cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh384637.07fu
title: SH384637.07FU

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/sh1750361.08fu
title: SH1750361.08FU

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/sh1750362.08fu
title: SH1750362.08FU

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/sh384638.07fu
title: SH384638.07FU

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/sh384639.07fu
title: SH384639.07FU

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/sh1750363.08fu
title: SH1750363.08FU

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: 10.21258/1663860
title: Inventario forestale nazionale svizzero - Tabella n. 896901
DOI: 10.21258/1641792
title: Inventario forestale nazionale svizzero - Tabella n. 898372
DOI: 10.21258/1636939
title: Inventario forestale nazionale svizzero - Tabella n. 897601
DOI: 10.5281/zenodo.4346585
title: Mining Detailed Information from Description for App functions comparison

description: The corresponding Dataset and Source-Code for the paper named "Mining Detailed Information from Description for App functions comparison"
DOI: 10.21258/1666380
title: Inventario forestale nazionale svizzero - Tabella n. 893446
DOI: 10.5281/zenodo.4346584
title: Mining Detailed Information from Description for App functions comparison

description: The corresponding Dataset and Source-Code for the paper named "Mining Detailed Information from Description for App functions comparison"
DOI: 10.21258/1669926
title: Inventario forestale nazionale svizzero - Tabella n. 892056
DOI: 10.21258/1630989
title: Inventario forestale nazionale svizzero - Tabella n. 891991
DOI: 10.21258/1641849
title: Inventario forestale nazionale svizzero - Tabella n. 898248
DOI: 10.21258/1642842
title: Inventario forestale nazionale svizzero - Tabella n. 891834
DOI: 10.21258/1658299
title: Inventario forestale nazionale svizzero - Tabella n. 891980
DOI: 10.21258/1639015
title: Inventario forestale nazionale svizzero - Tabella n. 899090
DOI: 10.21258/1669174
title: Inventario forestale nazionale svizzero - Tabella n. 897252
DOI: 10.21258/1642737
title: Inventario forestale nazionale svizzero - Tabella n. 897499
DOI: 10.21258/1665670
title: Inventario forestale nazionale svizzero - Tabella n. 896991
DOI: 10.21258/1658016
title: Inventario forestale nazionale svizzero - Tabella n. 899417
DOI: 10.21258/1671283
title: Inventario forestale nazionale svizzero - Tabella n. 902236
DOI: 10.21258/1669762
title: Inventario forestale nazionale svizzero - Tabella n. 898798
DOI: 10.21258/1670333
title: Inventario forestale nazionale svizzero - Tabella n. 902057
DOI: 10.21258/1630608
title: Inventario forestale nazionale svizzero - Tabella n. 897542
DOI: 10.21258/1651855
title: Inventario forestale nazionale svizzero - Tabella n. 902103
DOI: 10.25919/hanx-b832
title: Parkes pulsar observations with undefined project IDs for 2020_16

description: Parkes pulsar observations with undefined project IDs for 2020. This collection contains data from the ToO project PX062.
DOI: 10.6084/m9.figshare.13237076
title: DepMap 20Q4 Public

description: This dataset contains the results of Avana library CRISPR-Cas9 genome-scale knockout (prefixed with Achilles) as well as mutation, copy number and gene expression data (prefixed with CCLE) for cancer cell lines as part of the Broad Institute’s Cancer Dependency Map project. We have repackaged our fileset to include all quarterly-updating datasets produced by DepMap.<br>The Avana CRISPR-Cas9 genome-scale knockout data has expanded to include 808 cell lines, the RNAseq data includes 1376 cell lines, and the copy number data includes 1753 cell lines. Please see the README files for details regarding data processing pipeline procedures updates.<br>As our screening efforts continue, we will be releasing additional cancer dependency data on a quarterly basis for unrestricted use. For the latest datasets available, further analyses, and to subscribe to our mailing list visit https://depmap.org.<br>Descriptions of the experimental methods and the CERES algorithm are published in http://dx.doi.org/10.1038/ng.3984. Some cell lines were process using copy number data based on the Sanger Institute whole exome sequencing data (COSMIC: http://cancer.sanger.ac.uk.cell_lines, EGA accession number: EGAD00001001039) reprocessed using CCLE pipelines. A detailed description of the pipelines and tool versions for CCLE expression can be found here: https://github.com/broadinstitute/gtex-pipeline/blob/v9/TOPMed_RNAseq_pipeline.md.<br>v2 changes: The README file in version 1 for the Expression pipeline. Version 2 corrects this.<br>v3 changes: We have discovered several issues in the DepMap 20Q4 copy number data, described at https://forum.depmap.org/t/important-update-issues-with-depmap-20q4-data/344. These issues also affected the CRISPR (Avana) 20Q4 CERES data, which is dependent on copy number information. This version reverts the affected files to their previous versions which does not have these issues.<br>v4 changes:We have discovered additional issues with several of the gene expression files in the 20Q4 dataset which we will correct shortly. The issues, described in more detail below, affected the files CCLE_expression_full, CCLE_RNAseq_reads, and CCLE_RNAseq_transcripts. Note that these issues are independent of the problems with the copy number pipeline described above. Hence, these files were not reverted to their previous versions, and we are correcting them in the 20Q4 dataset.<br>CCLE_expression_full and CCLE_RNAseq_reads: Underlying datasets were swapped.<br>CCLE_RNAseq_transcripts: Data for the cell line ACH-000561 was incorrectly normalized in this dataset. <br>Note that, starting in 20Q4, the expression datasets use log(x+1) transformation for all TPM values (including now the CCLE_RNAseq_transcripts file), and no transformation for expected counts. See README for more details.<br>
DOI: 10.6084/m9.figshare.13237076.v3
title: DepMap 20Q4 Public

