cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29485847.v2
title: Raw Data from Microsoft Forms Poll on Political Correctness, Political Orientation, and Left-Wing Authoritarianism in the UK.

description: Raw survey data from 485 UK residents (2025) exploring political correctness, political orientation, and left-wing authoritarianism. Collected via Microsoft Forms, the anonymised Excel dataset includes responses on PC attitudes, LWA scores, and demographics. Findings show LWA and liberal ideology predict PC, with LWA as the strongest mediator.
DOI: 10.3535/lfb-vzd-hb2
title: Ilia spinosa Miers, 1881

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/psr-8tc-m49
title: Micippa platipes Rüppell, 1830

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ypb-g5c-fsv
title: Euphausia pseudogibba Ortmann, 1893

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bk3-5rf-0kb
title: Palaemon serratus (Pennant, 1777)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/c56-fld-crg
title: Bathyporeia pilosa Lindström, 1855

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7mm-6ex-gk2
title: Leptochela (Leptochela) serratorbita Spence Bate, 1888

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vwk-fv9-4e3
title: Balanus

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/3j7-qrp-ws0
title: Bathynectes maravigna (Prestandrea, 1839)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/lsq-pz2-7nz
title: Caphyra loevis (A. Milne-Edwards, 1869)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v11-3h8-ers
title: Hyas araneus (Linnaeus, 1758)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bd8-zv8-v9c
title: Clibanarius tricolor (Gibbes, 1850)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wqd-kwq-2yv
title: Themisto compressa Goës, 1866

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/2nk-375-ckt
title: Orchestia gammarellus (Pallas, 1766)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/73p-av9-ks5
title: Marinogammarus marinus (Leach, 1816)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.71761/36bbf408-ab4d-4c84-aced-614827df0e0a
title: KIM Mooring ADCP data @ 200m

description: This dataset comprises measurements from a moored Acoustic Doppler Current Profiler (ADCP), collected by the Krossfjord Italian Mooring (KIM), which is managed by the Institute of Polar Sciences of the National Research Council (CNR). The data was gathered in the Krossfjord, Svalbard Island, since September 2020. This dataset come from a new sensor acquired in the context of the Italian PNRR project ITINERIS with the aim to increase observation of essential ocean variables. This dataset contribute to the SIOS-Svalbard Integrated Arctic Earth Observing System, developed to observe the impacts of climate change, including the rapid loss of sea ice cover, the retreat of local glaciers, and the Atlantification of Arctic seas. Measured properties are: subsurface temperature and currents along the water column. This ensures sustained data collection and further enhances our understanding of the observed environmental changes.
DOI: 10.3535/pec-gha-632
title: Penaeus penicillatus Alcock, 1905

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/zkr-skp-vg5
title: Gastrosaccus sanctus (Van Beneden, 1861)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bzy-c97-wsr
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/sn6-lk6-j9m
title: Porcellio scaber scaber Latreille, 1804

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ww5-byt-j1w
title: Nannocalanus minor (Claus, 1863)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.71761/edcfcfea-397e-4ea2-ac33-b4ed324440c0
title: KIM Mooring CTD data @ 120m

description: This dataset comprises measurements from a moored CTD instruments, collected by the Krossfjord Italian Mooring (KIM), which is managed by the Institute of Polar Sciences of the National Research Council (CNR). The data was gathered in the Krossfjord, Svalbard Island, since September 2020. This dataset is also part of the SIOS-Svalbard Integrated Arctic Earth Observing System, developed to observe the impacts of climate change, including the rapid loss of sea ice cover, the retreat of local glaciers, and the Atlantification of Arctic seas. Mesured properties: seawater pressure, temperature, conductivity, salinity, density, oxygen concentration. The acquisition of this time series data is still ongoing and will continue, bolstered by the inclusion of this infrastructure within the framework of the Italian PNRR project ITINERIS. This ensures sustained data collection and further enhances our understanding of the observed environmental changes.
DOI: 10.3535/gzt-qes-agt
title: Caridina cantonensis Yü, 1938

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/153-hgm-bzx
title: Systellaspis debilis (A. Milne-Edwards, 1881)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/jja-3x8-pfh
title: Alpheus cyanoteles Yeo & Ng, 1996

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.57702/pcxtyu3t
title: TID2013 Database

description: The TID2013 database contains 3000 distorted images generated by applying 24 distortion operations at 5 levels to 25 pristine images.
DOI: 10.57702/dyj1ohrk
title: AGD20K

description: The AGD20K dataset provides a collection of 20,061 images captured from a third-person perspective (exocentric) and 3,755 images from a first-person perspective (egocentric). These images are annotated with labels for 36 different affordances, which represent the potential object interactions.
DOI: 10.15468/dl.jaqr62
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sophora alopecuroides, Goebelia alopecuroides, Goebelia alopecuroides, Goebelia alopecuroides alopecuroides, Goebelia alopecuroides tomentosa, Pseudosophora alopecuroides, Pseudosophora alopecuroides, Radiusia alopecuroides, Sophora alopecuroides alopecuroides, Sophora alopecuroides jaubertii, Sophora alopecuroides prodanii, Sophora alopecuroides tomentosa, Sophora alopecuroides tomentosa, Sophora alopecuroides tomentosa, Sophora alopecuroides tomentosa, Sophora alopecuroides tomentosa, Vexibia alopecuroides, Vexibia alopecuroides, Vexibia alopecuroides alopecuroides, Vexibia alopecuroides tomentosa, Vexibia alopecuroides tomentosa, Vexibiai alopecuroides, Vexibiaii alopecuroides)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1970",
 "Year is less than or equal to 2024",
 "CoordinateUncertaintyInMeters is greater than or equal to 0",
 "CoordinateUncertaintyInMeters is less than or equal to 4500",
 "BasisOfRecord is one of (Human Observation, Observation, Specimen, Material sample, Living Specimen)"
 ]
}

