cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5063/f1mg7mzh
title: Vegetation surveys in Cuyama Valley, CA, USA in 2016 and 2017 at the peak of megadrought

description: Vegetation surveys were used to identify the relative abundance patterns of plants with shrubs within the Cuyama Valley, CA. Plants were counted within 0.5m quadrats placed under shrubs and at paired-open microsite without a canopy. The shrub species Ephedra californica was the dominant woody plant regionally, and all patches with at least 25 shrubs present were sampled to some extent. This survey supports other work including manipulative experiments and climate tracking research.
DOI: 10.5257/iea/oil/2020
title: Oil Information (2020 Edition)

description: Oil Information is a comprehensive reference dataset on current developments in oil supply and demand. This publication contains key data on world production, trade, prices and consumption of major oil product groups, with time-series back to the early 1970s. Its core consists of a detailed and comprehensive picture of oil supply, demand, trade, production and consumption by end-user for each OECD country individually and for the OECD regions. Trade data are reported extensively by origin and destination.
DOI: 10.5281/zenodo.6353971
title: Soil Moisture and Sea Surface Temperature Data for Wikle et al. (2022)

description: Raw data (.nc) in NetCDF4 format, and formatted and rearranged data (.csv) in CSV format. With R Markdown document detailing the steps taken. All data obtained originally from NOAA's NCEP and NCDC data store systems. Data used in developing and demonstrating explainable AI models for <em>An Overview of Model Agnostic Explainability Methods for Machine Learning Applied to Environmental Data</em>, Wikle et al. (2022), for the <em>Special Issue on Environmental Data Science</em> for <em>Environmetrics. </em>See https://zenodo.org/record/6353636 for the corresponding model codebase.
DOI: 10.5281/zenodo.6901460
title: Dataset from: An intuitive form of the energy functional for resistive plasma perturbations

description: The energy functional of ideal magnetohydrodynamics (MHD) is extended to the regime of finite resistivity and transformed to an intuitive form, which separates pressure-gradient, current-density drive and stabilizing phenomena, analogously to the ideal version of the functional derived by Johnson and Greene. The resulting resistive energy functional is not in the form of a solvable eigenvalue problem but is intended to analyze the energetic composition of eigenfunctions which were calculated in advance by solving the MHD equations. The new resistive energy functional provides information on the different energetic drives and stabilizing phenomena of an eigenfunction. The new energy functional has been implemented in the CASTOR3D code in general 3D curvilinear coordinates and successfully validated across three different coordinate systems for a numerical test case.
DOI: 10.5439/1164928
title: Quality Controlled Radiosonde Profile from MC3E

description: The sonde-adjust VAP produces data that corrects documented biases in radiosonde humidity measurements. Unique fields contained within this datastream include smoothed original relative humidity, dry bias corrected relative humidity, and final corrected relative humidity. The smoothed RH field refines the relative humidity from integers - the resolution of the instrument - to fractions of a percent. This profile is then used to calculate the dry bias corrected field. The final correction fixes a time-lag problem and uses the dry-bias field as input into the algorithm. In addition to dry bias, solar heating is another correction that is encompassed in the final corrected relative humidity field. Additional corrections were made to soundings at the extended facility sites (S0*) as necessary: Corrected erroneous surface elevation (and up through rest of height of sounding), for S03, S04 and S05. Corrected erroneous surface pressure at Chanute (S02).
DOI: 10.6084/m9.figshare.19700056
title: DepMap 22Q2 Public

description: This DepMap release contains data from CRISPR knockout screens from project Achilles, as well as genomic characterization data from the CCLE project.<br>For more information, please see README.txt.
DOI: 10.15152/qdb.257
title: Data for: Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. QsarDB repository, QDB.

description: This QDB archive contains data and model(s) from the following publication: Oja, M.; Sild, S.; Piir, G.; Maran, U. Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. Pharmaceutics 2022.
DOI: 10.15156/bio/sh1488361.08fu
title: SH1488361.08FU

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/sh1488362.08fu
title: SH1488362.08FU

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/sh1951824.08fu
title: SH1951824.08FU

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/sh1951825.08fu
title: SH1951825.08FU

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: 10.17632/hbxtzs3zhd.1
title: Deletion of constitutive androstane receptor led to intestinal alterations and increased imidacloprid in murine liver. 

description: Supplemental Data and Figures for:

Title:
Deletion of constitutive androstane receptor led to intestinal alterations and increased imidacloprid in murine liver. 
Authors:
Anushna Sen1,2, Madison Goforth2,3, Kerry K. Cooper3, and Sayeepriyadarshini Anakk1,2,3,5 
Affiliations:
1Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL, 2Toxicology Training Program, University of Illinois at Urbana-Champaign, Urbana, IL, 3School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, 4Cancer Center at Illinois, 5Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL.
DOI: 10.5066/f7hq3x18
title: Groundwater Quality Data from the National Water Quality Assessment Project, May 2012 through December 2013

description: Groundwater-quality data were collected from 748 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from May 2012 through December 2013. The data were collected from four types of well networks: principal aquifer study networks, which assess the quality of groundwater used for public water supply; land-use study networks, which assess land-use effects on shallow groundwater quality; major aquifer study networks, which assess the quality of groundwater used for domestic supply; and enhanced trends networks, which evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, and radionuclides. These groundwater quality data are tabulated in a U.S. Geological Survey Data Series Report DS-997 which is available at http://dx.doi.org/10.3133/ds997 and in this data release. Quality-control samples also were collected; data from blank and replicate quality-control samples are included in the related report (DS-997) and this data release. This compressed file contains 28 files of groundwater-quality data in ASCII text tab-delimited format and 28 corresponding metadata in xml format for wells sampled for the U.S. Geological Survey National Water-Quality Assessment Project, May 2012 through December 2013.
DOI: 10.5066/f7w0942n
title: Datasets from Groundwater-Quality Data from the National Water-Quality Assessment Project, January through December 2014 and Select Quality-Control Data from May 2012 through December 2014

description: Groundwater-quality data were collected from 559 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from January through December 2014. The data were collected from four types of well networks: principal aquifer study networks, which assess the quality of groundwater used for public water supply; land-use study networks, which assess land-use effects on shallow groundwater quality; major aquifer study networks, which assess the quality of groundwater used for domestic supply; and enhanced trends networks, which evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some special interest constituents (arsenic speciation, chromium (VI) and perchlorate). These groundwater-quality data are tabulated in this data release and are described in a U.S. Geological Survey Data Series Report DS-1063 (https://doi.org/10.3133/ds1063). Quality-control samples also were collected and select data from 2012-12014 are included in the report DS-1063 and this data release. Data from the environmental and QC blank and replicate samples from the 2012-2013 sampling period were presented in Arnold and others (2016) (http://dx.doi.org/10.5066/F7HQ3X18). Data from VOC spike QC data from May 2012-December 2014 are published in this data release and related report (https://doi.org/10.3133/ds1063) along with an analysis of QC data where detections in field blank samples, variability in replicate samples, and recoveries in VOC spike samples are described for the entire sampling period through the date covered in this report (May 2012-December 2014). The compressed file contains 33 files of groundwater-quality data in ASCII text tab-delimited format and 33 corresponding metadata in xml format for wells sampled for the U.S. Geological Survey National Water-Quality Assessment Project. REFERENCES CITED &amp;#8203;Arnold, T.L., Bexfield, L.M., Musgrove, MaryLynn, Lindsey, B.D., Stackelberg, P.E., