cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xer6qn
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.12148 50.84532,14.49817 50.84532,14.49817 51.00362,14.12148 51.00362,14.12148 50.84532))",
 "HasGeospatialIssue is false",
 "Month is one of (February, January, April, March)",
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus merula",
 "Year 2022-2022"
 ]
}

 The dataset includes 19 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023285-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17560473
title: Underwater images collected by a Kite surf in Le-Morne-Manawa-Platin-Rouge, Mauritius - 2019-08-11

description: This dataset was collected by a Kite surf in Le-Morne-Manawa-Platin-Rouge, Mauritius - 2019-08-11. 

            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.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

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

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.5281/zenodo.17560702
title: Underwater images collected by a Kite surf in Le-Morne-Manawa-Platin-Rouge, Mauritius - 2019-08-11

description: This dataset was collected by a Kite surf in Le-Morne-Manawa-Platin-Rouge, Mauritius - 2019-08-11. 

            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.

            
                
                                       
                
                
 GPS information: 

                GPX file from Garmin watch.
            
                    
                

                
            

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

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

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.15216 50.85951,14.50021 50.85951,14.50021 50.98238,14.15216 50.98238,14.15216 50.85951))",
 "HasGeospatialIssue is false",
 "Month is one of (January, March, February, April, May, June)",
 "OccurrenceStatus is Present",
 "TaxonKey is Dendrocopos major",
 "Year 2022-2022"
 ]
}

 The dataset includes 19 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023286-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hs2ah2
title: Occurrence Download

description: A dataset containing 800 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material citation, Material sample, Specimen, Human Observation)",
 "Geometry POLYGON((-43.96404 -19.88301,-43.96415 -19.87954,-43.9644 -19.87922,-43.96468 -19.87855,-43.96467 -19.87795,-43.96417 -19.87639,-43.96491 -19.87546,-43.9662 -19.87476,-43.95874 -19.87028,-43.95748 -19.87074,-43.9572 -19.87009,-43.95572 -19.86952,-43.95904 -19.8608,-43.96158 -19.86009,-43.97022 -19.86304,-43.9687 -19.86714,-43.9691 -19.86831,-43.96997 -19.86907,-43.97179 -19.86944,-43.97379 -19.86417,-43.97605 -19.86464,-43.97609 -19.86625,-43.97596 -19.86786,-43.97616 -19.87026,-43.97638 -19.87074,-43.97678 -19.87317,-43.97687 -19.87526,-43.97702 -19.87491,-43.97711 -19.87746,-43.97717 -19.87969,-43.97726 -19.88125,-43.97778 -19.88266,-43.97778 -19.88345,-43.9775 -19.88496,-43.97691 -19.88528,-43.97684 -19.88556,-43.97698 -19.88672,-43.97746 -19.88903,-43.97781 -19.89127,-43.97728 -19.89236,-43.97425 -19.89071,-43.96404 -19.88301))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta"
 ]
}

 The dataset includes 800 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023287-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.md7dhk
title: Occurrence Download

description: A dataset containing 139 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.18915 50.84319,14.5315 50.84319,14.5315 50.97771,14.18915 50.97771,14.18915 50.84319))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus merula",
 "Year 2023-2025"
 ]
}

 The dataset includes 139 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023288-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gr96uh
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Centris trigonoides"
 ]
}

 The dataset includes 76 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023290-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2fdr4p
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.11669 50.86495,14.51439 50.86495,14.51439 50.99028,14.11669 50.99028,14.11669 50.86495))",
 "HasGeospatialIssue is false",
 "Month is one of (January, June, May, April, March, February)",
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus merula",
 "Year 2022-2022"
 ]
}

