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

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Heptapleurum fengii (C.J.Tseng & G.Hoo) Lowry & G.M.Plunkett"
 ]
}

 The dataset includes 45 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017854-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.63ubyp
title: Occurrence Download

description: A dataset containing 521 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Pseudophilautus wynaadensis (Jerdon, 1853)",
 "Year 1000-2023"
 ]
}

 The dataset includes 521 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028814-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gbxw99
title: Occurrence Download

description: A dataset containing 92018 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hesperis matronalis L."
 ]
}

 The dataset includes 92018 records from 865 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022177-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cjgvg9
title: Occurrence Download

description: A dataset containing 162489 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bromeliaceae"
 ]
}

 The dataset includes 162489 records from 394 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017496-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.carsxz
title: Occurrence Download

description: A dataset containing 343 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Rattus norvegicus (Berkenhout, 1769)"
 ]
}

 The dataset includes 343 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027576-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fzz23m
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hieracium placibile Johanss. & Sam."
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022181-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.13nclp
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Podocarpus glomeratus D.Don"
 ]
}

 The dataset includes 90 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017572-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jduza
title: Occurrence Download

description: A dataset containing 40546 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Laburnum anagyroides Medik.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 40546 records from 583 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039396-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.padnqw
title: Occurrence Download

description: A dataset containing 630 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is South Africa",
 "Geometry POLYGON((28.05811 -26.14208,28.06709 -26.14208,28.06709 -26.13553,28.05811 -26.13553,28.05811 -26.14208))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2019-2024"
 ]
}

 The dataset includes 630 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028903-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12772894
title: Instructions on how to run PanGenie on HGSVC3 + HPRC data

description: Input Data

Reference genome

The reference genome used (CHM13) can be obtained from: https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0.fa.gz

Reads

We used the raw 1kg Illumina reads (FASTA/FASTQ) obtained from: http://ftp.sra.ebi.ac.uk/vol1/fastq/.We created a single FASTQ file per sample by concatenating individual files, however, PanGenie can also be run with multiple files per sample (see instructions below on how this is done).

Input panel VCF

The input VCF was derived from Minigraph-Cactus VCFs produced from 65 HGSVC3 and 42 HPRC assemblies. It is available here in this repository:  MC_hgsvc3-hprc_chm13_filtered_bubbles.vcf.gz There is an additional VCF containing decomposed variant alleles, which will be needed to postprocess the PanGenie output (in order to translate bubble genotypes to genotypes for all nested variants). This VCF is also available in this repository and is called: MC_hgsvc3-hprc_chm13_filtered_decomposed.vcf.gz

Running PanGenie

We used PanGenie version v3.1.0 and ran it via singularity as described in the README (https://github.com/eblerjana/pangenie/tree/master). The singularity image used is available in this repository: eblerjana_eblerjana_pangenie-v3.1.0.sif

Commands used for genotyping

(1) Indexing (run only once):

  PanGenie-index -v MC_hgsvc3-hprc_chm13_filtered_bubbles.vcf -r chm13v2.0.fa -o index -t 24 



Note: the input panel VCF (-v) as well as the reference genome (-r) need to be uncompressed.


(2) Genotyping (run for each sample):

 PanGenie -a 108 -f index -i <(zcat <sample>.R1.fq.gz <sample>.R2.fq.gz)  -o pangenie_<sample> -j 24 -t 24 -s <sample> 



-j and -t specify the number of threads to be used for internal k-mer counting and genotyping steps (here 24 cores are used for both).

The -i parameter is used to provide input reads (in FASTA/FASTQ format). If you have more than one file per sample (e.g. for paired-end reads) use the syntax shown in the command above to avoid having to concatenate the files beforehand.


