cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.9ag9e7
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Occurrence evidence)",
 "Geometry POLYGON((-5.6 37.8,-0.6 37.8,-0.6 41.5,-5.6 41.5,-5.6 37.8))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Geodetic datum assumed WGS84",
 "OccurrenceStatus is Present",
 "TaxonKey is Testudines",
 "Year 2007-2018"
 ]
}

 The dataset includes 165 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041223-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44tfva
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Kylix alcyone (Dall, 1919)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089952-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2hgqzp
title: CCDC 2308073: Experimental Crystal Structure Determination

description: Related Article: Yuhang Wang, Peng Ma, Jianhui Wang|2024|Org.Lett.|26|3164|doi:10.1021/acs.orglett.4c00751
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hgr0r
title: CCDC 2308074: Experimental Crystal Structure Determination

description: Related Article: Yuhang Wang, Peng Ma, Jianhui Wang|2024|Org.Lett.|26|3164|doi:10.1021/acs.orglett.4c00751
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.8wkwj7
title: Occurrence Download

description: A dataset containing 114 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arabidella procumbens (Tate) E.A.Shaw"
 ]
}

 The dataset includes 114 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041225-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3tq9ug
title: Occurrence Download

description: A dataset containing 356 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ficus pyriformis Hook. & Arn."
 ]
}

 The dataset includes 356 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0173397-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q69c48
title: Occurrence Download

description: A dataset containing 528 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eucalyptus diversicolor F.Muell."
 ]
}

 The dataset includes 528 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041229-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11408981
title: Underwater images collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19

description: This dataset was collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.5281/zenodo.11408982
title: Underwater images collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19

description: This version is considered deprecated, please refer to the latest version of this deposit.
DOI: 10.5281/zenodo.12773282
title: Underwater images collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19

description: This version is considered deprecated, please refer to the latest version of this deposit.
DOI: 10.5281/zenodo.13171424
title: Underwater images collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19

description: This dataset was collected by  Scuba diving in St-Gilles, Réunion - 2015-06-19. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.15468/dl.vdmqpg
title: Occurrence Download

description: A dataset containing 8554 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Astragalus L.",
 "Geometry POLYGON((-105 34, -94 34, -94 43, -105 43, -105 34))"
 ]
}

 The dataset includes 8554 records from 83 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017499-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11409002
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-08-07

description: This dataset was collected by  Scuba diving in La-Saline, Réunion - 2015-08-07. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.5281/zenodo.11409003
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-08-07

description: This version is considered deprecated, please refer to the latest version of this deposit.
DOI: 10.5281/zenodo.12773285
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-08-07

description: This version is considered deprecated, please refer to the latest version of this deposit.
DOI: 10.5281/zenodo.13171493
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-08-07

description: This dataset was collected by  Scuba diving in La-Saline, Réunion - 2015-08-07. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.5281/zenodo.11409015
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-09-25

description: This dataset was collected by  Scuba diving in La-Saline, Réunion - 2015-09-25. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.5281/zenodo.13171585
title: Underwater images collected by  Scuba diving in La-Saline, Réunion - 2015-09-25

description: This dataset was collected by  Scuba diving in La-Saline, Réunion - 2015-09-25. 

            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.


            Underwater Images Collected by Scuba Diving in Réunion Island during the Hyscores Project. 
            For more details, visit the Hyscores Project.


            
 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: Internal fund by IFREMER.
DOI: 10.15468/dl.g427x7
title: Occurrence Download

description: A dataset containing 3464 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Centre for Biodiversity Genomics (BIOUG) - Marine Invertebrates"
 ]
}

 The dataset includes 3464 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017501-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k7y3rq
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Craspedacusta Lankester, 1880"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017502-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.