 The dataset includes 43 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023291-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17560842
title: Intrinsic alignment amplitude vs luminosity (KiDS-1000 bright red, n_s>2.5; Georgiou et al. 2025)

description: Dataset compiled by the echoIA Collaboration under the `aia-lum` schema.Contains intrinsic alignment amplitude measurements as a function of luminosityfor KiDS-1000 bright red subsample with a Sérsic index cut of n_s > 2.5, derived from Georgiou et al. (2025), "Intrinsic galaxy alignments in the KiDS-1000 bright sample: Dependence on colour, luminosity, morphology, and galaxy scale",A&A, 699, A252 (2025), https://doi.org/10.1051/0004-6361/202554134.Values were digitized and reformatted into a uniform tabular dataset with metadata for reuse inintrinsic alignment analyses.The echoIA Collaboration does not claim ownership of the original measurements; please citethe source publication(s) when using these data.
DOI: 10.5281/zenodo.17560841
title: Intrinsic alignment amplitude vs luminosity (KiDS-1000 bright red, n_s>2.5; Georgiou et al. 2025)

description: Dataset compiled by the echoIA Collaboration under the `aia-lum` schema.Contains intrinsic alignment amplitude measurements as a function of luminosityfor KiDS-1000 bright red subsample with a Sérsic index cut of n_s > 2.5, derived from Georgiou et al. (2025), "Intrinsic galaxy alignments in the KiDS-1000 bright sample: Dependence on colour, luminosity, morphology, and galaxy scale",A&A, 699, A252 (2025), https://doi.org/10.1051/0004-6361/202554134.Values were digitized and reformatted into a uniform tabular dataset with metadata for reuse inintrinsic alignment analyses.The echoIA Collaboration does not claim ownership of the original measurements; please citethe source publication(s) when using these data.
DOI: 10.15468/dl.6mxnvv
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.13044 50.84665,14.48124 50.84665,14.48124 50.99408,14.13044 50.99408,14.13044 50.84665))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dryocopus martius",
 "Year 2023-2025"
 ]
}

 The dataset includes 90 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023292-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17558836
title: Intrinsic alignment amplitude vs luminosity (KiDS-1000 bright red; Georgiou et al. 2025)

description: Dataset compiled by the echoIA Collaboration under the `aia-lum` schema.Contains intrinsic alignment amplitude measurements as a function of luminosityfor KiDS-1000 bright red sample, derived from Georgiou et al. (2025), "Intrinsic galaxy alignmentsin the KiDS-1000 bright sample: Dependence on colour, luminosity, morphology, and galaxy scale",A&A, 699, A252 (2025), https://doi.org/10.1051/0004-6361/202554134.Values were digitized and reformatted into a uniform tabular dataset with metadata for reuse inintrinsic alignment analyses.The echoIA Collaboration does not claim ownership of the original measurements; please citethe source publication(s) when using these data.
DOI: 10.5281/zenodo.17558837
title: Intrinsic alignment amplitude vs luminosity (KiDS-1000 bright red; Georgiou et al. 2025)

description: Dataset compiled by the echoIA Collaboration under the `aia-lum` schema.Contains intrinsic alignment amplitude measurements as a function of luminosityfor KiDS-1000 bright red sample, derived from Georgiou et al. (2025), "Intrinsic galaxy alignmentsin the KiDS-1000 bright sample: Dependence on colour, luminosity, morphology, and galaxy scale",A&A, 699, A252 (2025), https://doi.org/10.1051/0004-6361/202554134.Values were digitized and reformatted into a uniform tabular dataset with metadata for reuse inintrinsic alignment analyses.The echoIA Collaboration does not claim ownership of the original measurements; please citethe source publication(s) when using these data.
DOI: 10.5281/zenodo.17228225
title: Supplementary Data and Supplementary Code - Westerly wind shifts drove Southern Hemisphere mid-latitude peat growth since the last glacial, Thomas et al. 2025

description: Supplementary Data and Supplementary Code from Westerly wind shifts drove Southern Hemisphere mid-latitude peat growth since the last glacial, Thomas et al. 2025, doi:10.1038/s41561-025-01842-w

Supplementary Data tab 1. New 14C agesNew basal radiocarbon ages from peatlands across the Falkland Islands.

Supplementary Data tab 2. ALL basal agesThis tab includes a dataset of all peat basal ages from the Southern Hemisphere extratropics.Dataset is searchable (e.g. by sector, by latitude, by age, etc).Dataset is sorted by region (South Atlantic / southern Indian / SW Pacific).

Supplementary Data tab 3. Basal ages no duplicatesThis tab includes a dataset of all peat basal ages from the Southern Hemisphere extratropics, but excludes 30 dates that were considered to be duplicates.Dataset is searchable (e.g. by sector, by latitude, by age, etc).Dataset is sorted by region (South America / South Atlantic / South Indian / South Pacific).

