cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0203402.10fu
title: SH0203402.10FU

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/sh0203403.10fu
title: SH0203403.10FU

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/sh0203404.10fu
title: SH0203404.10FU

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/sh0203405.10fu
title: SH0203405.10FU

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/sh0203406.10fu
title: SH0203406.10FU

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.kvznnb
title: Occurrence Download

description: A dataset containing 266044 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "OccurrenceStatus is Present",
 "TaxonKey is Phascolarctos cinereus"
 ]
}

 The dataset includes 266044 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042759-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/1nhq-931w-cx0v
title: EPIC: GOES-East 1km Visible Channel TDF Data. Version 1.0

description: The GOES-8 Satellite data is at 1 kilometer. The data cover the period from 1 September2001 to 15 October 2001. That data are in tdf format.
DOI: 10.34740/kaggle/dsv/13249078
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.15468/dl.r9v8rk
title: Occurrence Download

description: A dataset containing 271 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-3.60508 40.02895,-3.60391 40.02895,-3.60391 40.03088,-3.60508 40.03088,-3.60508 40.02895))"
 ]
}

 The dataset includes 271 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042814-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zxeksf
title: Occurrence Download

description: A dataset listing the 130 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.76705 40.50271,-3.75026 40.50271,-3.75026 40.51056,-3.76705 40.51056,-3.76705 40.50271))",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset's 130 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042785-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5284/1133051
title: Digital Archive from an Archaeological Evaluation at The Old Plough, High Green, Abbotsley, Cambridgeshire, February 2023

description: This collection consists of site images, a CAD vector drawing, and report from an archaeological evaluation at The Old Plough, High Green, Abbotsley, Cambridgehsire. Works were conducted by Albion Archaeology in February 2023.
The majority of the identified remains are likely associated with previous use as a car park, with hardcore make-up layers and drainage provided by land drains and soakaways. It is clear from surrounding ground levels that the level of the area has been significantly reduced during construction of the car park, particularly in its eastern and southern parts. This is likely to have destroyed the majority of any archaeological remains that might otherwise have survived.
DOI: 10.15468/dl.qz5qwg
title: Occurrence Download

description: A dataset containing 354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.76394 40.41143,-3.72903 40.41143,-3.72903 40.43142,-3.76394 40.43142,-3.76394 40.41143))",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 354 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042815-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vj8x4r
title: Occurrence Download

description: A dataset containing 2266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gloeophyllum abietinum"
 ]
}

 The dataset includes 2266 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042817-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y6rd9p
title: Occurrence Download

description: A dataset containing 1019 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Gentiana rhodantha"
 ]
}

 The dataset includes 1019 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042818-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eg99cs
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tulipa platystemon"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042820-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/p673-p1nt-ry0j
title: EPIC: GOES-East 4km Multi-Spectral Channel TDF Data. Version 1.0

description: The GOES-8 Satellite data is at 4 kilometers. The data cover the period from 1 September 2001 to 15 October 2001. That data are in tdf format.
DOI: 10.15468/dl.s422wm
title: Occurrence Download

description: A dataset containing 3656 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2016",
 "Geometry POLYGON ((14.53347 44.4911, 14.51584 44.5125, 14.50417 44.5225, 14.48972 44.52666, 14.47666 44.53583, 14.42639 44.58166, 14.41611 44.59222, 14.40722 44.60388, 14.39542 44.62653, 14.39389 44.65943, 14.39542 44.67722, 14.39195 44.68985, 14.38277 44.69694, 14.33805 44.70674, 14.34777 44.65527, 14.3675 44.59028, 14.51111 44.47417, 14.51667 44.47333, 14.52597 44.47569, 14.53347 44.4911))"
 ]
}

