cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/a29c5465-b138-234d-e053-6c86abc040b9
title: The GEBCO_2020 Grid - a continuous terrain model of the global oceans and land.

description: The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA.
DOI: 10.17632/dtsn3xn3n6.5
title: Global chronostratigraphical correlation table for the last 2.7 million years v.2019 (Poster version)

description: This 'version 5' upload is the 2022-updated poster-version of Figure 1 of the Quaternary International 500 article (version 1). 
The Figure 2 inset from that paper, is also included here, for completeness. 
Cohen, K.M. & Gibbard, P.L. 2019 Global chronostratigraphical correlation table for the last 2.7 million years.
Quaternary International vol. 500. Fig. 1. https://doi.org/10.1016/j.quaint.2019.03.009

See abstract and full text of the linked paper for details, research history  and citations/references to materials included in the chart: it makes extensive use of published data sets and schemes, all cited in the main text, many of which have data repositories.

The 2020 update comprised the ratification of a GSSP for the Middle Pleistocene (introducing the Chibanian Stage), the splitting of the Subseries and Stages column and the way the GSSPs are indicated, and the lowering of the provisional numeric age for the Late Pleistocene Subseries/Stage from 0.129 to 0.126 (affecting the dashed horizontal line that serves as a left-right guide across the chart). The 2021 update corrected a MIS misnumbering at the top of the Olduvai (63, 65) present in older editions, spotted after over a decade of updating the figure/poster. Otherwise, the undivided poster version only differs from the 3-page spread figure in the QI paper in  placement and font size of title and version, placement of logotypes, inclusion of Utrecht University and University of Cambridge logo's on the poster (continued from earlier releases of the chart), reference to the Quaternary International v-500 2019 paper. 
All data featured on the chart, is referenced in brief in the text below, and referenced in full and documented in brief in the 2019 paper.

The 2019 QI-500 paper publication followed up the Episodes 2008 Gibbard & Cohen paper.
The 2021 and 2020 edition of the chart (versions 4, 3, 2 in this repository)  follow up editions in 2019 (QI-500/INQUA-Dublin; version 4) and the 2016 IUGS' Cape town IGC version (web-released at the time). 
The 2021 and 2022 edition are corrigenda regarding MIS labeling around the Olduvai (see text in Steps to reproduce).

The release of the poster version via data.mendeley.com, cross-referenced from the QI paper, was coordinated with the QI journal management (Elsevier) and editorship (INQUA). 
Use of the IUGS-ICS and INQUA logo's was coordinated with the respective organisations (and is continued from earlier releases of the chart). 

The PDF files contain scale-able vector graphics only and therefore should suit reproductions to mini-poster (A4, A3) and poster size  (e.g. A1) formats alike. 
Before seeking far zoomed-in usage of the chart: take notice of the discussion in the QI paper of chosen graphical resolution, versus achievable geological and chronometric correlation accuracy limits.
DOI: 10.18128/d070.v7.2
title: IPUMS Health Surveys: National Health Interview Survey, Version 7.2

description: The IPUMS NHIS is a harmonized set of data for over 50 years (1963-present) of the National Health Interview Survey (NHIS). The NHIS is the principal source of information on the health of the U.S. population, covering such topics as general health status, the distribution of acute and chronic illness, functional limitations, access to and use of medical services, insurance coverage, and health behaviors (such as exercise, diet, and tobacco and alcohol consumption). On average, the survey covers 40,000 persons each year. IPUMS NHIS facilitates cross-time comparisons of these invaluable survey data by coding variables identically across time and providing detailed documentation covering comparability issues for harmonized variables. IPUMS NHIS data are distributed for free through an online data access system (nhis.ipums.org) to any person who agrees to follow the responsible use guidelines set by the National Center for Health Statistics.
DOI: 10.21227/bhxy-ep04
title: MQTT Internet of Things Intrusion Detection Dataset

description: Message Queuing Telemetry Transport (MQTT) protocol is one of the most recent standards used in Internet of Things (IoT) machine to machine communication. The increase in the number of available IoT devices and used protocols reinforce the need for new and robust Intrusion Detection Systems (IDS). However, building IoT IDS requires the availability of datasets to process, train and evaluate these models. The dataset presented in this paper is the first to simulate and MQTT-based network. The dataset is generated using a simulated MQTT network architecture. The network comprises twelve sensors, a broker, a simulated camera, and an attacker. Five scenarios are recorded: (1) normal operation, (2) aggressive scan, (3) UDP scan, (4) Sparta SSH brute-force, and (5) MQTT brute-force attack. The raw pcap files are saved, then features are extracted. Three abstraction levels of features are extracted from the raw pcap files: (a) packet features, (b) Unidirectional flow features and (c) Bidirectional flow features. The csv feature files in the dataset are suited for Machine Learning (ML) usage. Also, the raw pcap files are suitable for the deeper analysis of MQTT IoT networks communication and the associated attacks.
DOI: 10.24432/c56s3t
title: Wine Quality
DOI: 10.25318/1310009601-eng
title:  Health characteristics, annual estimates

