cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.smx5j5
title: Occurrence Download

description: A dataset containing 15572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syringa vulgaris",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15572 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061798-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/0bj-wb9-zbk
title: Samolus valerandi L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/0aj-08a-y24
title: Cuscuta approximata Bab.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/3ab-dsh-7bd
title: Leucanthemum Hill

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wbq-ck8-pt1
title: Centaurea L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.mdk2q5
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aloina rigida",
 "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 76 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023820-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ns9hnf
title: Occurrence Download

description: A dataset containing 295615443 species occurrences available in GBIF matching the query:
{
 "Year" : [
 "2018-2020"
 ]
}

 The dataset includes 295615443 records from 3173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020057-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gdmnub
title: Occurrence Download

description: A dataset containing 185869 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((120.08986 24.39235,119.63497 22.8003,120.62802 21.70155,121.398 21.82574,121.6381 22.67852,122.26734 25.19545,121.44768 25.43555,120.6777 25.17061,120.08986 24.39235))",
 "IucnRedListCategory is one of (EN, VU, CR)",
 "Year 2022-2024"
 ]
}

 The dataset includes 185869 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007246-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3u3rm8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Actinopterygii",
 "Year is 2009"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007262-250426092105405/datasets/export for details.
DOI: 10.5067/asdc/suborbital/korusaq_metnav_aircraftinsitu_hanseokingair_data_1
title: KORUS-AQ Hanseo King Air Aircraft In Situ Meteorological and Navigational Data
DOI: 10.5281/zenodo.14736502
title: Code and data for the article "Geographic Networks of Gun Violence: Exploring Hot Spot Connectivity through Ballistic Evidence and Social Network Analysis"
DOI: 10.5281/zenodo.15498296
title: Code and data for the article "Geographic Networks of Gun Violence: Exploring Hot Spot Connectivity through Ballistic Evidence and Social Network Analysis"
DOI: 10.5281/zenodo.15498330
title: Absorption spectrum of ADS830WS dye

description: Absorption spectrum of ADS830WS dye solved in methanol, and in a resin matrix. Measured with Shimadzu UV-1800 spectrophotometer, with a wavelength resolution of 1 nm working in the range of 400 nm to 1000 nm.
DOI: 10.5281/zenodo.15498331
title: Absorption spectrum of ADS830WS dye

description: Absorption spectrum of ADS830WS dye solved in methanol, and in a resin matrix. Measured with Shimadzu UV-1800 spectrophotometer, with a wavelength resolution of 1 nm working in the range of 400 nm to 1000 nm.
DOI: 10.34740/kaggle/dsv/11009068
title: Deforestation Non-Deforestation Area Analysis
DOI: 10.34740/kaggle/dsv/11924429
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.zr6dqc
title: Occurrence Download

description: A dataset containing 728264 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hestina mena Moore, 1858, Apatura ulupi (Doherty, 1889), Dilipa fenestra (Leech, 1891), Neptis soma Moore, 1858, Chitoria chrysolora (Fruhstorfer, 1908), Timelaea albescens Oberthür, Hestina assimilis (Linnaeus, 1758), Catopyrops florinda (Butler, 1877), Sasakia charonda (Hewitson, 1862), Hestina japonica (Felder, 1862), Litinga mimica, Sasakia funebris (Leech, 1891), Caloptilia celtidis Kumata, 1982, Ninodes splendens (Butler, 1878), Beara dichromella Walker, 1866, Rhodinia verecunda Inoue, 1984, Makiptyelus dimorphus Maki, 1914, Libythea lepita Moore, 1857, Hoplapoderus pardaloides Voss, 1924, Hestina assimilis assimilis, Toyoides albipennis Matsumura, 1935, Mycalesis sangaica Butler, 1877, Macalpinomyces neglectus (Niessl) Vánky, Faronta albilinea Hübner, 1827, Manga basilinea Bowden, 1956, Stenachroia elongella Hampson, 1898, Chilo diffusilinea de Joannis, 1927, Busseola fusca Fuller, 1901, Nomophila noctuella (Denis & Schiffermüller), Chilo suppressalis Walker, 1863, Passerina ciris (Linnaeus, 1758), Tympanuchus phasianellus (Linnaeus, 1758), Sesamia inferens (Walker, 1856), Euproctis fasciata Walker, 1855, Cnaphalocrocis trapezalis Guenée, 1854, Creatonotos gangis (Linnaeus, 1763), Chilo sacchariphagus Bojer, 1856, Toxidia thyrrhus (Mabille, 1891), Thargella caura (Plötz, 1882), Notozulia entreriana (Berg, 1879), Leptoschoinus fucatus (J.C.F.Klug, 1829), Lonchura oryzivora (Linnaeus, 1758), Heterohyrax brucei (Gray, 1868), Redunca redunca (Pallas, 1767), Prosapia simulans (Walker, 1858), Mugadina superba Ewart & Moulds, 2021, Chloropelix canariensis Lindberg, 1936, Tetramelasma litopyx Stiller, 2011, Aeneolamia albofasciata (Lallemand, 1939), Euodice cantans (Gmelin, 1789))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 728264 records from 840 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015769-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17172/nomad/2025.05.23-1
title: NOMAD dataset: SrTiO3_Phases_and_defects
DOI: 10.15468/dl.su8xzk
title: Occurrence Download