description: This dataset contains the results of Avana library CRISPR-Cas9 genome-scale knockout (prefixed with Achilles) as well as mutation, copy number and gene expression data (prefixed with CCLE) for cancer cell lines as part of the Broad Institute’s Cancer Dependency Map project. We have repackaged our fileset to include all quarterly-updating datasets produced by DepMap.<br>The Avana CRISPR-Cas9 genome-scale knockout data has expanded to include 808 cell lines, the RNAseq data includes 1376 cell lines, and the copy number data includes 1753 cell lines. Please see the README files for details regarding data processing pipeline procedures updates.<br>As our screening efforts continue, we will be releasing additional cancer dependency data on a quarterly basis for unrestricted use. For the latest datasets available, further analyses, and to subscribe to our mailing list visit https://depmap.org.<br>Descriptions of the experimental methods and the CERES algorithm are published in http://dx.doi.org/10.1038/ng.3984. Some cell lines were process using copy number data based on the Sanger Institute whole exome sequencing data (COSMIC: http://cancer.sanger.ac.uk.cell_lines, EGA accession number: EGAD00001001039) reprocessed using CCLE pipelines. A detailed description of the pipelines and tool versions for CCLE expression can be found here: https://github.com/broadinstitute/gtex-pipeline/blob/v9/TOPMed_RNAseq_pipeline.md.<br>v2 changes: The README file in version 1 for the Expression pipeline. Version 2 corrects this.<br>v3 changes: We have discovered several issues in the DepMap 20Q4 copy number data, described at https://forum.depmap.org/t/important-update-issues-with-depmap-20q4-data/344. These issues also affected the CRISPR (Avana) 20Q4 CERES data, which is dependent on copy number information. This version reverts the affected files to their previous versions which does not have these issues.
DOI: 10.21258/1670963
title: Inventario forestale nazionale svizzero - Tabella n. 897498
DOI: 10.21258/1630674
title: Inventario forestale nazionale svizzero - Tabella n. 897741
DOI: 10.21258/1659961
title: Inventario forestale nazionale svizzero - Tabella n. 897482
DOI: 10.21258/1642450
title: Inventario forestale nazionale svizzero - Tabella n. 891740
DOI: 10.4225/08/57980d45bc556
title: Mean monthly net radiation modelled using the 1" DEM-S - 1" mosaic

description: Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive: • Incoming short-wave radiation on a sloping surface • Short-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface) • Incoming long-wave radiation • Outgoing long-wave radiation • Net long-wave radiation • Net radiation • Sky view factor All radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane. The radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view. The monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9630 . The 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value. The 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18671
DOI: 10.21258/1635593
title: Inventario forestale nazionale svizzero - Tabella n. 898337
DOI: 10.4225/08/579802c242e01
title: Mean monthly net radiation modelled using the 1" DEM-S - 3" mosaic

description: Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive: • Incoming short-wave radiation on a sloping surface • Short-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface) • Incoming long-wave radiation • Outgoing long-wave radiation • Net long-wave radiation • Net radiation • Sky view factor All radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane. The radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view. The monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9630 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18670
DOI: 10.4225/08/577dc332aa649
title: Mean monthly outgoing surface longwave radiation modelled using the 1" DEM-S - 1" mosaic data

