cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/zef-z4n-dks
title: Nuphar × spenneriana Gaudin

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0026567.10fu
title: SH0026567.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/dmb-gqp-b70
title: Nuphar × spenneriana Gaudin

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/z21-wrk-ccn
title: Nuphar × spenneriana Gaudin

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0026568.10fu
title: SH0026568.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/em9-n43-g6c
title: Hippuris vulgaris L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/pgb-2ls-he4
title: Epilobium ciliatum subsp. ciliatum

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0026569.10fu
title: SH0026569.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/bab-w0l-f61
title: Epilobium ciliatum subsp. ciliatum

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/yl8-7r2-p3r
title: Hippuris vulgaris L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0026570.10fu
title: SH0026570.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/5l8-gld-jnl
title: Hippuris vulgaris L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/edt-9vm-lfp
title: Hippuris vulgaris L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0026571.10fu
title: SH0026571.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.14247304
title: Wetland Use Intensity Rwanda 2020

description: The Wetland Use Intensity (WUI) indicator, which is not specific to a particular crop and which requires little ancillary data, is based on the Mean Absolute Spectral Dynamics (MASD), which is a cumulative measure of reflectance change across a time series of optical satellite images. It is sensitive to the compound effects of land cover changes caused by different agricultural practices, flooding or burning. The more frequent and intrusive management practices are on the land cover, the stronger the WUI signal. WUI thus serves as a surrogate indicator to measure pressure on wetland ecosystems. We developed a new and automated approach for WUI calculation that is implemented in the Google Earth Engine (GEE) cloud computing environment. Its automatic calculation, use of regular Sentinel-2 surface reflectance derived time series, and automatic cloud and cloud shadow masking renders WUI applicable for wetland management and produces high quality results with minimal user requirements, even under cloudy conditions. The dataset provided is calculated from bi-monthly composites from July 2019 to June 2021 to form a pseudo-year 2020 and covers the East African country of Rwanda.

The GEE code is available in the supplementary materials of (please cite when using the dataset):

Steinbach, S., Hentschel, E., Hentze, K., Rienow, A., Umulisa, V., Zwart, S.J., Nelson, A., 2023. Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales. Ecological Informatics 75, 102032. https://doi.org/10.1016/j.ecoinf.2023.102032

The research was supported by the project Copernicus-based Detection and Monitoring of tropical Wetlands (DeMo-Wetlands), which was funded by the German Federal Ministry for Economic Affairs and Energy (grant no. 50EE1537).
DOI: 10.5281/zenodo.14247305
title: Wetland Use Intensity Rwanda 2020

description: The Wetland Use Intensity (WUI) indicator, which is not specific to a particular crop and which requires little ancillary data, is based on the Mean Absolute Spectral Dynamics (MASD), which is a cumulative measure of reflectance change across a time series of optical satellite images. It is sensitive to the compound effects of land cover changes caused by different agricultural practices, flooding or burning. The more frequent and intrusive management practices are on the land cover, the stronger the WUI signal. WUI thus serves as a surrogate indicator to measure pressure on wetland ecosystems. We developed a new and automated approach for WUI calculation that is implemented in the Google Earth Engine (GEE) cloud computing environment. Its automatic calculation, use of regular Sentinel-2 surface reflectance derived time series, and automatic cloud and cloud shadow masking renders WUI applicable for wetland management and produces high quality results with minimal user requirements, even under cloudy conditions. The dataset provided is calculated from bi-monthly composites from July 2019 to June 2021 to form a pseudo-year 2020 and covers the East African country of Rwanda.