description: Health characteristics, annual estimates, by age group and sex, Canada (excluding territories) and provinces.
DOI: 10.25380/iastate.25541068.v1
title: Maize crown root images from 22 genotypes

description: This is an image dataset comprised of crown roots from 22 maize genotypes excavated from the soil at stages V6-V10 grown at the ISU Agricultural Engineering/Agronomy and Central Iowa Research Farm in Boone, Iowa on July 2022. After 7 days of air drying at room temperature, the crown roots were imaged using a Cannon DSLR camera. Images were saved in .jpg format and total 262 individual files. This dataset of field grown root systems can be leveraged to inform strategies for improved corn physiology.
DOI: 10.25380/iastate.25625430.v1
title: Maize seedling images from 617 genotypes

description: This dataset documents the phenotypes of 617 maize genotypes grown in the absence (“mock”) and presence of 10 mM indole-3-acetic acid (IAA) in .tif image format. This large-scale seedling data, which contains images in different 18 folders, increases our understanding of the phenotypic ranges displayed by maize in numerous agriculturally relevant traits, including organ size and responses to a key growth regulator.
DOI: 10.26093/cds/vizier.36160010
title: 46 open clusters GaiaDR2 HR diagrams

description: VizieR online Data Catalogue associated with article published in journal Astronomy & Astrophysics with title 'Gaia Data Release 2: Observational Hertzsprung-Russell diagrams.' (bibcode: 2018A&A...616A..10G)
DOI: 10.26093/cds/vizier.51590282
title: Membership in Ophiuchus & Upper Scorpius complex

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'A survey for new stars and brown dwarfs in the Ophiuchus star-forming complex.' (bibcode: 2020AJ....159..282E)
DOI: 10.48612/msupe/65u5-gf9t-45u3
title: Анализ связи между результатами единого государственного экзамена и академическими успехами студентов

description: Набор данных статьи "Анализ связи между результатами единого государственного экзамена и академическими успехами студентов". 
Цель работы заключается в исследовании влияния результатов ЕГЭ на академическую успеваемость студентов вуза на основе анализа данных, накопленных в процессе функционирования университетской информационной системы крупного регионального вуза. Методология исследования включает анализ данных о баллах ЕГЭ и дипломных оценках за 13 лет обучения в университете, применение линейной регрессии для оценки зависимости успеваемости студентов различных специальностей от баллов ЕГЭ. Обнаружена зависимость между разбросом баллов ЕГЭ при поступлении и последующей успеваемостью студентов, выраженной в виде среднего балла и дипломных оценок. Отмечено, что баллы ЕГЭ должны быть включены как дополнительные объясняющие переменные при построении моделей оценки образовательного процесса. Они также могут быть использованы для оптимизации процесса подготовки студентов к поступлению в вуз и дальнейшему обучению. Ценность работы заключается в оценке значимости баллов ЕГЭ как индикатора успешности студентов в вузе и их соответствия результатам обучения. Работа ориентирована на специалистов в области образования, принимающих решения об оценке и улучшении качества образовательного процесса.
DOI: 10.48612/msupe/mh9n-t1et-8v7t
title: Материалы эмпирического исследования роли адаптационной готовности и субъективной оценки ситуации в образовательной среде вуза в академической адаптации студентов

description: Представлена база данных исследования, целью которого являлось выявить роль адаптационной готовности и субъективной оценки ситуации в образовательной среде в академической адаптации студентов вуза.
DOI: 10.48612/msupe/xu26-hfxz-h4eh
title: Материалы тестов к статье "Сравнительный анализ сформированности математических понятий у студентов через призму теории APOS: город против села"
title: Таблица данных по опросу

description: Целью данного исследования является определение степени сформированности математических понятий у студентов через призму теории APOS в контексте социального и географического разнообразия. В исследовании участвовали 96 первокурсника Института строительства из Казанского государственного архитектурно-строительного университета. Эмпирическую основу составили данные письменного опроса, проведенного среди учащихся, с анализом количественных показателей на каждой из стадий APOS с учетом географического разнообразия. Исследование основывается на теории APOS (Действие-Процесс-Объект-Схема), которая позволяет поэтапно проследить процесс понимания, выявлять типичные ошибки и классифицировать их. В рамках данной теории был разработан опросник для анализа процесса формирования понимания математических концепций у студентов. Была проведена классификация ошибок как концептуальных и процессуальных, позволившая выявить различия между студентами в уровне их компетентности в соответствии со стадиями теории APOS.
DOI: 10.5067/7mcpbj41y0k6
title: MERRA-2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics V5.12.4
DOI: 10.5067/szymdfz7tj4h
title: Groundwater and Soil Moisture Conditions from GRACE and GRACE-FO Data Assimilation L4 7-days 0.25 x 0.25 degree Global V3.0
DOI: 10.5281/zenodo.10108942
title: ANI-2x Release

