cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0182359.10fu
title: SH0182359.10FU

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/sh0182360.10fu
title: SH0182360.10FU

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/sh0182361.10fu
title: SH0182361.10FU

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/sh0182362.10fu
title: SH0182362.10FU

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/sh0182363.10fu
title: SH0182363.10FU

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/sh0182364.10fu
title: SH0182364.10FU

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/sh0182365.10fu
title: SH0182365.10FU

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/sh0182366.10fu
title: SH0182366.10FU

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/sh0182367.10fu
title: SH0182367.10FU

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/sh0182368.10fu
title: SH0182368.10FU

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: 10.17183/mnt_cotier_gnb_papi_sm_20m_wgs84
title: MNT topo-bathymétrique côtier d'une partie du golfe normand-breton (PAPI Saint-Malo)

description: Le MNT topo-bathymétrique côtier d'une partie du golfe normand-breton à une résolution de 0.0002° (~ 20 m) a été réalisé dans le cadre du PAPI Saint-Malo. Le MNT englobe le plateau des Minquiers au Nord-Ouest jusqu'à la baie du Mont-Saint-Michel au Sud-Est. Le MNT est destiné à être implémenté dans les modèles hydrodynamiques afin de produire des prévisions aussi précises que possible des hauteurs d’eau et d’états de mer à la côte et donc d’améliorer la gestion du risque de submersion marine.
DOI: 10.17632/z6dfjh596r.1
title: WheelSimPhysio-2023

description: WheelSimPhysio-2023 dataset with implicit, explicit and performance data. The Implicit is the physiological responses throughout all the states of the experiment. Explicit measures are questionnaires and rating scales collected via the post-experience feedback phase. The performance metrics included joystick events, time to complete and the number of collisions that were captured inside the application. These metrics are widely used in the Quality of Experience evaluations.
DOI: 10.5067/omgev-axctd
title: OMG Ocean CTD Data
DOI: 10.17632/ph5bshx89v.1
title: Dataset - seasonal variability of carbonate chemistry in the Arctic Chukchi Sea shelf

description: This dataset describes the seasonal variability of carbonate chemistry in the Arctic Chukchi Sea shelf in 2008, 2010, 2014, 2016, and 2018. The dataset includes cruise number, sampling year, station, longitude, latitude, depth, temperature, salinity, dissolved inorganic carbon, total alkalinity, and calculated pH and aragonite saturation state.
DOI: 10.5281/zenodo.11187857
title: Data and code for Rowan et al. "Long-term biotic homogenization in the East African Rift System over the last 6 Myr of hominin evolution"

description: Data and code for Rowan et al. "Long-term biotic homogenization in the East African Rift System over the last 6 Myr of hominin evolution" published in Nature Ecology and Evolution.
DOI: 10.5281/zenodo.7988098
title: Estuarine hurricane wind and Delaware Bay and River extreme water level

description: DHSVM and FVCOM model datasets used in the result analysis of the manuscript article "Estuarine hurricane wind can intensify surge-dominated coastal and riverine extreme water level"
DOI: 10.5281/zenodo.7963514
title: Instances and Cutting schemes of CAOR-D-22-01050

description: Instances and Cutting schemes of CAOR-D-22-01050
DOI: 10.17183/campagne_oceano_stmalo
title: Campagne océanographique in situ aux abords de Saint Malo (Shom)
title: In situ oceanographic campaign around Saint Malo (Shom)

description: À l’initiative de Saint-Malo Agglomération (SMA), un Programme d’Actions pour la Prévention des Inondations (PAPI) d’intention a été mis en place. Son axe 2 s’intéresse à l’amélioration de la connaissance des phénomènes météo-marins pouvant conduire à des submersion marine (hauteurs d’eau, états de mer et courants). Pour y répondre, le Shom a conduit une campagne océanographique d’envergure, dans la baie de Saint-Malo, durant l’hiver 2018-2019, en parallèle d’une campagne bathymétrique. Des données de courants, de vagues et de hauteur d’eau, ont été acquises à l’aide d’un réseau de 22 mouillages, pour un total de 37 instruments, dont 18 capteurs de pression, 7 profileurs de courant, 4 profileurs de courant houlographe, 4 courantomètres ponctuels, 2 marégraphes et 2 bouées houlographiques. Cette base de données contient l’ensemble du jeu de données acquis avec trois niveau de traitement : L0 (sortie directe des capteurs au format binaire ou ascii), L1 (données prétraitées à l'aide du logiciel du fabricant au format ascii), L2 (données traitées et métadonnées au format NetCDF). Les données océanographiques traitées ont été tracées pour un contrôle visuel de qualité et sont disponibles en tant que "quick looks" sur le dépôt.
DOI: 10.5281/zenodo.10816330
title: Potential Ozone Depletion from Satellite Demise during Atmospheric Reentry in the Era of Mega-Constellations

description: Dataset support to "Potential Ozone Depletion from Satellite Demise during Atmospheric Reentry in the Era of Mega-Constellations"
DOI: 10.6084/m9.figshare.26554142
title: Additional file 7 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 7: Supplementary file 6. Species-wise amino acid composition of chloroplast proteomes.
DOI: 10.15468/dl.x44nun
title: Occurrence Download

description: A dataset containing 945 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron calophytum Franch."
 ]
}