 The dataset includes 3656 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042816-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34760/6800d78bd68ec
title: COVID HOME
title: Prospective cohort study of non-hospitalised COVID-19 patients

description: General Design

Type: Cohort study
Cohort type: Population cohort

Design description:
A prospective longitudinal observational study of COVID-19 outpatients was established in March 2020 at the beginning of the COVID-19 pandemic in the Netherlands. Laboratory confirmed SARS-CoV-2 infected individuals of all ages that did not merit hospitalisation, and their household (HH) members, were enrolled after written informed consent. Enrolled participants were visited at home within 48 hours after initial diagnosis, and then weekly on days 7, 14 and 21 to obtain clinical data, a blood sample for biochemical parameters/cytokines and serological determination; and a nasopharyngeal/throat swab plus urine, stool and sperm or vaginal secretion (if consenting) to test for SARS-CoV-2 by RT-PCR (viral shedding) and for viral culturing. Weekly nasopharyngeal/throat swabs and stool samples, plus a blood sample on days 0 and 21 were also taken from HH members to determine whether and when they became infected. All participants were invited to continue follow-up at 3-, 6-, 12- and 18-months post-infection to assess long-term sequelae and immunological status. 

Start/End data collection: 2020 until 2024

Population

Countries: Netherlands (the)
Regions: Drenthe, Friesland, Groningen
Number of participants: 270
Population age groups: All ages
Other inclusion criteria: 
"Onset of symptoms <5 days before inclusion, Positive diagnostic RT-PCR for SARS-CoV-2 performed within 48h of inclusion, Index person should supply all required samples in the protocol for the duration of the study, All HH members should join the study, Signing of informed consent form"
description: Longitudinal COVID-19 population cohort that was initiated during the COVID-19 pandemic in 2020 and continued until 2024. Enrolled participants were visited at home within 48-hours of diagnoses and followed-up over the next three weeks to collect clinical data, blood, nasal swaps, and other biological samples.
DOI: 10.15468/dl.m9ygw9
title: Occurrence Download

description: A dataset containing 418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "Geometry POLYGON((-3.11403 40.17924,-3.09811 40.17924,-3.09811 40.18816,-3.11403 40.18816,-3.11403 40.17924))",
 "HasCoordinate is true",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 418 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042821-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r3e5um
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helicella itala",
 "Country is Norway",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042824-250920141307145/datasets/export for details.
DOI: 10.26023/3cwg-xcy8-aw0s
title: EPIC: GOES-West 1km Visible Channel TDF Data. Version 1.0

description: The GOES-10 Satellite data is at 1 kilometer. The data cover the period from 1 September 2001 to 15 October 2001. That data are in tdf format.
DOI: 10.25413/sun.12173886
title: A probabilistic hot water usage model and simulator for use in residential energy management

description: Water heating contributes up to 40% of a household’s total electricity usage and places a substantial burden on the electricity grid due to high power ratings and users’ largely simultaneous hot water usage. The main determinants of its electricity draw are physical properties such as set temperature, insulation, and plumbing configuration; environmental conditions such as ambient temperature and inlet temperature; and the hot water usage profiles. These profiles include the usage volumes, the times of usage and the outlet temperatures. The efficacy of energy management techniques that model water heaters and the accuracy of their simulation results therefore rely on representative hot water usage profiles. Existing models for household hot water usage neglect differences between users, and temporal variations such as the season and the day of the week, and are not fully autonomous. We propose a probabilistic data-driven model for modelling individualised hot water profiles and an accompanying hot water usage simulator that includes all these factors. We gathered data from 77 residential households over a period of one year to train and evaluate the model for all four seasons. The results show that the simulated hot water usage profiles match the statistical properties of the measured data. Moreover, the individual hot water usage modelling and the resulting aggregated energy load on the grid closely match the measured data, improving on the existing hot water usage by halving the modelling error.
DOI: 10.15468/dl.6xj7qv
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.78939 40.48934,-3.76725 40.48934,-3.76714 40.50047,-3.78939 40.50052,-3.78939 40.48934))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042825-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25413/sun.12173886.v3
title: A probabilistic hot water usage model and simulator for use in residential energy management