Supplementary Data tab 4. Basal ages by latitude (no duplicates)This tab includes a dataset of all peat basal ages from the Southern Hemisphere extratropics, but excludes 30 dates that were considered to be duplicates, sorted by latitude.Dataset is searchable (e.g. by sector, by latitude, by age, etc).

Supplementary Data tab 5. KDE BY REGIONThis tab includes the KDE of the dataset (no duplicates) divided into regions (South Atlantic / South Indian / South Pacific). 

Supplementary Data tab 6. KDE BY LATITUDEThis tab includes the KDE of the dataset (no duplicates) divided into latitudinal bands.

Supplementary Code - OxCal code for Kernel Density Estimate (KDE) models.
DOI: 10.15468/dl.yawtrs
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Paratenuisentis ambiguus, Neodexiospira pseudocorrugata, Neodexiospira steueri)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 102 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023293-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kyfpm2
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Novafabricia infratorquata, Novafabricia posidoniae, Paralaeospira malardi)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 60 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023294-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17555684
title: Intrinsic alignment amplitude vs luminosity (SDSS-III BOSS LOWZ; Singh et al. 2015)

description: Dataset compiled by the echoIA Collaboration under the aia-lum schema.Contains intrinsic alignment amplitude measurements as a function of luminosity forSDSS-III BOSS LOWZ sample, derived from Singh et al. (2015), "Intrinsic alignments ofSDSS-III BOSS LOWZ sample galaxies", MNRAS, Vol 450, Issue 2, https://doi.org/10.1093/mnras/stv778.Values were digitized and reformatted into a uniform tabular dataset with metadata for reuse inintrinsic alignment analyses.The echoIA Collaboration does not claim ownership of the original measurements; please citethe source publication(s) when using these data.
DOI: 10.15468/dl.qmt25t
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amaranthus hybridus",
 "Country is Burundi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009492-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/0ac-7yj-mby
title: Sequoiadendron giganteum (Lindl.) J.Buchholz

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.15468/dl.3tt3gy
title: Occurrence Download

description: A dataset containing 258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-127.08 59.12,-84.39 59.12,-84.39 70.13,-127.08 70.13,-127.08 59.12))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Ochrophyta"
 ]
}

 The dataset includes 258 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009493-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e268cv
title: Occurrence Download

description: A dataset containing 14452 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Lithobates berlandieri)"
 ]
}

 The dataset includes 14452 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009495-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sybhjc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lacerta bilineata",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009494-250717081556266/datasets/export for details.
DOI: 10.15468/dl.tnpmnk
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alyssum wierzbickii"
 ]
}

 The dataset includes 130 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009496-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4q2k68
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pimelodus bufonius"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009498-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pc72ug
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amaranthus hybridus",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 21 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009497-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15238074
title: Coarse-Grained Molecular Dynamics Simulations of SARS-CoV-2 E Protein embedded in homogeneous saturated model membranes

description: Coarse-grained MD simulations of the SARS-CoV-2 E protein (PDB ID: 5X29) embedded in homogeneous mono-unsaturated model membranes of varying equilibrium thickness. Lipids with 2, 3, 4, 5, or 6 beads per acyl chain were used (Martini lipids DTPC, DLPC, DPPC, DBPC, and DXPC).

All simulations were performed using GROMACS 2016 and the Martini 2.2 force field. The Berendsen thermostat was set to 313 K and a semi-isotropic Berendsen barostat was set to 1 bar in both directions. The compressibility modulus in both dimensions was 3 × 10−5 bar−1 with time constant 3 ps. Electrostatics and van der Waals (vdW) were shifted with a cutoff r-value of 1.2 nm. All systems underwent 100,000 steps of steepest-descent energy minimization prior to MD simulation with a timestep of 0.025 ps.

Protein backbone beads were restrained with an elastic network which bonded all backbone bead pairs within 1.4 nm of one another with force constants of 5,000 kJ mol−1 nm−1. Five replicas of each system were simulated in the NPT ensemble for 10 μs. We discarded the first half of each trajectory prior to analysis. To determine the bulk leaflet thickness t0, we performed separate 2 μs NPT simulations of membranes composed of each lipid species listed above, but without a protein embedded. We discarded the first half of each trajectory prior to analysis.

Analysis performed using nougat. Figures and figure generation script included.