cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10943282
title: Experimental data for "An End-to-End Coding Scheme for DNA-Based Data Storage With Nanopore Sequenced Reads"

description: The experimental dataset used in "An End-to-End Coding Scheme for DNA-Based Data Storage With Nanopore Sequenced Reads."

A set of 91,766 150-nt oligos were synthesised with GenScript (oligos.fasta). Each oligo consists of a pseudo-random 110-nt payload flanked by 20-nt primers at each end. The strands are split in three roughly equal groups (two groups of 30,589 and one group of 30,588). Each group has a dedicated primer pair for targeted PCR amplification (the primer pairs used for amplification are provided in primers_synthesis.fasta). The pseudo-random payload was designed to avoid primer-payload collisions.

For each file, a sample from the synthesised pool was PCR amplified using the corresponding primer pair and sequenced using Oxford Nanopore Technologies MinION sequencing device following the standard library preparation protocol for amplicon DNA. The raw reads were basecalled using guppy, either in fast- ("acc-false") or high-accuracy ("acc-true") regime. The basecaller generated two groups of reads—"passQ-true" for the reads that passed the quality-score threshold of 8 and "passQ-false" for those that did not. For each group of reads, a BLAST-based fuzzy search for primer sequences was performed and, based on the resulting alignments, the segments containing the correct primer pairs and located at a distance of 150+-15nt were extracted (separately for forward and reverse-complemented reads). The segments are then assigned to the closest synthesized strand based on Levenshtein distance. The resulting clusters are used to estimate the parameters of the end-to-end DNA storage channel model and to test the proposed error-correction scheme.

The archive clustered_read_segments.tar.gz contains 12 sub-archives, for each file (0,1,2), accuracy ("acc-true" or "acc-false"), and Q-score ("passQ-true" or "passQ-false"). Within each sub-archive, there are two folders (one for forward read segments and one for backward read segments), and each folder contains two files: one for the reference synthesised (or "transmitted") sequences that correspond to the file in question ("TX__" — e.g., "TX__file=0_accBaCa=true_passQ=true_filter=true_forward_.txt") and another file for the sequenced (or "received") segment clusters ("RX__" — e.g., "RX__file=0_accBaCa=true_passQ=true_filter=true_forward_.txt"). The received clusters in the "RX__" file are ordered in correspondence with the synthesised sequences in the "TX__" file, and a line "===============================" is used as a separator.
DOI: 10.15468/dl.qwsrzj
title: Occurrence Download

description: A dataset containing 60333 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is UTA Reptiles"
 ]
}

 The dataset includes 60333 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011870-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ky2e3
title: Occurrence Download

description: A dataset containing 277452 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((2.479608666666667 32.097476, 2.479608666666667 49.184106666666665, -31.565747 49.184106666666665, -31.565747 32.097476, 2.479608666666667 32.097476))",
 "EventDate is 2010-08-01,2010-08-31"
 ]
}

 The dataset includes 277452 records from 547 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057285-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11408993
title: Underwater images collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17

description: This dataset was collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17. 

            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.11409287
title: Underwater images collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17

description: This dataset was collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17. 

            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.11409559
title: Underwater images collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17

description: This dataset was collected by an Autonomous Surface Vehicle in Trou-Deau, Réunion - 2024-05-17. 

            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.11300766
title: Detection history of 175 adult Plain-crested Elaenia (Elaenia cristata) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.

description: The input file for analysing the detection history of 175 adult Plain-crested Elaenia (Elaenia cristata) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.
DOI: 10.5281/zenodo.11300767
title: Detection history of 175 adult Plain-crested Elaenia (Elaenia cristata) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.

description: The input file for analysing the detection history of 175 adult Plain-crested Elaenia (Elaenia cristata) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.
DOI: 10.15468/dl.fnqebt
title: Occurrence Download

description: A dataset containing 22898 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 {
 "or" : [
 "Country is Romania",
 "Country is Poland",
 "Country is Slovakia",
 "Country is Sweden",
 "Country is Germany",
 "Country is Finland",
 "Country is France",
 "Country is Norway",
 "Country is Estonia",
 "Country is Czechia"
 ]
 },
 "Year 1000-2019",
 "HasCoordinate is true",
 "TaxonKey is Lynx lynx (Linnaeus, 1758)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 22898 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015020-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x8bdx9
title: Occurrence Download

description: A dataset containing 974 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Sorghum bicolor (L.) Moench"
 ]
}

 The dataset includes 974 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091321-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ey5tr5
title: Occurrence Download

description: A dataset containing 611361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-91.513 36.97,-87.495 36.97,-87.495 42.508,-91.513 42.508,-91.513 36.97))",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1965-2024"
 ]
}

 The dataset includes 611361 records from 235 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066265-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9lvlbj
title: Occurrence Download

description: A dataset containing 564 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aphanius dispar (Rüppell, 1829)"
 ]
}

 The dataset includes 564 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006122-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fehxz7
title: Occurrence Download

description: A dataset containing 1318696 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Pandion haliaetus (Linnaeus, 1758)",
 "Year 2016-2020"
 ]
}

 The dataset includes 1318696 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0100575-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z2f9cx
title: Occurrence Download

description: A dataset containing 4050 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 8.25584103701234",
 "DecimalLongitude is less than 8.25890059019673",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 4050 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007089-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mdfmbt
title: Occurrence Download

description: A dataset containing 1690 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is South Africa",
 "Year 2017-2018",
 "TaxonKey is Delichon urbicum (Linnaeus, 1758)"
 ]
}

 The dataset includes 1690 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006115-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yxgvkc
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aneilema aparine H.Perrier"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007078-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hec3yu
title: Occurrence Download

description: A dataset containing 1191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ambystoma velasci Dugès, 1888"
 ]
}

 The dataset includes 1191 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127452-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9yq6pw
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidium rhytidocarpum (Hook.) Al-Shehbaz"
 ]
}

 The dataset includes 20 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040917-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nc3pfv
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parhippolyte sterreri (C.W.J.Hart & Manning, 1981)"
 ]
}

 The dataset includes 31 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066269-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7rvadc
title: Occurrence Download

description: A dataset containing 35192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "PublishingCountry is Chile",
 {
 "or" : [
 "TaxonKey is Cryptocarya alba (Molina) Looser",
 "TaxonKey is Plantae"
 ]
 }
 ]
}

 The dataset includes 35192 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127456-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.0cslsv
title: Occurrence Download

description: A dataset containing 4246 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Diversidad de peces de las lagunas costeras de Pueblo Viejo y el Mango, Veracruz"
 ]
}

 The dataset includes 4246 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024255-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebp9ed
title: Occurrence Download

description: A dataset containing 1335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phyllaphis fagi (Linnaeus, 1761))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1335 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042073-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nwucyu
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Beilschmiedia troupinii R.Wilczek"
 ]
}

 The dataset includes 25 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052358-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.77rpnc
title: Occurrence Download

description: A dataset containing 22034 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Liquidambar styraciflua L.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22034 records from 196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0141492-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uo79hi
title: Occurrence Download

description: A dataset containing 4009 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nestor notabilis Gould, 1856"
 ]
}

 The dataset includes 4009 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024258-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3mum4r
title: Occurrence Download

description: A dataset listing the 11 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.28383 2.90505,-75.09864 2.90505,-75.09864 3.06703,-75.28383 3.06703,-75.28383 2.90505))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chiroptera"
 ]
}

 The dataset's 11 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066264-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qqd4tx
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Valipora campylancristrota (Wedl, 1855))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 26 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042074-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.