 The dataset includes 945 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063868-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26554136
title: Additional file 5 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 5: Supplementary file 4. Percent abundance of acidic and basic pI proteins in chloroplast proteomes.
DOI: 10.6084/m9.figshare.26554136.v1
title: Additional file 5 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 5: Supplementary file 4. Percent abundance of acidic and basic pI proteins in chloroplast proteomes.
DOI: 10.6084/m9.figshare.26554130
title: Additional file 3 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 3: Supplementary file 2. Amino acid counts per proteome in chloroplast proteomes.
DOI: 10.6084/m9.figshare.26554142.v1
title: Additional file 7 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 7: Supplementary file 6. Species-wise amino acid composition of chloroplast proteomes.
DOI: 10.15468/dl.vznb5b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.78722 -33.206916, 148.78722 -33.209162, 148.791712 -33.209162, 148.791712 -33.206916, 148.78722 -33.206916))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063869-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26554133
title: Additional file 4 of Decoding the Virtual 2D Map of the Chloroplast Proteomes

description: Additional file 4: Supplementary file 3. Lineage-specific molecular mass (kDa) of chloroplast proteomes.
DOI: 10.5281/zenodo.10183948
title: Supplementary material for: Coral reef potential connectivity in the southwest Indian Ocean

description: Supplementary datasets and scripts for Coral reef potential connectivity in the southwest Indian Ocean. Please see the readme!
DOI: 10.17632/7wwmwj9rzk.1
title: Forest carbon supplementary data

description: Row data and software output
DOI: 10.5281/zenodo.10866260
title: Great Britain Primary Substation Datasets

description: The growing demand for electrified heating, electrified transportation, and power-intensive data centres challenge distribution networks. If electrification projects are carried out without considering electrical distribution infrastructure, there could be unexpected blackouts and financial losses. Datasets containing real-world distribution network information are required to address this. On the other hand, social data, such as household heating composition, are closely coupled with people’s lives. Studying the coupling between the energy system and society is important in promoting social welfare. To fill these gaps, this paper introduces two datasets. The first is the main dataset for the distribution networks in Great Britain (GB), collecting information on firm capacity, peak demands, locations, and parent transmission nodes (the Grid Supply Point, namely GSP) for all primary substations (PSs). PSs are a crucial part of the UK distribution network and are at the lowest voltage level (11 kV) with publicly available data for most UK Distribution Network Operators (DNOs). Substation firm capacity and peak demand facilitate an understanding of the remaining room of the existing network. The parent GSP information helps link the dataset of distribution networks to datasets of transmission networks. These datasets are collected, processed, and merged from various files published by the six DNOs in GB. There were inconsistencies among the PS names across files even for the same DNO. A Python script and manual validation are performed to carefully process and merge the corresponding PS information. The second dataset extends the main network dataset, linking each PS to information about the number of households that use different types of central heating recorded in census data (Census in year 2021 for England and Wales, and Census 2011 for Scotland as the most recent Scotland Census 2022 data has not yet been fully released). The derivation of the second dataset is based on locations of PSs collected in the main dataset with appropriate assumptions. The derivation process may also be replicated to integrate other social datasets.

 

If you are interested and would like to use this dataset. Please cite our paper:

Zhou, Yihong, Chaimaa Essayeh, and Thomas Morstyn. "Datasets of Great Britain Primary Substations Integrated with Household Heating Information." Data in Brief (2024): 110483. https://doi.org/10.1016/j.dib.2024.110483.

The paper encloses a detailed description of all the files and methods for processing and deriving our data. The paper above also describes the values, applications, possible extensions, and limitations of the released datasets.
DOI: 10.5281/zenodo.8359619
title: Digital Elevation Model of Hintereis- and Kesselwandferner 08.10.2010

description: DTM_RegionHintereis_2010_r1.tif: DEM of Hintereis- and Kesselwandferner, acquisition date 08.10.2010 by airborne laser scan (ALS), cellsize 1x1 m, UTM WGS84, ellipsoid heights<br> DTM_RegionHintereis_2010_r1_gc.tif: Same as above but corrected for geoid heights. These DEMs are a 1x1 m version of the 10x10 m DEM from 08.10.2010 available on https://doi.org/10.1594/PANGAEA.875889 Reference: Bollmann et al. 2015: https://onlinelibrary.wiley.com/doi/10.1002/ppp.1852 Data Source / Acknowledgement: The ALS data were provided by the Institute of Geography, University of Innsbruck, Austria, financed by the project ‘Multiscale Snow/Icemelt Discharge Simulation into Alpine Reservoirs’ (MUSICALS).
DOI: 10.5281/zenodo.12620977
title: Regional Assessments of Glacier Mass Change (RAGMAC) experiment dataset

description: This repository contains the dataset that was distributed to the participants of the Regional Assessments of Glacier Mass Change (RAGMAC) workinggroup of the International Association of Cryospheric Science (IACS, 2023).

In short, the dataset is divided in 5 study sites: Hintereisferner (Austrian Alps - HEF_AT), Grosser Aletschgletscher (Swiss Alps - ALE_CH), Vestre Svartisen ice cap (Scandes, Norway - VES_NO), Baltoro glacier (Karakoram, Pakistan - BAL_PK), and the Northern Patagonian Icefield (Andes, Chile - NPI_CL).

For each site, we provide series of Digital Elevation Models (DEMs) derived from SRTM, ASTER and TanDEM-X sensors. Additionally, we provide glacier outlines extracted from the Randolph Glacier Inventory version 6, for all glaciers in the study area, and selected glaciers for which participants were required to calculate the geodetic mass balance.

Additionally, we provide the airborne DEMs that were used as reference data to evaluate the spaceborne DEMs. These are available for the cases HEF_AT, ALE_CH and VES_NO, all included in the single zip file “validation_data.zip”.

For details on the dataset, experiment and any reference to this dataset, please refer to the following publication: Piermattei et al. (2024) "Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data" The Cryosphere, DOI: 10.5194/egusphere-2023-2309 (to be updated upon final acceptance).

NOTE: As of July 2024, the TanDEM-X DEMs cannot be publicly shared due to license restrictions. We are discussing future opportunities to share the data in a future version of this repository.