description: A dataset listing the 15212 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-82.2561 27.39159,-81.19213 27.39159,-81.19213 28.38386,-82.2561 28.38386,-82.2561 27.39159))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 15212 records were derived from 565 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015771-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15496946
title: Tesla option chain Data

description:  

This dataset contains preprocessed option data for Tesla Inc. (TSLA), curated for time-series modeling of implied volatility (IV). The dataset spans multiple strike prices and both call and put options. Each row corresponds to a unique combination of date, strike price, and option type, along with relevant financial features.

Key columns include:





DATE: Date of the option quote (in YYYY-MM-DD format)




Strike Price: Strike price of the option




cp_flag: Option type — Call (c) or Put (p)




SP/CP: Ratio of spot price to strike price




r: Risk-free interest rate




time to maturity: Time to expiration (in years)




real_iv: Realized implied volatility (target variable)



 
description: This Python script processes the TSLA options dataset to train an LSTM (Long Short-Term Memory) neural network for forecasting implied volatility.

Key operations include:





Loading and preprocessing the data




Generating fixed-length time-series sequences (x) of 30-day windows using the following features:DATE, Strike Price, cp_flag, SP/CP, time to maturity




Constructing a supervised learning target y (next-day real_iv)




Splitting the data into training and testing sets




Scaling features using standard scaler




Defining and training a two-layer LSTM model using TensorFlow/Keras




Evaluating model performance using rmse,mae,R2



The code allows reproducibility of the full data transformation pipeline and provides a template for IV forecasting using deep learning on historical option data.
DOI: 10.5281/zenodo.15496947
title: Tesla option chain Data

description:  

This dataset contains preprocessed option data for Tesla Inc. (TSLA), curated for time-series modeling of implied volatility (IV). The dataset spans multiple strike prices and both call and put options. Each row corresponds to a unique combination of date, strike price, and option type, along with relevant financial features.

Key columns include:





DATE: Date of the option quote (in YYYY-MM-DD format)




Strike Price: Strike price of the option




cp_flag: Option type — Call (c) or Put (p)




SP/CP: Ratio of spot price to strike price




r: Risk-free interest rate




time to maturity: Time to expiration (in years)




real_iv: Realized implied volatility (target variable)



 
description: This Python script processes the TSLA options dataset to train an LSTM (Long Short-Term Memory) neural network for forecasting implied volatility.

Key operations include:





Loading and preprocessing the data




Generating fixed-length time-series sequences (x) of 30-day windows using the following features:DATE, Strike Price, cp_flag, SP/CP, time to maturity




Constructing a supervised learning target y (next-day real_iv)




Splitting the data into training and testing sets




Scaling features using standard scaler




Defining and training a two-layer LSTM model using TensorFlow/Keras




Evaluating model performance using rmse,mae,R2



The code allows reproducibility of the full data transformation pipeline and provides a template for IV forecasting using deep learning on historical option data.
DOI: 10.15468/dl.mpwmmf
title: Occurrence Download

description: A dataset containing 84372 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidium didymum L."
 ]
}

 The dataset includes 84372 records from 1026 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015767-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1290779.10fu
title: SH1290779.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.mkwvgr
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.22_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.22.9_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004291-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1290780.10fu
title: SH1290780.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290782.10fu
title: SH1290782.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290783.10fu
title: SH1290783.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290787.10fu
title: SH1290787.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25574/30608
title: Chandra X-ray Observatory ObsId 30608

description: Capturing the Collimation and True Energy of the Brightest Gamma-ray Burst, GRB 221009A
DOI: 10.15156/bio/sh1290788.10fu
title: SH1290788.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290789.10fu
title: SH1290789.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290790.10fu
title: SH1290790.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25574/30611
title: Chandra X-ray Observatory ObsId 30611

description: Capturing the Collimation and True Energy of the Brightest Gamma-ray Burst, GRB 221009A
DOI: 10.15156/bio/sh1290793.10fu
title: SH1290793.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1290794.10fu
title: SH1290794.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.