cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.td7faz
title: Occurrence Download

description: A dataset containing 3498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-74.69949 41.36794,-74.88198 41.23084,-75.1221 40.99928,-75.03565 40.91949,-75.08368 40.82508,-75.20854 40.75963,-75.20854 40.63584,-75.09328 40.5775,-74.96842 40.39488,-74.28648 40.4826,-74.19043 40.62126,-74.04636 40.7014,-73.97913 40.80327,-73.89268 41.03551,-73.88308 41.13686,-73.95031 41.23084,-73.95031 41.30303,-74.69949 41.36794))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Odocoileus virginianus (Zimmermann, 1780)"
 ]
}

 The dataset includes 3498 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000037-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.drxtyv
title: Occurrence Download

description: A dataset containing 13063 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ziziphus jujuba Mill.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 13063 records from 212 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000027-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t272qn
title: Occurrence Download

description: A dataset containing 1575 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Wyethia amplexicaulis (Nutt.) Nutt.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1575 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000033-250226150154925/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.28485737
title: Array files from 697 and EOL-1 cell lines

description: We performed whole-genome sequencing (WGS) with nanopore sequencing (NS) for copy number variant (CNV) calling in the acute myeloid (eosinophilic) leukemia (EOL-1) and B-cell precursor acute lymphoblastic leukemia (697) cell lines. Genomic DNA libraries were prepared using a rapid library preparation protocol and sequenced on the MinION device (Oxford Nanopore Technologies). NS data were processed using Guppy for basecalling, lra for read alignment, and CuteSV and Sniffles2 for variant calling. Mean coverage depths were of 13.1X for EOL-1 and 11.4X for 697. Simultaneously, chromosomal microarray analysis and CNV validation were performed on the same samples using array technology. We demonstrate that WGS with nanopore technology enables the identification of the majority of structural copy number variations detected by the gold-standard array method.The raw signal intensity data (.cel files) from ThermoFisher CytoScan HD® array (ThermoFisher Scientific, California, USA) were converted to .cychp files. The .cychp files are compatible with Genotyping Console v4.0 and Chromosome Analysis Suite 4.0.0.385 software.
DOI: 10.15468/dl.5xjqux
title: Occurrence Download

description: A dataset listing the 55 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-74.0755 40.15731,-75.03237 38.78925,-73.64056 39.60662,-74.0755 40.15731))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Elasmobranchii"
 ]
}

 The dataset's 55 records were derived from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000017-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6nx8wu
title: Occurrence Download

description: A dataset containing 227 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Utricularia benjaminiana Oliv."
 ]
}

 The dataset includes 227 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000035-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h55cwg
title: Occurrence Download

description: A dataset containing 160 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gnaphalium stewartii C.B.Clarke ex Hook.fil."
 ]
}

 The dataset includes 160 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000039-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/cc7dhrv
title: CCDC 220557: Experimental Crystal Structure Determination

description: Related Article: R.L.Davidovich, A.V.Gerasimenko, V.B.Logvinova, S.-Z.Hu|2003|Zh.Neorg.Khim.|48|69|
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.eyuz3c
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lithocarpus erythrocarpus (Ridl.) A.Camus"
 ]
}

 The dataset includes 13 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000041-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brhuku
title: Occurrence Download

description: A dataset containing 7412 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xanthisma spinulosum (Pursh) D.R.Morgan & R.L.Hartm.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7412 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000031-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/j5nt-6sdg
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/m4ut-6r49
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/xped-qyyr
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/zajt-ujxv
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/5fg4-59ne
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/972m-tjc5
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/hfgp-5y34
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/ngpx-nq98
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/qpmf-9guv
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/se8y-4jbu
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/ssfj-uwr4
title: Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/z37d-nskq
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/ce7u-qh9f
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/e97d-fhch
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/fbf4-9259
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/kcuh-knx4
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/mgpv-gpta
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/mnex-r8pg
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/n6uv-vgvd
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/qmrg-kvtc
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/rgx2-hypx
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/s7st-j3eb
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/shek-b4vk
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/3azd-tkmv
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/3bt5-ebx6
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/8tk3-xfdq
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/btmv-4443
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/d543-tpbu
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/epbq-qwpm
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/esrr-h334
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/f5fd-hz9u
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/hb7c-7bvd
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/hr5f-p6aa
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/kkae-ggfv
title: Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/qtwn-f6bu
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/sc7r-dxmp
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/w9t7-qujf
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/wkye-fuev
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/wwz4-yy3f
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/yytm-ctsp
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.48597/z2uu-dfnf
title: Measurement of Ozone at Jungfraujoch

description: Measurement of Ozone at Jungfraujoch
DOI: 10.15468/dl.8a9674
title: Occurrence Download

description: A dataset containing 3983 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Withania somnifera (L.) Dunal",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3983 records from 126 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000032-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11176912
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27. 

            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.11177009
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27. 

            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.11177095
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-27. 

            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.sv854z
title: Occurrence Download

description: A dataset containing 3880 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thymelaea tartonraira (L.) All.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3880 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018503-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17882/96945
title: GOLDYS hydro-biological data : Pelagic seasonal dynamics of the Gulf of Lion (North-western Mediterranean) in 2022-2023

description: As plankton strongly relies on environmental conditions, its abundance, composition and dynamics often reflect short term and local scale environmental variability. However, in the Gulf of Lion (GoL, northern most part of the western Mediterranean basin), plankton dynamic is still poorly understood particularly regarding its seasonal variations. In addition, major anthropogenic forcing involving heavy fishing pressure in the area have given rise to numerous management plans aimed at protecting the GoL's exploited species, and led to a growing need for knowledge about the overall functioning of this complex ecosystem. A research project aimed at surveying the GoL demersal and pelagic seasonal dynamics (GOLDYS project, 2021-2023) was undertaken to attempt filling this knowledge gap (Jacob, Salvado et al., 2023).
DOI: 10.17882/80790
title: Lucky Strike segment (Mid-Atlantic Ridge) - WHOI Towcam seafloor photomosaic (Graviluck 2006 Cruise): ~1-cm resolution colour geotiffs from navigation-based photomosaics (UTM zone 25 projection)

description: Colour seafloor photomosaics along towed camera tracks crossing the axis of the Lucky Strike ridge segment (Mid Altantic Ridge).  Images were acquired with the WHOI TowCam system (https://www.whoi.edu/what-we-do/explore/underwater-vehicles/towed-vehicles/towcam/), during the Graviluck 2016 cruise.  Images are process for colour and illumination correction. Images are placed and photomosaiced based on USBL navigation of the TowCam, altitude, and orientation.  The datasets include geotiffs for each of the tracks. To be cited: cited: Gini et al. (submitted); Escartin et al. (2008; 2014).
DOI: 10.34740/kaggle/ds/6199288
title: 🇯🇵 Reddit r/Japan Subreddit Dataset
DOI: 10.15468/dl.tzrfzq
title: Occurrence Download

description: A dataset containing 148 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Portugal, Spain)",
 "Geometry POLYGON((-8.83397 41.06975,-8.37709 41.04242,-8.46592 43.12652,-9.14102 42.79105,-8.83397 41.06975))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fagus L.",
 "Year 2004-2024"
 ]
}

 The dataset includes 148 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008566-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.