cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11176400
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24. 

            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!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.5281/zenodo.11176545
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24. 

            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!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.5281/zenodo.11176764
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-24. 

            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!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.12770/6e24aa82-e451-4c70-a3da-f56e8b88a577
title: 16S rRNA metabarcoding characterization of microbial communities in sediments of the Black Sea for ABERS project, 2022.

description: 16S rRNA amplicon metabarcoding from samples of the GHASS2 cruise (Romanian sector of the Black Sea, september 2021). Samples originate from marine sediment gravity coring samples as well as submarine samples from microbial mats and microbial reefs.
DOI: 10.12770/aacbc240-13a6-4d89-ac3e-f49c466afe13
title: Bathymétrie - mer Noire, au large du delta du Danube (campagne GHASS2, 2021)

description: Bathymétrie de la zone de rupture de pente du plateau continental, au large du delta du Danube, en mer Noire, au pas de 15 mètres. Ce jeu de données est un Modèle Numérique de Terrain bathymétrique, issu de l'acquisition acoustique du sondeur multifaisceaux SB7111 (100 kHz) et SB7150 (12 kHz) du N/O Pourquoi Pas ?, lors de la campagne GHASS2, du 16 aout au 30 septembre 2021.
Description de la campagne : RIBOULOT Vincent, DUPRE Stéphanie, KER Stéphan, SULTAN Nabil (2021) GHASS2 cruise, RV Pourquoi pas ?, https://doi.org/10.17600/18001358
DOI: 10.17882/102536
title: Pore pressure and temperature data from the Black Sea collected using Ifremer piezometers (2021-2023)

description: The piezometer is designed to measure in-situ pore pressure relative to the hydrostatic pressure and temperature. For this dataset, in-situ excess pore pressure and temperature measurements were made using cable-deployed piezometers equipped with a sediment piercing lance of 60 mm diameter carrying differential pore pressure (pore pressure in excess of hydrostatic pressure or fluid excess pore pressure) and temperature sensors, ballasted with lead weights (up to 1000 kg). The piezometer pore pressure and temperature sensors have an accuracy of ±0.5 kPa and 0.05 °C, respectively.
DOI: 10.15468/dl.4wuev6
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Gnetum gnemon L.",
 "Year 2020-2025"
 ]
}

 The dataset includes 25 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000014-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4zad2j
title: Occurrence Download

description: A dataset containing 41827 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Halimeda J.V.F.Lamouroux, 1812"
 ]
}

 The dataset includes 41827 records from 266 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000013-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6082/uchicago.14637
title: NCES Teaching and Learning International Survey (TALIS)

description: The Teaching and Learning International Survey (TALIS) is a survey about teachers, teaching, and learning environments. Sponsored by the Organization for Economic Cooperation and Development (OECD), TALIS is composed of two questionnaires—one for teachers and one for their principals—that ask questions about their backgrounds, work environments, professional development, and beliefs and attitudes about teaching. TALIS is unique because it is the only comparative international education study that collects data on nationally representative samples of teachers. For the United States, TALIS provides key information on teachers and principals and how they and their working and learning environments compare internationally.
DOI: 10.15468/dl.44ssax
title: Occurrence Download

description: A dataset listing the 865 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (iNaturalist Research-grade Observations, Observation.org, Nature data from around the World)",
 "GadmGid is DEU.10.3_1",
 "TaxonKey is Tracheophyta",
 "Year 2020-2025"
 ]
}

 The dataset's 865 records were derived from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000001-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ph9vf3
title: Occurrence Download

description: A dataset containing 290 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gnomophalium pulvinatum (Delile) Greuter"
 ]
}

 The dataset includes 290 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000016-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tenp8h
title: Occurrence Download

description: A dataset containing 13066 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Museo Entomológico Francisco Luis Gallego UNAL-MED"
 ]
}

 The dataset includes 13066 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000015-250226150154925/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.27992171
title: Appendices - Philipp von Stosch: Collecting, Drawing, Studying and Publishing Engraved Gems

description: This book, published with two digital-only appendices, is designed to show and discuss another facet of Stosch that would argue with the dense mythology of a spy, hoarder and libertine clouding the true nature of his accomplishments as an antiquarian, collector, patron and scholar. This is possible due to discovery and study of a substantial part of Stosch’s, previously considered lost, enormous <i>Paper Museum of Gems</i>. The artists, including Pier Leone Ghezzi, Girolamo Odam, Bernard Picart, Antonio Maria Zanetti, Markus Tuscher, Theodorus Netscher, Georg Martin Preißler, Johann Justin Preißler and Johann Adam Schweickart, tirelessly worked in a studio organised by Stosch on the faithful documentation of vast numbers of engraved gems. Made for a variety of purposes, they expose Stosch’s crucial role in the creation and transfer of knowledge that contributed immensely to the transformation of eighteenth-century antiquarianism towards a more scholarly archaeological science.
DOI: 10.6084/m9.figshare.27992171.v1
title: Appendices - Philipp von Stosch: Collecting, Drawing, Studying and Publishing Engraved Gems

description: This book, published with two digital-only appendices, is designed to show and discuss another facet of Stosch that would argue with the dense mythology of a spy, hoarder and libertine clouding the true nature of his accomplishments as an antiquarian, collector, patron and scholar. This is possible due to discovery and study of a substantial part of Stosch’s, previously considered lost, enormous <i>Paper Museum of Gems</i>. The artists, including Pier Leone Ghezzi, Girolamo Odam, Bernard Picart, Antonio Maria Zanetti, Markus Tuscher, Theodorus Netscher, Georg Martin Preißler, Johann Justin Preißler and Johann Adam Schweickart, tirelessly worked in a studio organised by Stosch on the faithful documentation of vast numbers of engraved gems. Made for a variety of purposes, they expose Stosch’s crucial role in the creation and transfer of knowledge that contributed immensely to the transformation of eighteenth-century antiquarianism towards a more scholarly archaeological science.
DOI: 10.15468/dl.bn4vw8
title: Occurrence Download

description: A dataset containing 3042392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "Year is 2012",
 "Month is April"
 ]
}

 The dataset includes 3042392 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000010-250226125047203/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/26975
title: Chandra X-ray Observatory ObsId 26975

description: After a Mega-Flare: Surface Magnetic Fields, Particle Ejection and Disk Ionization
DOI: 10.15468/dl.nftm8x
title: Occurrence Download

description: A dataset containing 341916 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phyteuma L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 341916 records from 1043 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000002-250226125047203/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1052830.10fu
title: SH1052830.10FU

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/sh1052832.10fu
title: SH1052832.10FU

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/sh1052834.10fu
title: SH1052834.10FU

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/sh1052837.10fu
title: SH1052837.10FU

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/sh1052839.10fu
title: SH1052839.10FU

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.