(3) Decompose bubbles (run for each sample)

cat pangenie_<sample>_genotyping.vcf | python3 convert-to-biallelic.py MC_hgsvc3-hprc_chm13_filtered_decomposed.vcf > pangenie_<sample>_genotyping_biallelic.vcf



Note: the convert-to-biallelic.py script is provided in this repository.
DOI: 10.5281/zenodo.12772895
title: Instructions on how to run PanGenie on HGSVC3 + HPRC data

description: Input Data

Reference genome

The reference genome used (CHM13) can be obtained from: https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0.fa.gz

Reads

We used the raw 1kg Illumina reads (FASTA/FASTQ) obtained from: http://ftp.sra.ebi.ac.uk/vol1/fastq/.We created a single FASTQ file per sample by concatenating individual files, however, PanGenie can also be run with multiple files per sample (see instructions below on how this is done).

Input panel VCF

The input VCF was derived from Minigraph-Cactus VCFs produced from 65 HGSVC3 and 42 HPRC assemblies. It is available here in this repository:  MC_hgsvc3-hprc_chm13_filtered_bubbles.vcf.gz There is an additional VCF containing decomposed variant alleles, which will be needed to postprocess the PanGenie output (in order to translate bubble genotypes to genotypes for all nested variants). This VCF is also available in this repository and is called: MC_hgsvc3-hprc_chm13_filtered_decomposed.vcf.gz

Running PanGenie

We used PanGenie version v3.1.0 and ran it via singularity as described in the README (https://github.com/eblerjana/pangenie/tree/master). The singularity image used is available in this repository: eblerjana_eblerjana_pangenie-v3.1.0.sif

Commands used for genotyping

(1) Indexing (run only once):

  PanGenie-index -v MC_hgsvc3-hprc_chm13_filtered_bubbles.vcf -r chm13v2.0.fa -o index -t 24 



Note: the input panel VCF (-v) as well as the reference genome (-r) need to be uncompressed.


(2) Genotyping (run for each sample):

 PanGenie -a 108 -f index -i <(zcat <sample>.R1.fq.gz <sample>.R2.fq.gz)  -o pangenie_<sample> -j 24 -t 24 -s <sample> 



-j and -t specify the number of threads to be used for internal k-mer counting and genotyping steps (here 24 cores are used for both).

The -i parameter is used to provide input reads (in FASTA/FASTQ format). If you have more than one file per sample (e.g. for paired-end reads) use the syntax shown in the command above to avoid having to concatenate the files beforehand.


(3) Decompose bubbles (run for each sample)

cat pangenie_<sample>_genotyping.vcf | python3 convert-to-biallelic.py MC_hgsvc3-hprc_chm13_filtered_decomposed.vcf > pangenie_<sample>_genotyping_biallelic.vcf



Note: the convert-to-biallelic.py script is provided in this repository.
DOI: 10.15468/dl.ytycje
title: Occurrence Download

description: A dataset containing 852673 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Asteraceae",
 {
 "or" : [
 "Country is Canada",
 "Country is United States of America"
 ]
 },
 {
 "or" : [
 "StateProvince is Ontario",
 "StateProvince is Quebec",
 "StateProvince is New Brunswick",
 "StateProvince is Illinois",
 "StateProvince is Indiana",
 "StateProvince is Tennessee",
 "StateProvince is Vermont",
 "StateProvince is Florida",
 "StateProvince is Alabama",
 "StateProvince is Georgia",
 "StateProvince is Lousiana",
 "StateProvince is Mississippi",
 "StateProvince is South Carolina",
 "StateProvince is Connecticut",
 "StateProvince is Kentucky",
 "StateProvince is Massachusetts",
 "StateProvince is Ohio",
 "StateProvince is Rhode Island",
 "StateProvince is Wisconsin",
 "StateProvince is Michigan",
 "StateProvince is Maine",
 "StateProvince is Minnesota",
 "StateProvince is New Hampshire"
 ]
 },
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 852673 records from 216 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028902-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gh62yx
title: Occurrence Download

description: A dataset containing 8835743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is Anas platyrhynchos Linnaeus, 1758",
 "Year 2018-2022"
 ]
}

 The dataset includes 8835743 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028904-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cztas6
title: Occurrence Download

description: A dataset containing 5623 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Empoasca fabae (Harris, 1841)"
 ]
}