description: Water heating contributes up to 40% of a household’s total electricity usage and places a substantial burden on the electricity grid due to high power ratings and users’ largely simultaneous hot water usage. The main determinants of its electricity draw are physical properties such as set temperature, insulation, and plumbing configuration; environmental conditions such as ambient temperature and inlet temperature; and the hot water usage profiles. These profiles include the usage volumes, the times of usage and the outlet temperatures. The efficacy of energy management techniques that model water heaters and the accuracy of their simulation results therefore rely on representative hot water usage profiles. Existing models for household hot water usage neglect differences between users, and temporal variations such as the season and the day of the week, and are not fully autonomous. We propose a probabilistic data-driven model for modelling individualised hot water profiles and an accompanying hot water usage simulator that includes all these factors. We gathered data from 77 residential households over a period of one year to train and evaluate the model for all four seasons. The results show that the simulated hot water usage profiles match the statistical properties of the measured data. Moreover, the individual hot water usage modelling and the resulting aggregated energy load on the grid closely match the measured data, improving on the existing hot water usage by halving the modelling error.
DOI: 10.15468/dl.qawfyw
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helicella itala",
 "Country is Denmark",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042823-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9kwsbq
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Helicella itala",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042826-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybrjaa
title: Occurrence Download

description: A dataset containing 8170 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2016",
 "Geometry POLYGON ((14.41889 44.99304, 14.41 45.00472, 14.37694 45.0525, 14.35889 45.10111, 14.35389 45.11916, 14.35805 45.13611, 14.36639 45.14659, 14.36361 45.16055, 14.35306 45.1668, 14.31763 45.17541, 14.30875 45.17014, 14.27479 45.12187, 14.27527 45.10334, 14.30806 45.07305, 14.3175 45.06597, 14.34111 45.05667, 14.35361 45.04514, 14.3925 44.95611, 14.39718 44.91159, 14.36208 44.90736, 14.34139 44.91611, 14.33139 44.84972, 14.38944 44.695, 14.45111 44.62639, 14.48389 44.60777, 14.48806 44.60583, 14.49334 44.60639, 14.5168 44.61403, 14.53014 44.63368, 14.50639 44.67083, 14.47055 44.74056, 14.45945 44.8275, 14.42639 44.98472, 14.41889 44.99304))"
 ]
}

 The dataset includes 8170 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042827-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15470/jurozi
title: Herbario MAIA, colecci?n de Eucalyptus del ICIFOR-INIA (CSIC)

description: El Herbario MAIA tiene su origen en las colecciones del antiguo Instituto Forestal de Investigaciones y Experiencias (1929). Est? ordenado seg?n el sistema filogen?tico de clasificaci?n de plantas de Adolf Engler. Contiene fundamentalmente ?rboles, arbustos y especies herb?ceas recogidas en los bosques y pastizales naturales de Espa?a.
Es un herbario hist?rico fundado en 1940 y actualmente adscrito al Instituto de Ciencias Forestales (ICIFOR) del Instituto Nacional de Investigaci?n y Tecnolog?a Agraria y Alimentaria (CSIC-INIA).
El herbario est? compuesto principalmente por la colecci?n de taxones del genero Eucalyptus, ligados a los trabajos del Mapa Forestal de Espa?a.
La colecci?n MAIA-Euc esta dedicada al g?nero Eucalyptus. Contiene 590 pliegos de 126 taxones espec?ficos de este g?nero ?o afines- cultivados en Espa?a.
DOI: 10.15468/dl.zcpn7z
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-3.60478 40.03162,-3.60238 40.03162,-3.60238 40.03271,-3.60478 40.03271,-3.60478 40.03162))"
 ]
}

 The dataset includes 180 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042828-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rqtgnn
title: Occurrence Download

description: A dataset containing 225 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.60124 40.37531,-3.60065 40.37555,-3.60307 40.38697,-3.62173 40.39078,-3.62441 40.38181,-3.60124 40.37531))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 225 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042830-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/6mkv-e4a0-h90w
title: EPIC: GOES-West 4km Multi-Spectral Channel TDF Data. Version 1.0

description: The GOES-10 Satellite data is at 4 kilometers. The data cover the period from 1 September 2001 to 15 October 2001. That data are in tdf format.