description: Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive: • Incoming short-wave radiation on a sloping surface • Short-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface) • Incoming long-wave radiation • Outgoing long-wave radiation • Net long-wave radiation • Net radiation • Sky view factor All radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane. The radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view. The data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18335 . The 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value. The 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18336
DOI: 10.21258/1633964
title: Inventario forestale nazionale svizzero - Tabella n. 897824
DOI: 10.26066/rds.1972404
title: Discharge: Langshisha Glacier old station

description: This dataset provides discharge measurements at terminus of Langshisha Glacier in Langtang Valley. The station is no longer operational.
DOI: 10.26066/rds.1972405
title: Discharge: Langshisha Glacier new station

description: This dataset provides discharge measurements at terminus of Langshisha Glacier in Langtang Valley. The station is no longer operational. An earlier station was located a little bit further upstream (separate dataset)
DOI: 10.26066/rds.1972406
title: Discharge: Lirung Glacier

description: This dataset provides discharge measurements at the outlet or the terminus lake at Lirung Glacier in Langtang Valley. The station is no longer operational. Discharge calculated from stage height measurements over multiple years, based on a rating curve developed locally with rhodamine dilution. At the location of the station is now the inlet for the hydropower plant.
DOI: 10.26066/rds.1972407
title: Discharge: Langtang Khola

description: This dataset provides discharge measurements at the main arm of the Langtang River in Langtang Valley. Additionally, the water temperature is recorded. The station is located where previously measurements have been undertaken for many years at a daily level. Discharge calculated from stage height measurements over multiple years, based on a rating curve developed between 2013 and 2018.
DOI: 10.26066/rds.1972408
title: Micromet station: Morimoto

description: This sensor measures wind speed, direction, air temperature and relative humidity. It is located on Morimoto, Langtang.
DOI: 10.26066/rds.1972409
title: Micromet station: Lirung glacier

description: This sensor measures wind speed, direction, air temperature and relative humidity. It is located on Lirung Glacier in Langtang Valley.
DOI: 10.26066/rds.1972410
title: Micromet station: Yala 3

description: This sensor measures wind speed, direction, air temperature and relative humidity. It was placed for a short period on the Yala Plateau, below Yala Base Camp in Langtang Valley.
DOI: 10.26066/rds.1972411
title: Micromet station: Yala 2

description: This sensor measures wind speed, direction, air temperature and relative humidity. It was placed for a short period on Yala Glacier in Langtang Valley.
DOI: 10.26066/rds.1972412
title: Micromet station: Yala 1

description: This sensor measures wind speed, direction, air temperature and relative humidity. It was placed for a short period on Yala Glacier in Langtang Valley.
DOI: 10.26066/rds.1972413
title: Pluviometer: Morimoto

description: This sensor measures precipitation volume and intensity with a bucket. Additionally air temperature, relative humidity and snow height are recorded. It is located in Langtang Valley on the ridge below Morimoto Glacier.
DOI: 10.26066/rds.1972414
title: Pluviometer: Langshisha

description: This sensor measures precipitation volume and intensity with a bucket. Additionally air temperature, relative humidity and snow height are recorded. It is located in Langtang Valley on left moraine (looking up-valley) of Langshisha Glacier.
DOI: 10.26066/rds.1972415
title: Pluviometer: Ganja La

description: This sensor measures precipitation volume and intensity with a bucket. Additionally air temperature and snow height are recorded. It is located in Langtang Valley below Ganja La Pass. It is no longer operational.
DOI: 10.26066/rds.1972416
title: Tipping Bucket: Ganja La 1

description: This sensor measures precipitation volumes with the tipping technique, where each signal is a fixed volume of water. It is located below Ganja La Pass in Langtang
DOI: 10.26066/rds.1972417
title: Soil Moisture: Tserko Ri

description: This sensor measures soil moisture at three depths in the soil. It is located in the Langtang Valley, on Yala Plateau, just north of and below Tserko Ri peak.
DOI: 10.26066/rds.1972418
title: Soil Moisture: Langshisha Pluvio

description: This sensor measures soil moisture at three depths in the soil. It is located in the Langtang Valley, next to the Langshisha Pluviometer on the left moraine of Langshisha Glacier.
DOI: 10.26066/rds.1972419
title: Soil Moisture: Langshisha BC

description: This sensor measures soil moisture at three depths in the soil. It is located in the Langtang Valley, between Langshisha and Shalbachum Glacier at Langshisha Basecamp, next to an existing Tipping Bucket.