cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0094752.10fu
title: SH0094752.10FU

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: 10.13145/bacdive102724.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102725.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094753.10fu
title: SH0094753.10FU

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: 10.13145/bacdive102725.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102726.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094754.10fu
title: SH0094754.10FU

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/sh0094755.10fu
title: SH0094755.10FU

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: 10.13145/bacdive102726.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102727.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094756.10fu
title: SH0094756.10FU

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: 10.13145/bacdive102727.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094757.10fu
title: SH0094757.10FU

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: 10.13145/bacdive102728.20230509.8.1
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive102728.20251217.10
title: Arthrobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0094758.10fu
title: SH0094758.10FU

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: 10.5281/zenodo.15035195
title: 316L Stainless Steel Micrographs

description: 8138 optical images of 316L stainless steel after performing an electrolytic etch with 10% oxalic acid at 6V. The steel is etched and then imaged in the as-received state.

Images are captured with a Zeiss Axio.M2 equipped with an EC Epiplan-Neofluar 20x/0.5 HD DIC M27 objective in reflective brightfield. Each frame is 1024 x 1024 pixels, with a scaling of 0.274 x 0.274 µm per pixel.

When montaged, the full image is 74171 x 75082 pixels, 20.31 x 20.56 mm, with a 20% overlap allowed between frames.

Please note these are the raw frames from image capture, from a rectangular area, and so some frames will only show Bakelite (in which the steel is mounted) and due to the automated nature of image capture, some images will not be perfectly in focus.
DOI: 10.5281/zenodo.15035196
title: 316L Stainless Steel Micrographs

description: 8138 optical images of 316L stainless steel after performing an electrolytic etch with 10% oxalic acid at 6V. The steel is etched and then imaged in the as-received state.

Images are captured with a Zeiss Axio.M2 equipped with an EC Epiplan-Neofluar 20x/0.5 HD DIC M27 objective in reflective brightfield. Each frame is 1024 x 1024 pixels, with a scaling of 0.274 x 0.274 µm per pixel.

When montaged, the full image is 74171 x 75082 pixels, 20.31 x 20.56 mm, with a 20% overlap allowed between frames.

Please note these are the raw frames from image capture, from a rectangular area, and so some frames will only show Bakelite (in which the steel is mounted) and due to the automated nature of image capture, some images will not be perfectly in focus.
DOI: 10.5281/zenodo.15041315
title: Raw NMR FID data of 30 East Asian traditional medicine formulations

description: This is NMR FID data of 30 East Asian traditional medicine formulations.

This will be reported in the article titled "Comparative analysis of 30 East Asian Traditional Medicine formulations revealed the applicability of 1H NMR spectroscopy in quality control", which will be submitted soon.
DOI: 10.5281/zenodo.15041699
title: Raw NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis

description: This is NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis.

Isolation and structural elucidation of these compounds will be reported in the article titled "Uncovering detoxification enzymes diversity of wood-decaying fungi through qualitative untargeted metabolomics", which will be submitted soon.
DOI: 10.5281/zenodo.7376078
title: Raw NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis

description: This is NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis.

Isolation and structural elucidation of these compounds will be reported in the article titled "Uncovering detoxification enzymes diversity of wood-decaying fungi through qualitative untargeted metabolomics", which will be submitted soon.
DOI: 10.5281/zenodo.7376079
title: Raw NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis

description: This is NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis. Isolation and structural elucidation of these compounds will be reported in the article titled "Uncovering detoxification enzymes diversity of wood-decaying fungi through qualitative untargeted metabolomics", which will be submitted soon.
DOI: 10.3886/e156042v1
title: National Neighborhood Data Archive (NaNDA): School Counts and Characteristics by School District, United States, 2000-2018

description: This dataset contains data on schools and
school districts within the United States from 2000 through 2018. Key variables
include district-level enrollment by race and ethnicity; numbers of teachers and
counselors; teacher-student ratios; counts of public, private, and charter
schools within districts; and expenditures and revenue, including per-pupil
revenue.<br><br>A curated version of this data is available through ICPSR at https://doi.org/10.3886/ICPSR38569.v1<br><br><br>
description: School districts in the United States, including U.S. island territories. Smallest Geographic Unit: school district
DOI: 10.15468/dl.wr8p6d
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Delia cardui (Meigen, 1826)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 59 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013282-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e156043v1
title: National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by Census Tract, United States, 2009-2010 and 2015-2016