 The dataset includes 5623 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028905-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12772943
title: Pingüinos de Palmer

description: Los datos fueron colectados y publicados por Dr. Kristen Gorman y la Palmer Station, Antarctica LTER, mimebro de Long Term Ecological Research Network. Los datos fueron traducidos como parte del paquete de r "datos". Este recurso es usado para ejemplos educativos.
DOI: 10.5281/zenodo.12772944
title: Pingüinos de Palmer

description: Los datos fueron colectados y publicados por Dr. Kristen Gorman y la Palmer Station, Antarctica LTER, mimebro de Long Term Ecological Research Network. Los datos fueron traducidos como parte del paquete de r "datos". Este recurso es usado para ejemplos educativos.
DOI: 10.25403/upresearchdata.26269879
title: <b>Soil water, irrigation and yield data for low flow and conventional drip irrigated citrus orchards</b>

description: The dataset consists of weather, yield and soil moisture data seasons 2021-23 for a Nadorcott mandarin orchard under various drip irrigation treatments in Nelspruit, South Africa. Capacitance probe, ileaf weather data, yield and quality data are all summarized within this dataset. Drip irrigation has emerged as a very effective method for the irrigation of citrus and recent advances in drip irrigation technology have reduced emitter delivery rates by 70% compared to conventional drip, in an attempt to increase irrigation efficiency by decreasing drainage and increasing water storage in the rootzone.
DOI: 10.15468/dl.fj3gew
title: Occurrence Download

description: A dataset containing 72114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-2000.0",
 "Geometry POLYGON((12.45189 55.56253,12.68395 55.55959,12.68164 55.72956,12.45189 55.72956,12.45189 55.56253))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta",
 "Year 2000-2024"
 ]
}

 The dataset includes 72114 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028907-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12772976
title: DigiOpitmus uplink datas simulations

description: Simulações de dados de uplink do DigiOpitmus. Project: https://github.com/EdilsonFilho/digi-optimus-uplink.git
DOI: 10.5281/zenodo.12772977
title: DigiOpitmus uplink datas simulations

description: Simulações de dados de uplink do DigiOpitmus. Project: https://github.com/EdilsonFilho/digi-optimus-uplink.git
DOI: 10.15468/dl.nvnjpz
title: Occurrence Download

description: A dataset containing 61288 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "Geometry POLYGON((9.53569 47.34306,9.5162 47.3287,9.48751 47.30773,9.50139 47.26042,9.58492 47.24758,9.62326 47.29293,9.64947 47.31775,9.63343 47.35266,9.59882 47.36603,9.53569 47.34306))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 61288 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028908-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12749315
title: MODES DATA - Hough functions and frequencies - 2 v3
DOI: 10.5281/zenodo.12749316
title: MODES DATA - Hough functions and frequencies - 2 v3
DOI: 10.15468/dl.9scw2z
title: Occurrence Download

description: A dataset containing 2012765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "InstitutionCode is BDBCV"
 ]
}

 The dataset includes 2012765 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028901-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hehghe
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Vaccinium microcarpum (Turcz. ex Rupr.) Schmalh. ex Busch"
 ]
}

 The dataset includes 43 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028910-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12749406
title: MODES DATA - Hough functions and frequencies - 3 v3
DOI: 10.5281/zenodo.12749407
title: MODES DATA - Hough functions and frequencies - 3 v3
DOI: 10.15468/dl.p84vpg
title: Occurrence Download

description: A dataset listing the 2172 species recorded in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-2000.0",
 "Geometry POLYGON((12.43687 55.55428,12.69229 55.55428,12.69229 55.75329,12.43687 55.75329,12.43687 55.55428))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta",
 "Year 1999-2024"
 ]
}

 The dataset's 2172 records were derived from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028906-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8v2b5
title: Occurrence Download

description: A dataset containing 50656 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phoeniconaias minor (É.Geoffroy Saint-Hilaire, 1798)"
 ]
}

