cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1139637.09fu
title: SH1139637.09FU

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/sh1139638.09fu
title: SH1139638.09FU

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/sh1139639.09fu
title: SH1139639.09FU

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/sh1139640.09fu
title: SH1139640.09FU

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/sh1139641.09fu
title: SH1139641.09FU

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/sh1139642.09fu
title: SH1139642.09FU

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: 10.6084/m9.figshare.22611482
title: Additional file 2 of Multi-omic interactions in the gut of children at the onset of islet autoimmunity

description: Additional file 2: Supplementary Table S1. Cohort characteristics. Supplementary Table S2. OTU associated with age. Supplementary Table S3. MOFA loadings contributing to latent factors 1-6 for model 1. Supplementary Table S4. MOFA loadings contributing to latent factors 1-8 for model 2. Supplementary Table S5. Top 20 loadings for latent factor 6 from model 2.
DOI: 10.6084/m9.figshare.22611482.v1
title: Additional file 2 of Multi-omic interactions in the gut of children at the onset of islet autoimmunity

description: Additional file 2: Supplementary Table S1. Cohort characteristics. Supplementary Table S2. OTU associated with age. Supplementary Table S3. MOFA loadings contributing to latent factors 1-6 for model 1. Supplementary Table S4. MOFA loadings contributing to latent factors 1-8 for model 2. Supplementary Table S5. Top 20 loadings for latent factor 6 from model 2.
DOI: 10.15156/bio/sh1139643.09fu
title: SH1139643.09FU

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/sh1139644.09fu
title: SH1139644.09FU

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/sh1139645.09fu
title: SH1139645.09FU

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/sh1139646.09fu
title: SH1139646.09FU

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: 10.21233/cnj8-qb40
title: Kipabiskau Lake ostracode surface sample dataset

description: Raw data for the Kipabiskau Lake ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/2ff1-2b69
title: LDDsite676 ostracode surface sample dataset

description: Raw data for the LDDsite676 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/0gez-qy36
title: LDDsite2053 water chemistry dataset

description: Raw data for the LDDsite2053 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.15468/y98bvh
title: - A-new-harvestman-species-of-the-genus-Graecophalangium-Roewer, - 1923 (Arachnida: - Opiliones: - Phalangiidae) - from-Turkey-

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tchemeris, Aleksey N. (2021): - A-new-harvestman-species-of-the-genus-Graecophalangium-Roewer, - 1923 (Arachnida: - Opiliones: - Phalangiidae) - from-Turkey-. Zootaxa 5081 (1): 141-150, DOI: https://doi.org/10.11646/zootaxa.5081.1.6
DOI: 10.21233/vx4g-mf53
title: Lenora Lake ostracode surface sample dataset

description: Raw data for the Lenora Lake ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/nbx6-c341
title: LDDsite1027 water chemistry dataset

description: Raw data for the LDDsite1027 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/e3kq-w754
title: LDDsite708 water chemistry dataset

description: Raw data for the LDDsite708 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/hs7z-5931
title: Little Joe Lake ostracode surface sample dataset

description: Raw data for the Little Joe Lake ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/0935-sd50
title: Oxtongue Lake water chemistry dataset

description: Raw data for the Oxtongue Lake water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/f50q-vv04
title: LDDsite2076 ostracode surface sample dataset

description: Raw data for the LDDsite2076 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/bnb1-am71
title: LDDsite954 ostracode surface sample dataset

description: Raw data for the LDDsite954 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/7kk4-9476
title: LDDsite2083 water chemistry dataset

description: Raw data for the LDDsite2083 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/ey95-fw25
title: Pine Creek water chemistry dataset

description: Raw data for the Pine Creek water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/kfwe-ck14
title: LDDsite767 water chemistry dataset

description: Raw data for the LDDsite767 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/z40m-4274
title: Barrier Lake water chemistry dataset

description: Raw data for the Barrier Lake water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/tkjm-qp26
title: LDDsite954 water chemistry dataset

description: Raw data for the LDDsite954 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/86kn-t113
title: Kipabiskau River water chemistry dataset

description: Raw data for the Kipabiskau River water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/q1wj-jz97
title: LDDsite2116 water chemistry dataset

description: Raw data for the LDDsite2116 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/qc37-fn67
title: LDDsite2119 water chemistry dataset

description: Raw data for the LDDsite2119 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/5enk-7v89
title: LDDsite2139 ostracode surface sample dataset

description: Raw data for the LDDsite2139 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/qwta-dp45
title: LDDsite2141 water chemistry dataset

description: Raw data for the LDDsite2141 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/jf0n-gg91
title: Lake St. Joseph ostracode surface sample dataset

description: Raw data for the Lake St. Joseph ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/xd16-4k37
title: Wood River water chemistry dataset

