cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.avu4se
title: Occurrence Download

description: A dataset containing 4657 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Museum of Comparative Zoology, Harvard University, Vertebrate Zoology Division - Herpetology, Yale Peabody Museum, Georgia Southern University - Savannah Science Museum Herpetology Collection, NCSM Herpetology Collection, CM Herps Collection, MVZ Herp Collection (Arctos), University of Florida Herpetology, NatureServe Network Species Occurrence Data, Biodiversity Research and Teaching Collections - TCWC Vertebrates)",
 "TaxonKey is Malaclemys terrapin (Schoepff, 1793)",
 "Year 1993-2023"
 ]
}

 The dataset includes 4657 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013570-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kxr4nd
title: Occurrence Download

description: A dataset containing 40109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "Geometry POLYGON((-8.4 39.9,-8 39.9,-8 40.3,-8.4 40.3,-8.4 39.9))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae",
 "Year 2010-2024"
 ]
}

 The dataset includes 40109 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009289-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-3363
title: Primiritel' = [Reconciler], vol. 8, no. 4-5 (April-May 1936)

description: [description english/roman)] 12 issues per year; For a history of Reconciler, see https://cdm15799.contentdm.oclc.org/cdm/compoundobject/collection/p15799coll14/id/2561/rec/12
DOI: 10.15468/dl.aannqw
title: Occurrence Download

description: A dataset containing 193492 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Cephalaspidomorphi"
 ]
}

 The dataset includes 193492 records from 275 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0435761-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6e89za
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 30ff48bd-4dd1-429d-a5a5-348c8e5fbfb1",
 "TaxonKey is Diphaulaca aulica (Olivier, 1808)"
 ]
}

 The dataset includes 70 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011048-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfpnjn
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011050-250402121839773/datasets/export for details.
DOI: 10.5281/zenodo.11172211
title: Underwater images collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-01-31

description: This dataset was collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-01-31. 

            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.11172275
title: Underwater images collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-02-03

description: This dataset was collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-02-03. 

            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.11172470
title: Underwater images collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-02-03

description: This dataset was collected by an Autonomous Surface Vehicle in Grandfond, Réunion - 2023-02-03. 

            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: 10.6084/m9.figshare.28493156
title: Macro plant remains from N4 Collooney to Castlebaldwin

description: Dataset containing information about identified plant remains from sites excavated along the route of the N4 Collooney to Castlebalwdin road. Including sites at Carrownagark (https://excavations.ie/report/2017/Sligo/0029031/) and Ardloy and Springfield (https://excavations.ie/report/2017/Sligo/0029056/).
DOI: 10.15468/dl.mm38rt
title: Occurrence Download

description: A dataset containing 97386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chlorophyta",
 "Year 2021-2024"
 ]
}

 The dataset includes 97386 records from 225 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000756-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tszzqr
title: Occurrence Download

description: A dataset containing 729 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Abutilon palmeri A.Gray",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 729 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000760-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pzwx49
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "StateProvince is 内蒙古",
 "TaxonKey is Acer ginnala Maxim."
 ]
}

 The dataset includes 20 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000757-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dyd7dc
title: Occurrence Download

description: A dataset containing 789 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Moscow University Herbarium (MW)",
 "TaxonKey is Prangos Lindl."
 ]
}

 The dataset includes 789 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000758-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wc8nh7
title: Occurrence Download

description: A dataset containing 128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acaena splendens Hook. & Arn.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 128 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000761-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kjzpfq
title: Occurrence Download

description: A dataset containing 6670 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eurema blanda (Boisduval, 1836)"
 ]
}