description: ANI-2x Data Set
The ANI-2x data set of density function theory properties for small organic molecules containing H, C, N, O, S, F, and Cl at the following levels of theory: 

wB97X/631Gd (data used to train model in the ANI-2x paper)
wB97X/def2TZVPP
wB97MD3BJ/def2TZVPP
wB97MV/def2TZVPP
B973c/def2mTZVP
The sample data loader script provides an example of how to access the contents of the data sets using h5py. 
View the supplementary information for more information on the formatting and contents of the data sets. 
 
This data is a part of the ANI family of datasets. ANI1x and ANI1ccx can be found through the following link: https://github.com/aiqm/ANI1x_datasets
 
Details on the generation of this data can be found in the ANI-2x paper.
DOI: 10.5281/zenodo.12789305
title: Aqueous phase processing affects the formation and size distribution of aerosol organic functional groups during heavy pollution

description: Data from Hefei,a major urban city in Eastern China, including chemical composition, Infrared spectrum (IR), and pollution air data.
DOI: 10.5281/zenodo.13627394
title: Functional annotation of 180 RefSeq reference plant proteomes reveals a dataset of 113,684 NLR proteins

description: Abstract

Nucleotide-binding leucine-rich repeat receptors (NLRs) are critical components of plant immune systems, responsible for detecting pathogens and initiating defence responses. As part of our exploration of NLR protein diversity across a broad spectrum of plant species, we created a comprehensive NLRome dataset by analyzing 180 reference plant genomes from the NCBI RefSeq database (Pruitt et al. 2007). This database includes high-quality genome annotations for species from a wide phylogenetic range, encompassing algae, gymnosperms, early flowering plants, monocots, and dicots (https://www.ncbi.nlm.nih.gov/refseq/). Using NLRtracker, a specialized bioinformatics tool that integrates InterProScan for domain identification, we extracted and catalogued NLR proteins across these diverse genomes. Based on the NLR definition of RefPlantNLR and NLRtracker (Kourelis et al. 2021), 169 of the 180 species had at least 1 NLR predicted. In total, we catalogued 113,686 NLRs, ranging from 33 in Cucurbita maxima to 4155 in Quercus robur. In addition to NLR annotation, NLRtracker provided functional annotations for the entire proteome of each species enabling comparative genomics and evolutionary studies.

 

NLRtracker output legend:






File extension



Description





* _NLRtracker.tsv



NLRtracker overview output with gene status.





*_NLR.lst



Identifier list of NLRs.





*_NLR.gff3



NLR annotation of motifs, domains, and regions in GFF3 format.





*_NLR.fasta



NLR FASTA sequences.





*_NLR-associated.lst



Identifier list of NLR associated genes.





*_NLR-associated.gff3



NLR associated genes annotation of motifs, domains, and regions in GFF3 format.





*_NLR_associated.fasta



NLR associated genes FASTA sequences.





*_NBARC.fasta



NB-ARC domain FASTA sequences.





*_NBARC_deduplictated.fasta



Deduplicated NB-ARC domain FASTA sequences.





*_iTOL.txt



Domain annotation file for iTOL.





*_iTOL_dedup.txt



Domain annotation file of the deduplicated sequences for iTOL.





*_Domains.tsv



Full-length and domain sequence and metadata for all NLRtracker output.





interpro_result.gff



InterProScan output of the query proteome.





 

Supplementary Data

Data S1. RefSeq species list and metadata.

Data S2. Per genome sequence number statistics table for proteomes, total NLR, and putative NLR types determined by NLRtracker.
DOI: 10.5281/zenodo.13910109
title: Transmission spectroscopy data of the D2 line of rubidium-87 in the hyperfine Paschen-Back regime

description: Contains experimental data and corresponding simulations. Also includes scripts to generate the figures of the referenced paper.
DOI: 10.5281/zenodo.14534684
title: Dataset for "Systematic exploration of direct solar absorption potential to enhance direct contact membrane distillation"

description: Dataset containing the model results for the study "Systematic exploration of direct solar absorption potential to enhance direct contact membrane distillation", where a Direct Contact Membrane Distillation (DCMD) module with direct solar absorption at the feed water side is simulated.

