cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31323997.v3
title: BIO326_2026

description: # Structural Variant Teaching Dataset Bos taurus – Chromosome 13 (IGV-ready subset)<br>---<br>## Overview<br>This dataset was prepared for teaching structural variant (SV) analysis using long-read sequencing data (Oxford Nanopore).<br>The material includes:<br>- Two samples (2024 and 2025)- High-confidence structural variants- Chromosome 13 only- Reads restricted to ±20 kb around selected SV loci<br>The dataset is intentionally reduced in size so that it loads quickly in IGV and can be used in classroom settings without heavy computational requirements.<br>---<br>## Dataset Contents<br>### Reference Genome (Chromosome 13 only)<br>- `Bos_taurus_chr13.fa`- `Bos_taurus_chr13.fa.fai`<br>Reference sequence used for alignment and visualization.<br>---<br>### Alignment Files<br>- `2024_chr13_teaching_20kb.bam`- `2024_chr13_teaching_20kb.bam.bai`- `2025_chr13_teaching_20kb.bam`- `2025_chr13_teaching_20kb.bam.bai`<br>These BAM files contain only reads overlapping selected structural variant regions (±20 kb). They allow direct comparison between two samples.<br>---<br>### Structural Variant Calls<br>- `joint_chr13_teaching_20kb.vcf.gz`- `joint_chr13_teaching_20kb.vcf.gz.tbi`<br>Joint multi-sample SV calls generated using Sniffles2 (v2.0.7).<br>High-confidence variants were selected using the following criteria:<br>- PRECISE calls only- QUAL ≥ 50- One sample homozygous alternate (1/1)- The other sample homozygous reference (0/0)- Variant read support ≥ 4- No conflicting reference reads in the alternate sample<br>---<br>### Gene Annotation<br>- `Bos_taurus_chr13.gtf.gz`- `Bos_taurus_chr13.gtf.gz.tbi`<br>Ensembl gene annotation restricted to chromosome 13.<br>---<br>## How to Use in IGV1. Load the reference genome (`Bos_taurus_chr13.fa`)2. Load both BAM files3. Load the VCF file4. Load the gene annotation (GTF)5. Navigate to a variant coordinate6. Compare genotype and read support between samples<br>---<br>## Educational Purpose<br>This dataset enables students to:<br>- Visualize insertions and deletions in long-read alignments- Compare genotypes between two samples- Interpret read-level support (DV / DR)- Understand how structural variants are represented in VCF- Connect structural variation to gene structure- Investigate gene function using public databases<br>---<br>## Software Required<br>- IGV (recommended for visualization)- samtools- bcftools- bedtools- Sniffles2 (for reproducibility)<br>---<br>## Notes<br>- Data were derived from course-based research activities.- Only chromosome 13 is included.- Only selected high-confidence SV regions are retained.- The dataset is intended for teaching and demonstration purposes.<br>---<br>
DOI: 10.6084/m9.figshare.31323997.v2
title: BIO326_2026