 The dataset includes 50656 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028911-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dn3n96
title: Occurrence Download

description: A dataset containing 11980 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "DatasetKey is one of (Observation.org, Nature data from around the World, Naturalis Biodiversity Center (NL) - Mollusca, iNaturalist Research-grade Observations, Natural History Museum Rotterdam - Specimens, International Barcode of Life project (iBOL), INSDC Sequences, Museum of Comparative Zoology, Harvard University, naturgucker, Naturalis Biodiversity Center (NL) - Museum collection digitized at storage unit level, ZOBODAT (Zoological Botanical Database))",
 "TaxonKey is Arianta arbustorum (Linnaeus, 1758)"
 ]
}

 The dataset includes 11980 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028912-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bcky9s
title: Occurrence Download

description: A dataset containing 15255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "GadmGid is BEL.3_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 15255 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028913-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10572563
title: UA - Gaussian Depth Disc (GDD dataset)
title: Deep Learning for Single-Shot Structured Light Profilometry: A Comprehensive Dataset and Performance Analysis

description: Dear reader,


Welcome! You must be an avid profilometry person to be interested in downloading our dataset.

Before you start tinkering with the dataset package please do install the requirements.txt libraries for a more easy step into operating this system.

We hope to have made the hierarchy of the package as clear as possible! Also note that this system was written in VScode.

The Matlab script that creates the surface has been included for if you yourself would like to print one out and do in depth research!

Find your way to the examples folder, there you can find "entire_dataset". This folder contains a script to divide the original h5 file containing all data

into whatever sub-options you'd like. An example divided dataset has already been given namely the 80/20 division of respectively training and validation

data in the "example_dataset" folder.

In the folder models you will find the two models mentioned in the publication related to this dataset. These two were published with the dataset since they

had either the highest performance on the training and validation dataset (DenseNet) or on the random physical object test (CNN).

A training script is included (training_script.py) to show you how these models were created, so if you wish to add new models to the networks.py file in the classes folder, you can!

The validation jupyter notebook contains two visualisation tools to quickly and neatly show the performance of your model on the recorded dataset.

Lastly to test on the recorded objects you can run the "test_physical_data.py" and "test_physical_data_sine_deivation.py" scripts.


We hope this helps you in your research and we hope it further improves any and all research within the single shot profilometry field! 😊


Kind regards,


Rhys Evans,

InViLab,

University of Antwerp, Belgium
DOI: 10.5281/zenodo.12771948
title: UA - Gaussian Depth Disc (GDD dataset)
title: Deep Learning for Single-Shot Structured Light Profilometry: A Comprehensive Dataset and Performance Analysis

description: Dear reader,


Welcome! You must be an avid profilometry person to be interested in downloading our dataset.

Before you start tinkering with the dataset package please do install the requirements.txt libraries for a more easy step into operating this system.

We hope to have made the hierarchy of the package as clear as possible! Also note that this system was written in VScode.

The Matlab script that creates the surface has been included for if you yourself would like to print one out and do in depth research!

Find your way to the examples folder, there you can find "entire_dataset". This folder contains a script to divide the original h5 file (480x640) containing all data

into whatever sub-options you'd like (had to be made int16 as to not exceed to 50GB limit of Zenodo, you are more than welcome to reach out for the 32int format!). We included a downsampled format of 120x160 (int32) as this makes the file size more managable for pc's with not enough RAM. An example divided dataset has already been given namely the 80/20 division of respectively training and validation data in the "example_dataset" folder, of the downsampled dataset.

In the folder models you will find the two models mentioned in the publication related to this dataset. These two were published with the dataset since they

had either the highest performance on the training and validation dataset (DenseNet) or on the random physical object test (CNN).

A training script is included (training_script.py) to show you how these models were created, so if you wish to add new models to the networks.py file in the classes folder, you can!

The validation jupyter notebook contains two visualisation tools to quickly and neatly show the performance of your model on the recorded dataset.

Lastly to test on the recorded objects you can run the "test_physical_data.py" and "test_physical_data_sine_deivation.py" scripts.


We hope this helps you in your research and we hope it further improves any and all research within the single shot profilometry field! 😊


Kind regards,


Rhys Evans,

InViLab,

University of Antwerp, Belgium