 The dataset includes 6670 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000762-250225214225278/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.28398295
title: The complete chloroplast genome sequence of <i>Camellia sinensis</i> var. <i>sinensis</i> cultivar “Yuexiangzao”

description: <i>Camellia sinensis</i> var. <i>sinensis</i> cultivar “Yuexiangzao” (YXZ) was a new tea cultivar in China. In this study, we reported a complete chloroplast (CP) genome based on the DNGSEQ sequencing technology. The CP genome sequence of YXZ was 157,041 bp in length and contained a large single copy (LSC, 86,594 bp), a small single copy (SSC, 18,291 bp), and two inverted repeats (IRs, 26,078 bp). The GC contents of LSC, SSC, and two IRs were 35.31%, 30.53%, and 42.94%, respectively. The phylogenetic analysis showed that YXZ was closely related to <i>C. sinensis</i> cv. “Tieluohan” and <i>C. sinensis</i> cv. “Xinyang 10.”
DOI: 10.6084/m9.figshare.28398295.v1
title: The complete chloroplast genome sequence of <i>Camellia sinensis</i> var. <i>sinensis</i> cultivar “Yuexiangzao”

description: <i>Camellia sinensis</i> var. <i>sinensis</i> cultivar “Yuexiangzao” (YXZ) was a new tea cultivar in China. In this study, we reported a complete chloroplast (CP) genome based on the DNGSEQ sequencing technology. The CP genome sequence of YXZ was 157,041 bp in length and contained a large single copy (LSC, 86,594 bp), a small single copy (SSC, 18,291 bp), and two inverted repeats (IRs, 26,078 bp). The GC contents of LSC, SSC, and two IRs were 35.31%, 30.53%, and 42.94%, respectively. The phylogenetic analysis showed that YXZ was closely related to <i>C. sinensis</i> cv. “Tieluohan” and <i>C. sinensis</i> cv. “Xinyang 10.”
DOI: 10.6084/m9.figshare.28332418
title: The complete chloroplast genome and phylogenetic analysis of <i>Emilia prenanthoidea</i> (Asteraceae)

description: <i>Emilia prenanthoidea</i> (<i>Emilia prenanthoidea</i> DC. Prodr. (DC.), 1838) belongs to the Asteraceae family and is a popular Miao medicinal plant in Guizhou, China. It has anti-inflammatory and antitumor properties. It is often used as a medication for healing injury, clearing heat and detoxifying, boosting blood circulation and eliminating blood stasis, and lowering inflammation and diuresis. This is the first reported study on the complete chloroplast genome of <i>E. prenanthoidea</i>. The <i>E. prenanthoidea</i> chloroplast genome is 151, 406 bp long, contains a pair of inverted repeats (IRs 24,705 bp), and is separated into a large single-copy (84,010 bp) and a short single-copy (17,986 bp) region. One hundred thirty genes were predicted, including 85 protein-coding genes, 37 tRNA genes, and eight rRNA genes. Nine protein-coding genes (<i>rps</i>16, <i>rpo</i>C1, <i>atp</i>F, <i>pet</i>B, <i>pet</i>D, <i>rpl</i>16, <i>rpl</i>2, <i>ndh</i>B, <i>ndh</i>A) had a single intron, two protein-coding genes (<i>ycf</i>3, <i>clp</i>P) had two, and the remainder had none. The phylogenetic analysis found <i>Emilia prenanthoidea</i> and <i>Emilia sonchifolia</i> clustered on a single branch, with <i>Pericallis hybrida</i> as its sister group. This study enhances our understanding of the evolutionary relationships within the Asteraceae family and provides valuable insights for developing germplasm-specific molecular markers.
DOI: 10.6084/m9.figshare.28332418.v1
title: The complete chloroplast genome and phylogenetic analysis of <i>Emilia prenanthoidea</i> (Asteraceae)