description: # Structural Variant Teaching Dataset Bos taurus – Chromosome 13 (IGV-ready subset)<br>---<br>## Overview<br>This dataset was prepared for teaching structural variant (SV) analysis using long-read sequencing data (Oxford Nanopore).<br>The material includes:<br>- Two samples (2024 and 2025)- High-confidence structural variants- Chromosome 13 only- Reads restricted to ±20 kb around selected SV loci<br>The dataset is intentionally reduced in size so that it loads quickly in IGV and can be used in classroom settings without heavy computational requirements.<br>---<br>## Dataset Contents<br>### Reference Genome (Chromosome 13 only)<br>- `Bos_taurus_chr13.fa`- `Bos_taurus_chr13.fa.fai`<br>Reference sequence used for alignment and visualization.<br>---<br>### Alignment Files<br>- `2024_chr13_teaching_20kb.bam`- `2024_chr13_teaching_20kb.bam.bai`- `2025_chr13_teaching_20kb.bam`- `2025_chr13_teaching_20kb.bam.bai`<br>These BAM files contain only reads overlapping selected structural variant regions (±20 kb). They allow direct comparison between two samples.<br>---<br>### Structural Variant Calls<br>- `joint_chr13_teaching_20kb.vcf.gz`- `joint_chr13_teaching_20kb.vcf.gz.tbi`<br>Joint multi-sample SV calls generated using Sniffles2 (v2.0.7).<br>High-confidence variants were selected using the following criteria:<br>- PRECISE calls only- QUAL ≥ 50- One sample homozygous alternate (1/1)- The other sample homozygous reference (0/0)- Variant read support ≥ 4- No conflicting reference reads in the alternate sample<br>---<br>### Gene Annotation<br>- `Bos_taurus_chr13.gtf.gz`- `Bos_taurus_chr13.gtf.gz.tbi`<br>Ensembl gene annotation restricted to chromosome 13.<br>---<br>## How to Use in IGV<br>1. Load the reference genome (`Bos_taurus_chr13.fa`)2. Load both BAM files3. Load the VCF file4. Load the gene annotation (GTF)5. Navigate to a variant coordinate6. Compare genotype and read support between samples<br>---<br>## Educational Purpose<br>This dataset enables students to:<br>- Visualize insertions and deletions in long-read alignments- Compare genotypes between two samples- Interpret read-level support (DV / DR)- Understand how structural variants are represented in VCF- Connect structural variation to gene structure- Investigate gene function using public databases<br>---<br>## Software Required<br>- IGV (recommended for visualization)- samtools- bcftools- bedtools- Sniffles2 (for reproducibility)<br>---<br>## Notes<br>- Data were derived from course-based research activities.- Only chromosome 13 is included.- Only selected high-confidence SV regions are retained.- The dataset is intended for teaching and demonstration purposes.<br>---<br>
DOI: 10.5281/zenodo.18629997
title: Solid-state NMR data for publication: Revision of crystal structures with disordered hydrogen Resolving apparent proton disorder in short hydrogen bonds: A combined X-ray diffraction, ssNMR and periodic DFT study

description: ### data from 600 MHz JEOL spectrometer ###DAKWES sample 1H, saturation recovery experiment: /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_satrec_1H_echo-3-1.jdfDAKWES sample 1H, raw 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdfDAKWES sample, extracted S0-part from 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdfDAKWES sample 1H, S-part from 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdf

PUHROZ sample 1H, saturation recovery experiment: /PUHROZ/20250312_PUHROZ_1.0mm_62.5kHz_satrec_1H_echo-2-1.jdfPUHROZ sample, raw 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-1.jdfPUHROZ sample, extracted S0-part from 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-2.jdfPUHROZ sample, extracted S-part from 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-3.jdf

FAFFAV sample 1H, saturation recovery experiment: /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_satrec_1H_echo-1-1.jdfFAFFAV sample, raw 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-1.jdfFAFFAV sample, extracted S0-part from 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-2.jdfFAFFAV sample, extracted S-part from 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-3.jdfFAFFAV sample, raw 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-1.jdfFAFFAV sample, extracted S0-part from 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-2.jdfFAFFAV sample, extracted S-part from 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-3.jdfFAFFAV sample, first reference spectra from T-FILTERED RESPDOR data : /FAFFAV/20250606_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-4-1.jdf 

JEOL pulse program for T-filtered RESPDOR : jb_t-filter_RESPDOR_SR4_3D.jxp
DOI: 10.5281/zenodo.18629996
title: Solid-state NMR data for publication: Revision of crystal structures with disordered hydrogen Resolving apparent proton disorder in short hydrogen bonds: A combined X-ray diffraction, ssNMR and periodic DFT study

description: ### data from 600 MHz JEOL spectrometer ###DAKWES sample 1H, saturation recovery experiment: /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_satrec_1H_echo-3-1.jdfDAKWES sample 1H, raw 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdfDAKWES sample, extracted S0-part from 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdfDAKWES sample 1H, S-part from 1H-14N 3D RESPDOR data : /DAKWES/20250203_DEKWES_1.0mm_62.5kHz_respdor_3d-1-1.jdf

PUHROZ sample 1H, saturation recovery experiment: /PUHROZ/20250312_PUHROZ_1.0mm_62.5kHz_satrec_1H_echo-2-1.jdfPUHROZ sample, raw 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-1.jdfPUHROZ sample, extracted S0-part from 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-2.jdfPUHROZ sample, extracted S-part from 1H-14N 3D RESPDOR data : /PUHROZ/20250318_PUHROZ_1.0mm_62.5kHz_respdor_3d-1-3.jdf

