cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11177205
title: Underwater images collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28. 

            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.11177399
title: Underwater images collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28. 

            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.11177400
title: Underwater images collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28. 

            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.11177488
title: Underwater images collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28. 

            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.11177487
title: Underwater images collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Cap-La-Houssaye, Réunion - 2023-06-28. 

            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: 10.15468/dl.wxcmrh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Primula scotica Hook.",
 "Geometry POLYGON((-4.47763888888889 56.7401388888889, -2.79986111111111 56.7401388888889, -2.79986111111111 57.4134722222222, -4.47763888888889 57.4134722222222, -4.47763888888889 56.7401388888889))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011059-250402121839773/datasets/export for details.
DOI: 10.15468/dl.362j5y
title: Occurrence Download

description: A dataset containing 14914303 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is South Africa",
 "DatasetKey is Southern African Bird Atlas Project 2",
 "Geometry POLYGON((-21.79103 -40.59188,73.79103 -40.59188,73.79103 -2.40812,-21.79103 -2.40812,-21.79103 -40.59188))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (CR, EN, VU, NT, LC, DD, NE)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 2012-2025"
 ]
}

 The dataset includes 14914303 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011049-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.avp7a4
title: Occurrence Download

description: A dataset containing 20309 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thalictrum simplex L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 20309 records from 276 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000863-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fttakg
title: Occurrence Download

description: A dataset containing 66102395 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((-21.55377 45.18223,-22.24533 -13.13973,66.96652 -14.75338,67.8886 43.56858,-21.55377 45.18223))",
 "License is CC-BY 4.0"
 ]
}

 The dataset includes 66102395 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000754-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5u7p8d
title: Occurrence Download

description: A dataset containing 369 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Euploea modesta Butler, 1866"
 ]
}

 The dataset includes 369 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000866-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mjc3vt
title: Occurrence Download

description: A dataset containing 94648 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "Geometry POLYGON((1.3 48,3.7 48,3.7 49.5,1.3 49.5,1.3 48))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hymenoptera"
 ]
}

 The dataset includes 94648 records from 836 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000865-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4n3x84
title: Occurrence Download

description: A dataset containing 765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Cethosia hypsea Doubleday"
 ]
}

 The dataset includes 765 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000854-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5uncnn
title: Occurrence Download

description: A dataset containing 123099 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Burundi"
 ]
}

 The dataset includes 123099 records from 366 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000796-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tuduyv
title: Occurrence Download

description: A dataset containing 87632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pyrola rotundifolia L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 87632 records from 490 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000860-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111143099
title: Telaga Batu or Sabokingking inscription, MNI D155

description: [Text Description:] Telaga Batu or Sabokingking inscription; snake hoods at top and outlet for liquid at bottom ❧ [Text or Publication Number Note:] MNI D155 ❧ [Medium:] Stone ❧ [Script Note:] Southern Brahmi ❧ [Physical Object Description:] Stela ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.r3uvnp
title: Occurrence Download

description: A dataset containing 23108597 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2000-2022"
 ]
}

 The dataset includes 23108597 records from 574 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091745-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc1sto1633025
title: InscriptiFact -- an image database of inscriptions and artifacts
DOI: 10.25549/inscriptifact-ouc111143058
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.15468/dl.xawdx6
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mycosphaerella tassiana (De Not.) Johanson",
 {
 "or" : [
 "Country is United States",
 "Country is Canada",
 "Continent is North America"
 ]
 }
 ]
}

 The dataset includes 180 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126715-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc1sto1632975
title: InscriptiFact -- an image database of inscriptions and artifacts
DOI: 10.25549/inscriptifact-ouc111143360
title: Telaga Batu or Sabokingking inscription, MNI D155

description: [Text Description:] Telaga Batu or Sabokingking inscription; snake hoods at top and outlet for liquid at bottom ❧ [Text or Publication Number Note:] MNI D155 ❧ [Medium:] Stone ❧ [Script Note:] Southern Brahmi ❧ [Physical Object Description:] Stela ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.b2ffz3
title: Occurrence Download

description: A dataset containing 318 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "GadmGid is ITA",
 "GadmGid is CHE"
 ]
 },
 "TaxonKey is Aristolochia lutea Desf."
 ]
}

 The dataset includes 318 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0184178-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111143371
title: Telaga Batu or Sabokingking inscription, MNI D155

description: [Text Description:] Telaga Batu or Sabokingking inscription; snake hoods at top and outlet for liquid at bottom ❧ [Text or Publication Number Note:] MNI D155 ❧ [Medium:] Stone ❧ [Script Note:] Southern Brahmi ❧ [Physical Object Description:] Stela ❧ [Physical Object Note:] Stone