 The dataset includes 237 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079880-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/vh0y5xi8
title: Deep information for learning and control

description: The dataset is used to test the proposed method for inferring representations of time series.
DOI: 10.57702/88a0wr1r
title: Network Data

description: Network data collected from smart home devices and IoT devices.
DOI: 10.57702/eup6zcgt
title: Rating Transition Model

description: Rating agencies publish these type of matrices usually once a year for a few time frames. Short-term rating matrices are usually published with time frames of 1, 3, 6, 12 months and long-term rating matrices with time frames of 1, 2, 3, 5, 10 years. We see a lot of uncertainty in the historical data published by the agencies increasing with larger time frames, which we will discuss in more details in Section 4.2.
DOI: 10.15468/dl.d7cgft
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.38269099999999 23.343858, 89.306207 23.338281, 89.23162499999999 23.321689, 89.160798 23.294495, 89.095484 23.257374, 89.03729800000001 23.211248, 88.98767700000001 23.157261, 88.947839 23.096751, 88.918756 23.031215, 88.90113100000001 22.962273, 88.895381 22.891626, 88.901629 22.821015, 88.919704 22.752178, 88.94914300000001 22.686804, 88.989211 22.626499, 89.038911 22.572738, 89.09701699999999 22.526839, 89.162103 22.489923, 89.232573 22.462891, 89.30670499999999 22.446403, 89.38269099999999 22.440862, 89.45867699999999 22.446403, 89.532809 22.462891, 89.603279 22.489923, 89.66836499999999 22.526839, 89.726471 22.572738, 89.77617100000001 22.626499, 89.816239 22.686804, 89.84567800000001 22.752178, 89.863753 22.821015, 89.870001 22.891626, 89.864251 22.962273, 89.846626 23.031215, 89.817543 23.096751, 89.777705 23.157261, 89.728084 23.211248, 89.669898 23.257374, 89.604584 23.294495, 89.53375699999999 23.321689, 89.459175 23.338281, 89.38269099999999 23.343858))"},{"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 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079879-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/hf9k0ctq
title: WU-Minn Human Connectome Project

description: The WU-Minn Human Connectome Project (HCP) dataset is used for training and quantitative comparison.
DOI: 10.57702/zd6nsetn
title: VLOG-People

description: VLOG-People dataset is used for training the model, and it contains videos of people performing various actions.
DOI: 10.57702/062y2eor
title: You2Me

description: A dataset for human motion synthesis, consisting of 3D human motion data and corresponding text descriptions.
DOI: 10.57702/lfif0eg0
title: Malware Detection Dataset

description: The dataset used in this paper is a large-scale regression dataset, containing 2,342,274 Portable Executable (PE) files, each represented with almost 100,000 features.
DOI: 10.57702/6qx4q89r
title: MART dataset

description: The MART dataset contains 500 art pieces by professional artists and 10 thousand ratings by 100 people (74 females, ages 18–65).
DOI: 10.57702/d3uanjrl
title: Self-supervised similarity models based on well-logging data

description: The dataset used in the paper is a collection of well logging data from various oil fields, including the Taranaki Basin, Petlab Science, and Norwegian offshore data.
DOI: 10.57702/x08fsfv4
title: LUT dataset for fuel performance analysis

description: The dataset used in this paper for look-up table (LUT) construction, including 8 essential fuel performance QoIs.
DOI: 10.57702/5899e2l4
title: Cancer2 benchmark

description: The Cancer2 benchmark is a dataset used to evaluate the performance of Bayesian network structure learning algorithms.
DOI: 10.57702/9o4922um
title: ICFHR2010 dataset

description: The ICFHR2010 dataset is a dataset of modern handwriting that is heterogeneous by document resolutions, text line heights and skews.
DOI: 10.57702/gph89wfi
title: New York City Taxi Network

description: The dataset is a collection of New York City taxi data, and the authors use it to demonstrate the utility of the hitting probability metric for structure detection, dimension reduction, and visualization.
DOI: 10.57702/k962uizr
title: HuMMan-MoGen

description: HuMMan-MoGen: A large-scale benchmark for fine-grained spatio-temporal motion generation and editing.
DOI: 10.57702/9v019kt1
title: TCGA datasets

description: The TCGA datasets are used as a baseline testing dataset for many developed methods, including the most relevant related work.
DOI: 10.15156/bio/sh0153715.10fu
title: SH0153715.10FU

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/sh0153716.10fu
title: SH0153716.10FU

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/sh0153717.10fu
title: SH0153717.10FU

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/sh0153718.10fu
title: SH0153718.10FU

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/sh0153719.10fu
title: SH0153719.10FU

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/sh0153720.10fu
title: SH0153720.10FU

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/sh0153721.10fu
title: SH0153721.10FU

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.wjd9kg
title: Occurrence Download

description: A dataset containing 1513275 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is IDN",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 2000-2026"
 ]
}

 The dataset includes 1513275 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000717-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0153722.10fu
title: SH0153722.10FU

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/sh0153723.10fu
title: SH0153723.10FU

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.