FAFFAV sample 1H, saturation recovery experiment: /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_satrec_1H_echo-1-1.jdfFAFFAV sample, raw 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-1.jdfFAFFAV sample, extracted S0-part from 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-2.jdfFAFFAV sample, extracted S-part from 1H-14N 3D RESPDOR data : /FAFFAV/20250601_FAFFAV_1.0mm_62.5kHz_respdor_3d-1-3.jdfFAFFAV sample, raw 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-1.jdfFAFFAV sample, extracted S0-part from 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-2.jdfFAFFAV sample, extracted S-part from 1H-14N 3D T-FILTERED RESPDOR data : /FAFFAV/20250609_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-1-3.jdfFAFFAV sample, first reference spectra from T-FILTERED RESPDOR data : /FAFFAV/20250606_FAFFAV_1.0mm_62.5kHz_t-filter_RESPDOR_14N_1H-4-1.jdf 

JEOL pulse program for T-filtered RESPDOR : jb_t-filter_RESPDOR_SR4_3D.jxp
DOI: 10.5281/zenodo.14712896
title: Quality Control in Additive Manufacturing: Image Dataset for Defect Detection in Fused Filament Fabrication

description: This image dataset was created to support the development of image-based defect detection and quality control systems in additive manufacturing, particularly in fused filament fabrication. It includes high resolution images as well as cropped images of 3D printed objects with production defects, such as extrusion errors and layershifts and stringing errors, as well as images of defect-free prints. The data was captured from three different camera angles during production. 

Please cite this repository if you use the dataset in your work.
DOI: 10.5281/zenodo.18628777
title: Quality Control in Additive Manufacturing: Image Dataset for Defect Detection in Fused Filament Fabrication

description: This image dataset was created to support the development of image-based defect detection and quality control systems in additive manufacturing, particularly in fused filament fabrication. It includes high resolution images as well as cropped images of 3D printed objects with production defects, such as extrusion errors and layershifts and stringing errors, as well as images of defect-free prints. The data was captured from three different camera angles during production. 

Please cite this repository if you use the dataset in your work.
DOI: 10.15468/dl.muaxhg
title: Occurrence Download

description: A dataset containing 445 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerocactus scheerii",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 445 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014818-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/9jutqw
title: Entomologische Sammlung (ETHZ-ENT) of Eidgenössische Technische Hochschule Zürich

description: Entomological collection of the Swiss Federal Institute of Technology in Zurich. With 2 million specimens mostly from Switzerland and Europe; the collection is the fourth largest entomological collection in Switzerland.
DOI: 10.15468/dl.kqgpgb
title: Occurrence Download

description: A dataset containing 9164 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus iria",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 9164 records from 405 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014819-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b7ksnq
title: Occurrence Download

description: A dataset containing 244 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carapichea ipecacuanha",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 244 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014820-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2d3xyd
title: CCDC 2208314: Experimental Crystal Structure Determination

description: Related Article: Yuxuan Qi, Zhiquan Cai, Yi-Si Feng, Junru Wang, Zhenhong Dai, Zhifei Cheng|2025|J.Colloid Interface Sci.|700|138528|doi:10.1016/j.jcis.2025.138528
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.4phthb
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Laimosemion rectocaudatus",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 19 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014821-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18629900
title: Climate drivers and European Gross Primary Productivity (1772–2020)

description: This dataset contains annual climate indices and ecosystem productivity variables used in the manuscript "Two Centuries of Increasing European Gross Primary Production Driven by Climate Variability (1772-2020)". Variables include atmospheric CO₂ concentrations, large-scale climate oscillations (AMO, NAO), drought indices (PDSI, VPDI), soil moisture, temperature, and Gross Primary Productivity (GPP).
DOI: 10.5281/zenodo.18629901
title: Climate drivers and European Gross Primary Productivity (1772–2020)

description: This dataset contains annual climate indices and ecosystem productivity variables used in the manuscript "Two Centuries of Increasing European Gross Primary Production Driven by Climate Variability (1772-2020)". Variables include atmospheric CO₂ concentrations, large-scale climate oscillations (AMO, NAO), drought indices (PDSI, VPDI), soil moisture, temperature, and Gross Primary Productivity (GPP).
DOI: 10.15468/dl.uun6dc
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lecidea huxariensis",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014822-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ga5mra
title: Occurrence Download

description: A dataset containing 2403655 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia",
 "Year 2003-2022"
 ]
}

 The dataset includes 2403655 records from 326 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014776-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ffd8rr
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prosopis sericantha"
 ]
}