The GEE code is available in the supplementary materials of (please cite when using the dataset):

Steinbach, S., Hentschel, E., Hentze, K., Rienow, A., Umulisa, V., Zwart, S.J., Nelson, A., 2023. Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales. Ecological Informatics 75, 102032. https://doi.org/10.1016/j.ecoinf.2023.102032

The research was supported by the project Copernicus-based Detection and Monitoring of tropical Wetlands (DeMo-Wetlands), which was funded by the German Federal Ministry for Economic Affairs and Energy (grant no. 50EE1537).
DOI: 10.15468/dl.2av8je
title: Occurrence Download

description: A dataset containing 445 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Russian Federation, Korea, Republic of, Netherlands, Korea (Democratic People’s Republic of), China)",
 "TaxonKey is Elaphe schrenckii Strauch, 1873"
 ]
}

 The dataset includes 445 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008546-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eswaqv
title: Occurrence Download

description: A dataset containing 8521 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ophiocordyceps Petch"
 ]
}

 The dataset includes 8521 records from 258 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008547-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xusm8b
title: Occurrence Download

description: A dataset containing 2062 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Uranoscopus scaber Linnaeus, 1758"
 ]
}

 The dataset includes 2062 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008548-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5ega8r
title: Occurrence Download

description: A dataset containing 653 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 {
 "or" : [
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "Geometry POLYGON((-77.7103 6.33765,-74.3882 6.33765,-74.3882 9.6271,-77.7103 9.6271,-77.7103 6.33765))"
 ]
 },
 "HasGeospatialIssue is false",
 "TaxonKey is Eichhornia crassipes (Mart.) Solms"
 ]
}

 The dataset includes 653 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008549-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j6zwku
title: Occurrence Download

description: A dataset containing 339 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Spain, Portugal)",
 "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 Castanea Mill.",
 "Year 2004-2024"
 ]
}

 The dataset includes 339 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008550-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10059806
title: Mahanagar Yatayat Transport Dataset
DOI: 10.15468/dl.fnnw28
title: Occurrence Download

description: A dataset containing 186 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Chrysolophus amherstiae (Leadbeater, 1829)",
 "Year 2023-2024"
 ]
}

 The dataset includes 186 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008551-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vkpgj5
title: Occurrence Download

description: A dataset containing 1548 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"2476643","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"BASIS_OF_RECORD","value":"PRESERVED SPECIMEN","matchCase":false},{"type":"equals","key":"CONTINENT","value":"southamerica","matchCase":false}]}

 The dataset includes 1548 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008552-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pkcqvp
title: Occurrence Download

description: A dataset containing 508 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Rasgos funcionales de plantas leñosas nativas y exóticas en áreas verdes de Bogotá, Colombia"
 ]
}

 The dataset includes 508 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008553-241126133413365/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.27934059
title: Supplementary Material

description: Extraction with forwarders: production, load and operating cycle, and cost data.
DOI: 10.6084/m9.figshare.27934059.v1
title: Supplementary Material

description: Extraction with forwarders: production, load and operating cycle, and cost data.
DOI: 10.15468/dl.q5epq7
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is one of (Spain, Portugal)",
 "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 Castanea Mill.",
 "Year 2004-2024"
 ]
}

 The dataset's 1 records were derived from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008554-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ck4aj8
title: Occurrence Download

description: A dataset containing 508 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Rasgos funcionales de plantas leñosas nativas y exóticas en áreas verdes de Bogotá, Colombia"
 ]
}

 The dataset includes 508 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008555-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3qy6cj
title: Occurrence Download

description: A dataset containing 1548 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"2476643","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"BASIS_OF_RECORD","value":"PRESERVED SPECIMEN","matchCase":false},{"type":"equals","key":"CONTINENT","value":"southamerica","matchCase":false}]}

 The dataset includes 1548 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008556-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgdddd
title: Occurrence Download

description: A dataset containing 21353 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xyrichtys novacula (Linnaeus, 1758)"
 ]
}

 The dataset includes 21353 records from 149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008559-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nn8gxt
title: Occurrence Download

description: A dataset containing 14149 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Zeus faber Linnaeus, 1758"
 ]
}

 The dataset includes 14149 records from 247 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008560-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7jjymp
title: Occurrence Download

description: A dataset containing 172605 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xiphias gladius Linnaeus, 1758"
 ]
}

 The dataset includes 172605 records from 185 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008557-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2xjfh
title: Occurrence Download

description: A dataset containing 1931 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Zeugopterus punctatus (Bloch, 1787)"
 ]
}

 The dataset includes 1931 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008561-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11179160
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-19

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2023-10-19. 

            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.

            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