description: Raw data for the Wood River water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/gg3e-2c94
title: LDDsite2158 ostracode surface sample dataset

description: Raw data for the LDDsite2158 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/wa53-3a37
title: LDDsite2180 water chemistry dataset

description: Raw data for the LDDsite2180 water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/vrbz-y571
title: Castor Creek water chemistry dataset

description: Raw data for the Castor Creek water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/g97a-ny79
title: LDDsite2437 ostracode surface sample dataset

description: Raw data for the LDDsite2437 ostracode surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.5281/zenodo.5750549
title: Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Sint-Katelijne-Waver, Belgium

description: Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Sint-Katelijne-Waver (51°3'25"N 4°11'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).
description: This work was supported by Research Foundation Flanders (FWO) [1S97418N] and is part of the Ph.D. research 'Towards future-proof buildings in Flanders: Climate and Life Cycle modelling for resilient office buildings'. The climate model data used is the result of the CORDEX.be project funded by the Belgian federal government (Belgian Science Policy Office project BR/143/A2/CORDEX.be) and can be requested via nicole.vanlipzig@kuleuven.be. Computational resources for these integrations were provided by the VSC (Flemish Supercomputer Centre), funded by the Research Foundation – Flanders (FWO) and the Flemish Government - department EWI. The hourly observational data for the bias correction were provided by RMI (Belgian Royal Meteorological Institute).
description: {"references": ["Ramon, D., Allacker, K., De Troyer, F., Wouters, H., & van Lipzig, N. P. (2020). Future heating and cooling degree days for Belgium under a high-end climate change scenario. Energy and Buildings, 216, 109935.", "Nik, V. M. (2016). Making energy simulation easier for future climate\u2013Synthesizing typical and extreme weather data sets out of regional climate models (RCMs). Applied Energy, 177, 204-226.", "H. Wouters, M. Demuzere, U. Blahak, K. Fortuniak, B. Maiheu, J. Camps, D. Tielemans, N.P.M. Van Lipzig, The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: Description and application with the COSMO-CLM model for a Belgian summer, Geosci. Model Dev. 9 (2016) 3027\u20133054. doi:10.5194/gmd-9-3027-2016.", "S. Vanden Broucke, H. Wouters, M. Demuzere, N.P.M. van Lipzig, The influence of convection-permitting regional climate modeling on future projections of extreme precipitation: dependency on topography and timescale, Clim. Dyn. (2019). doi:10.1007/s00382-018-4454-2.", "Ramon, D., Allacker K. (202X) Integrated assessment method for climate resilient buildings: framework and application on a Flemish office building. In preparation."]}
DOI: 10.5281/zenodo.5750548
title: Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Sint-Katelijne-Waver, Belgium

description: Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Sint-Katelijne-Waver (51°3'25"N 4°11'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).
description: This work was supported by Research Foundation Flanders (FWO) [1S97418N] and is part of the Ph.D. research 'Towards future-proof buildings in Flanders: Climate and Life Cycle modelling for resilient office buildings'. The climate model data used is the result of the CORDEX.be project funded by the Belgian federal government (Belgian Science Policy Office project BR/143/A2/CORDEX.be) and can be requested via nicole.vanlipzig@kuleuven.be. Computational resources for these integrations were provided by the VSC (Flemish Supercomputer Centre), funded by the Research Foundation – Flanders (FWO) and the Flemish Government - department EWI. The hourly observational data for the bias correction were provided by RMI (Belgian Royal Meteorological Institute).
description: {"references": ["Ramon, D., Allacker, K., De Troyer, F., Wouters, H., & van Lipzig, N. P. (2020). Future heating and cooling degree days for Belgium under a high-end climate change scenario. Energy and Buildings, 216, 109935.", "Nik, V. M. (2016). Making energy simulation easier for future climate\u2013Synthesizing typical and extreme weather data sets out of regional climate models (RCMs). Applied Energy, 177, 204-226.", "H. Wouters, M. Demuzere, U. Blahak, K. Fortuniak, B. Maiheu, J. Camps, D. Tielemans, N.P.M. Van Lipzig, The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: Description and application with the COSMO-CLM model for a Belgian summer, Geosci. Model Dev. 9 (2016) 3027\u20133054. doi:10.5194/gmd-9-3027-2016.", "S. Vanden Broucke, H. Wouters, M. Demuzere, N.P.M. van Lipzig, The influence of convection-permitting regional climate modeling on future projections of extreme precipitation: dependency on topography and timescale, Clim. Dyn. (2019). doi:10.1007/s00382-018-4454-2.", "Ramon, D., Allacker K. (202X) Integrated assessment method for climate resilient buildings: framework and application on a Flemish office building. In preparation."]}