 The dataset includes 229 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014823-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bj2ubd
title: Occurrence Download

description: A dataset containing 161275 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Andromeda polifolia"
 ]
}

 The dataset includes 161275 records from 569 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014701-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17325906
title: Ethical Framing in Large Language Models : A Cross-Cultural Comparative Dataset
DOI: 10.25439/rmt.28581179
title: Development and validation of the Global Urban Heat Vulnerability Index (GUHVI) - supplementary materials

description: This data package contains supplementary materials related to development and validation of the Global Urban Heat Vulnerability Index (GUHVI) conducted for 8 Australian capital cities, and 9 diverse cities worldwide. This research was initiated by the Global Observatory of Healthy and Sustainable Cities for the 1000 Cities Challenge and inclusion in the Global Healthy & Sustainable City Indicators (GHSCI) open-source software.This data package contains the following:The Jupyter Notebook hosting a custom Python script that makes use of the Google Earth Engine API and geemap API to generate an overall heat vulnerability raster, three sub-index rasters, and ten input rasters.POPD, SHDI, and IMR input rasters. The remaining inputs into the GUHVI are automatically fetched from cloud storage as the script runs.GUHVI and iHVI visual comparison as .jpg file.A folder for each of the 8 Australian cities involved in the study, containing the 14 GUHVI rasters, urban centre boundary in .shp format, and hottest third of the year date range in .txt format in the 'GUHVI Outputs' folder. The 'iHVI Outputs' folder contains the input LST, NDVI, NDBI .csv files, and the output heat vulnerability and sub-index .csv files. The 'QGIS Data' folder contains the SA1 .shp files attributed with heat vulnerability scores, and the iHVI and GUHVI comparison rasters.A folder for each of the 9 international cities involved in the study, containing the 14 GUHVI rasters, urban centre boundary in .shp format, hottest third of the year date range in .txt format, and the QGIS project file provided to collaborators for validation.R scripts for generating the normalized mean results, population percentage per heat vulnerability class table, and combined box, half-violin and strip plots for each city.The instructional video provided to collaborators as a .mp4 file, which outlines how to navigate the QGIS project, and how to access and record comments in the live spreadsheet.The complete validation spreadsheet with comments included as a .pdf file.Supplementary tables listing the urban centre boundary source files for each city, and the OpenStreetMap data source used to perform the coastal pixel overlap methodology as a .pdf file.
DOI: 10.25439/rmt.28581179.v2
title: Development and validation of the Global Urban Heat Vulnerability Index (GUHVI) - supplementary materials

description: This data package contains supplementary materials related to development and validation of the Global Urban Heat Vulnerability Index (GUHVI) conducted for 8 Australian capital cities, and 9 diverse cities worldwide. This research was initiated by the Global Observatory of Healthy and Sustainable Cities for the 1000 Cities Challenge and inclusion in the Global Healthy & Sustainable City Indicators (GHSCI) open-source software.This data package contains the following:The Jupyter Notebook hosting a custom Python script that makes use of the Google Earth Engine API and geemap API to generate an overall heat vulnerability raster, three sub-index rasters, and ten input rasters.POPD, SHDI, and IMR input rasters. The remaining inputs into the GUHVI are automatically fetched from cloud storage as the script runs.GUHVI and iHVI visual comparison as .jpg file.A folder for each of the 8 Australian cities involved in the study, containing the 14 GUHVI rasters, urban centre boundary in .shp format, and hottest third of the year date range in .txt format in the 'GUHVI Outputs' folder. The 'iHVI Outputs' folder contains the input LST, NDVI, NDBI .csv files, and the output heat vulnerability and sub-index .csv files. The 'QGIS Data' folder contains the SA1 .shp files attributed with heat vulnerability scores, and the iHVI and GUHVI comparison rasters.A folder for each of the 9 international cities involved in the study, containing the 14 GUHVI rasters, urban centre boundary in .shp format, hottest third of the year date range in .txt format, and the QGIS project file provided to collaborators for validation.R scripts for generating the normalized mean results, population percentage per heat vulnerability class table, and combined box, half-violin and strip plots for each city.The instructional video provided to collaborators as a .mp4 file, which outlines how to navigate the QGIS project, and how to access and record comments in the live spreadsheet.The complete validation spreadsheet with comments included as a .pdf file.Supplementary tables listing the urban centre boundary source files for each city, and the OpenStreetMap data source used to perform the coastal pixel overlap methodology as a .pdf file.