description: <i>Emilia prenanthoidea</i> (<i>Emilia prenanthoidea</i> DC. Prodr. (DC.), 1838) belongs to the Asteraceae family and is a popular Miao medicinal plant in Guizhou, China. It has anti-inflammatory and antitumor properties. It is often used as a medication for healing injury, clearing heat and detoxifying, boosting blood circulation and eliminating blood stasis, and lowering inflammation and diuresis. This is the first reported study on the complete chloroplast genome of <i>E. prenanthoidea</i>. The <i>E. prenanthoidea</i> chloroplast genome is 151, 406 bp long, contains a pair of inverted repeats (IRs 24,705 bp), and is separated into a large single-copy (84,010 bp) and a short single-copy (17,986 bp) region. One hundred thirty genes were predicted, including 85 protein-coding genes, 37 tRNA genes, and eight rRNA genes. Nine protein-coding genes (<i>rps</i>16, <i>rpo</i>C1, <i>atp</i>F, <i>pet</i>B, <i>pet</i>D, <i>rpl</i>16, <i>rpl</i>2, <i>ndh</i>B, <i>ndh</i>A) had a single intron, two protein-coding genes (<i>ycf</i>3, <i>clp</i>P) had two, and the remainder had none. The phylogenetic analysis found <i>Emilia prenanthoidea</i> and <i>Emilia sonchifolia</i> clustered on a single branch, with <i>Pericallis hybrida</i> as its sister group. This study enhances our understanding of the evolutionary relationships within the Asteraceae family and provides valuable insights for developing germplasm-specific molecular markers.
DOI: 10.6084/m9.figshare.28368450
title: Two complete chloroplast genomes of <i>Ceratophyllum</i>, an aquatic genus with unresolved phylogenetic position

description: <i>Ceratophyllum</i> is an aquatic genus noted for its enigmatic position in the angiosperm phylogenetic tree. In this study, we assembled and annotated the chloroplast genomes of two species. The chloroplast genome length of <i>Ceratophyllum platyacanthum</i> subsp. <i>oryzetorum</i> (Kom.) (V.Komarov, 1988) and <i>Ceratophyllum submersum</i> L. (Carl Linnaeus, 1763) is 156,168 bp and 156,554 bp, respectively. The chloroplast genomes of <i>Ceratophyllum</i> encode 113 unique genes, including 79 protein-coding genes, four rRNA genes, and 30 tRNA genes. The assembly of these two chloroplast genomes not only contributes to our understanding of the genome of <i>Ceratophyllum</i> but also provides valuable insights for the evolutionary study of angiosperms.
DOI: 10.6084/m9.figshare.28368450.v1
title: Two complete chloroplast genomes of <i>Ceratophyllum</i>, an aquatic genus with unresolved phylogenetic position

description: <i>Ceratophyllum</i> is an aquatic genus noted for its enigmatic position in the angiosperm phylogenetic tree. In this study, we assembled and annotated the chloroplast genomes of two species. The chloroplast genome length of <i>Ceratophyllum platyacanthum</i> subsp. <i>oryzetorum</i> (Kom.) (V.Komarov, 1988) and <i>Ceratophyllum submersum</i> L. (Carl Linnaeus, 1763) is 156,168 bp and 156,554 bp, respectively. The chloroplast genomes of <i>Ceratophyllum</i> encode 113 unique genes, including 79 protein-coding genes, four rRNA genes, and 30 tRNA genes. The assembly of these two chloroplast genomes not only contributes to our understanding of the genome of <i>Ceratophyllum</i> but also provides valuable insights for the evolutionary study of angiosperms.
DOI: 10.6084/m9.figshare.28450870
title: The complete mitochondrial genome of a rarely reported porcelain crab, <i>Pisidia striata</i> (Anomura, Galatheoidea, Porcellanidae), from the Chinese waters

description: The species <i>Pisidia striata</i> is predominantly distributed along the southeastern coast of China and belongs to the shallow-water crab family Porcellanidae. The complete mitochondrial genome of <i>P. striata</i>, which spans 15,357 bp and contains 13 protein-coding genes, 22 tRNAs and 2 rRNAs, is presented in this study. The nucleotide composition reveals A (37.81%), T (35.48%), G (9.75%), and C (16.96%). Phylogenetic analysis demonstrates a close relationship between <i>P. striata</i> and <i>P. serratifrons</i> within the <i>Pisidia</i> clade with robust bootstrap support values. This mitochondrial genome will be a significant supplement for the genus <i>Pisidia</i> and whole mitogenome phylogenetic analysis provided insights into further evolutionary research of Porcellanidae.