to SOC were markedly higher in agricultural ecosystems compared with natural ecosystems, with a contrasting trend in the FNC/BNC ratio. Soil physicochemical properties (soil C/N ratio and clay content) were the most important predictors of the contributions of FNC and BNC to SOC in both ecosystems, while geographical factor (elevation) was the most important predictor of the FNC/BNC ratio. Our study enhances the current level of understanding regarding microbially mediated biogeochemical cycling and SOC dynamics, underscoring the critical role of microbial necromass in the global C cycle.
DOI: 10.18112/openneuro.ds007436.v1.0.0
title: Multisensory learning dataset
DOI: 10.6084/m9.figshare.29664326
title: Data for "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"

description: Source data for the paper "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"
DOI: 10.6084/m9.figshare.29664326.v3
title: Data for "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"

description: Source data for the paper "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"
DOI: 10.6084/m9.figshare.29664326.v2
title: Data for "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"

description: Source data for the paper "<b>Motion aftereffects from viewing another’s gaze are restricted to the line of sight</b>"
DOI: 10.17630/f90f7396-85a4-40c0-a081-7df0e8990057
title: Ultrafast triggering of insulator-metal transition in two-dimensional VSe2 (dataset)
DOI: 10.15156/bio/sh1401654.10fu
title: SH1401654.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1401665.10fu
title: SH1401665.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1401671.10fu
title: SH1401671.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1401675.10fu
title: SH1401675.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1401678.10fu
title: SH1401678.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1401680.10fu
title: SH1401680.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.ygeh7t
title: Occurrence Download

description: A dataset containing 21128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Puma concolor",
 "Year 1996-2026"
 ]
}

 The dataset includes 21128 records from 323 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006138-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1401684.10fu
title: SH1401684.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.