The following data are contained in the dataset:



productivity_per_length: productivity of the considered DCMD module, as obtained from the model [(kg/s)/m^2]

TPC_mean: average temperature polarization coefficient along the DCMD module, as obtained from the model [-]

CPC_mean: average concentration polarization coefficient along the DCMD module, as obtained from the model [-]

velocity_inlet: inlet velocity of feed and permeate water, as imposed in the model. Negative values refer to counter-current flows [m/s]

T_feed: inlet temperature of feed water, as imposed in the model. Inlet temperature of permeate water is fixed to 293.15 K [K]

channel_thickness: thickness of feed and permeate water channels, as imposed in the model [m]

q_sun: solar irradiance absorbed on the top feed water channel, as imposed in the model [W/m^2]

length: length of feed and permeate water channels, as imposed in the model [m]

membrane_porosity: porosity of the membrane, as imposed in the model [-]

membrane_lambda: thermal conductivity of the membrane, as imposed in the model [W/(m*K)]

membrane_thickness: thickness of the membrane, as imposed in the model [m]

membrane_pore_radius: average pore radius of the membrane, as imposed in the model [m]
DOI: 10.5281/zenodo.14544899
title: Supporting material for "A hierarchical immune receptor network in lettuce reveals contrasting patterns of evolution in sensor and helper NLRs"

description: Description

AF3.zip AlphaFold 3 predicted structures for monomeric and hexameric NRC helper and sensor sequences.

GFF.zip Simplified GFF annotation of selected Asterales species used for gene-distance analysis.

PAML.zip Codon-based nucleotide sequences, phylogenetic trees, and CodeML input and output files from PAML analysis. Files are divided between domain-based analysis and full-length analysis for each NRC subclade.

trees.zip Phylogenetic trees generated and used in the analysis and making of the figures.

sequences.zip Nucleotide sequences and amino acid alignments of Lactuca NRC helpers and sensors.
DOI: 10.5281/zenodo.14614802
title: mimicINT workflow: Use cases for interaction interface identification and protein interaction inference

description: We used the mimicINT workflow (https://doi.org/10.5281/zenodo.12078118) to:



Identify putative interfaces in experimentally identified interactions between secreted effectors from the enteropathogenic Escherichia coli serotype O157:H7 (EHEC) and human proteins;

Infer the interactions between human and Marburg virus (MARV) proteins.
DOI: 10.5281/zenodo.14919755
title: Data and code: Kuipers et al. (2025) Relationships between mean species abundance (MSA) and potentially disappeared fraction of species (PDF) are consistent but also uncertain. Environmental and Sustainability Indicators

description: Zip folder conaining the data and code that support the findings of Kuipers et al. (2025) Relationships between mean species abundance (MSA) and potentially disappeared fraction of species (PDF) are consistent but also uncertain. Environmental and Sustainability Indicators.
DOI: 10.5281/zenodo.3164691
title: Pythia8 Quark and Gluon Jets for Energy Flow

description: Two datasets of quark and gluon jets generated with Pythia 8, one with all kinematically realizable quark jets and one that excludes charm and bottom quark jets (at the level of the hard process). The one without c and b jets was originally used in Energy Flow Networks: Deep Sets for Particle Jets. Generation parameters are listed below: Pythia 8.226 (without bc jets), Pythia 8.235 (with bc jets), \(\sqrt{s}=14\,\text{TeV} \) Quarks from WeakBosonAndParton:qg2gmZq, gluons from WeakBosonAndParton:qqbar2gmZg with the Z decaying to neutrinos FastJet 3.3.0, anti-ki jets with R=0.4 \(p_T^\text{jet}\in[500,550]\,\text{GeV},\,|y^\text{jet} |&lt;1.7\) There are 20 files in each dataset, each in compressed NumPy format. Files including charm and bottom jets have 'withbc' in their filename. There are two arrays in each file X: (100000,M,4), exactly 50k quark and 50k gluon jets, randomly sorted, where M is the max multiplicity of the jets in that file (other jets have been padded with zero-particles), and the features of each particle are its pt, rapidity, azimuthal angle, and pdgid. y: (100000,), an array of labels for the jets where gluon is 0 and quark is 1. If you use this dataset, please cite this Zenodo record as well as the corresponding paper: P. T. Komiske, E. M. Metodiev, J. Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165. For the corresponding dataset of Herwig jets, see this Zenodo record. The datasets can be downloaded and read into python automatically using the EnergyFlow Python package. Changes: v1 - Added files with b and c quark jets.
description: {"references": ["P. T. Komiske, E. M. Metodiev, J. Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165.", "P. T. Komiske, E. M. Metodiev, EnergyFlow, https://energyflow.network."]}