description: This dataset contains measures of
neighborhood-school gap for 2009-2010 and 2015-2016. Neighborhood-school gap
(NS gap) refers to the discrepancy between the demographics of a public school
and its surrounding community. For example, if 60% of a school’s student body
is Black, but 30% of the neighborhood population is Black, the school has a
positive Black neighborhood-school gap. The dataset measures gaps in race and
poverty between elementary school student populations and the census tracts that
those elementary schools serve. Data is at the census tract level. Supplemental
data containing component variables used to calculate NS gap at the school and
block group level is also available.<br><br>A curated version of this data is available through ICPSR at: http://dx.doi.org/10.3886/ICPSR38579.v1
description: Census tracts in the United States, including U.S. island territories. Smallest Geographic Unit: census tract
DOI: 10.15468/dl.bjtb2f
title: Occurrence Download

description: A dataset containing 98 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pudu puda (Molina, 1782)",
 "Year 1981-2010"
 ]
}

 The dataset includes 98 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013283-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e156045v1
title: National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by ZIP Code Tabulation Area, United States, 2009-2010 and 2015-2016

description: This dataset contains measures of
neighborhood-school gap for 2009-2010 and 2015-2016. Neighborhood-school gap
(NS gap) refers to the discrepancy between the demographics of a public school
and its surrounding community. For example, if 60% of a school’s student body
is Black, but 30% of the neighborhood population is Black, the school has a
positive Black neighborhood-school gap. The dataset measures gaps in race and
poverty between elementary school student populations and the ZIP code tabulation areas (ZCTAs) that
those elementary schools serve. Data is at the ZCTA level. Supplemental
data containing component variables used to calculate NS gap at the school and
block group level is also available.<br><br> A curated version of this data is available through ICPSR at http://dx.doi.org/10.3886/ICPSR38579.v1
description: ZIP code tabulation areas in the United States, including U.S. island territories. Smallest Geographic Unit: ZIP code tabulation area
description: A ZIP code to ZCTA crosswalk must be used to combine this dataset with ZIP code geocoded data. Such a crosswalk is available on the UDS Mapper website at https://udsmapper.org/zip-code-to-zcta-crosswalk/. Sample code for merging the UDS Mapper crosswalk with NaNDA datasets is available on the NaNDA repository at https://www.openicpsr.org/openicpsr/project/120088/.
DOI: 10.3886/e110641v1
title: National Neighborhood Data Archive (NaNDA): Street Connectivity by Census Tract, United States, 2010

description: This dataset contains
measures of street connectivity (how well streets connect with one another)
within all United States census tracts. This includes measures of the number of
street segments (links) and intersections (nodes) per tract, street length within
tracts, and indices representing overall connectivity within the tract.<br><br>A curated version of this data is available through ICPSR at http://dx.doi.org/10.3886/ICPSR38580.v1 <br>
description: Streets in all census tracts within the United States, excluding the US island territories. Smallest Geographic Unit: census tract
DOI: 10.25345/c5g44j335
title: MassIVE MSV000097348 - Title: A Novel Protective Role of Astrocytic GFAP in Tau Proteostasis
title: Dataset 1: These samples are from mouse brains and include nine eluates with the antibody of interest and nine eluates from the same samples with the Ig isotype control. The labeling scheme was as follows: 126 - Mouse_T126_GFAP, 127N - Mouse_T126_IgG, 127C - Mouse_T156_GFAP, 128N - Mouse_T156_IgG, 128C - Mouse_T171_Myc, 129N - Mouse_T171_IgG, 129C - Mouse_T198_Myc, 130N - Mouse_T198_IgG, 130C - Mouse_T200_Myc, 131N - Mouse_T200_IgG, 131C - Mouse_T206_GFAP, 132N - Mouse_T206_IgG, 132C - Mouse_T218_GFP, 133N - Mouse_T218_IgG, 133C - Mouse_T177_Myc, 134N - Mouse_T177_IgG, 134C - Mouse_T211_Myc, 135N - Mouse_T211_IgG Dataset 2: These samples are human brain extracts, and the labeling scheme is as follows:, 129C - Human_1946_GFAP , 130N - Human_1956_IgG, 130C - Human_1636_GFAP, 131N - Human_1636_IgG, 131C - Human_2097_GFAP, 132N - Human_2097_IgG, 132C - Human_2057_GFAP, 133N - Human_2057_IgG, 133C - Human_1703_GFAP, 134N - Human_1703_IgG, 134C - Human_1628_GFAP, 135N - Human_1628_IgG
DOI: 10.3886/e134561v1
title: National Neighborhood Data Archive (NaNDA): Street Connectivity by ZIP Code Tabulation Area, United States, 2010

description: This dataset contains
measures of street connectivity (how well streets connect with one another)
within all United States ZIP code tabulation areas (ZCTAs). This includes measures of the number of
street segments (links) and intersections (nodes) per ZCTA, street length within ZCTA, and indices representing overall connectivity within the ZCTA.<br><br>A curated version of this data is available through ICPSR at http://dx.doi.org/10.3886/ICPSR38580.v1 <br>
description: Streets in all ZIP code tabulation areas within the United States, excluding the US island territories. Smallest Geographic Unit: ZIP code tabulation area
description: A ZIP code to ZCTA crosswalk must be used to combine this dataset with ZIP code geocoded data. Such a crosswalk is available on the UDS Mapper website at https://udsmapper.org/zip-code-to-zcta-crosswalk/. Sample code for merging the UDS Mapper crosswalk with NaNDA datasets is available on the NaNDA repository at https://www.openicpsr.org/openicpsr/project/120088/.
DOI: 10.3886/e160261v1
title: National Neighborhood Data Archive (NaNDA): Traffic Volume by ZIP Code Tabulation Area, United States, 1963-2019

description: This dataset contains measures of traffic
volume per ZIP code tabulation area (ZCTA) in the United States from 1963 to
2019 (primarily 1997 to 2019). High traffic volume may be used as a proxy for heavy traffic, high
traffic speeds, and impediments to walking or biking. The dataset contains
measures of the average, maximum, and minimum traffic volume per ZCTA per year.
These figures are available for all streets, highways, and non-highways.
Because data is collected intermittently across locations over time, traffic
volume has been interpolated for years in which no measures are available.<br><br>A curated version of this data is available through ICPSR at https://www.icpsr.umich.edu/web/ICPSR/studies/38584/versions/V1<br>
description: ZIP code tabulation areas in the United States, excluding U.S. island territories. Note that data is not available for every ZCTA and year because traffic measurements are not available in every year. Measures for missing years are interpolated where possible. Smallest Geographic Unit: ZIP code tabulation area
description: A ZIP code to ZCTA crosswalk must be used to combine this dataset with ZIP code geocoded data. Such a crosswalk is available on the UDS Mapper website at https://udsmapper.org/zip-code-to-zcta-crosswalk/. Sample code for merging the UDS Mapper crosswalk with NaNDA datasets is available on the NaNDA repository at https://www.openicpsr.org/openicpsr/project/120088/.
DOI: 10.3886/e160262v1
title: National Neighborhood Data Archive (NaNDA): Traffic Volume by Census Tract, United States, 1963-2019

description: This dataset contains measures of traffic
volume per census tract in the United States from 1963 to 2019 (primarily 1997
to 2019). High traffic volume may be used as a proxy for heavy traffic, high
traffic speeds, and impediments to walking or biking. The dataset contains
measures of the average, maximum, and minimum traffic volume per tract per
year. These figures are available for all streets, highways, and non-highways. <br><br><br>A curated version of this data is available through ICPSR at: athttps://www.icpsr.umich.edu/web/ICPSR/studies/38584/versions/V1<br>
description: Census tracts in the United States, excluding U.S. island territories. Note that data is not
available for every tract and year because traffic measurements are not
available in every year. Unlike the ZCTA-level version of this dataset, measures are not interpolated for missing years. Smallest Geographic Unit: census tract
DOI: 10.15468/dl.49hhya
title: Occurrence Download

description: A dataset containing 241190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Culex pipiens Linnaeus, 1758",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 241190 records from 282 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013239-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.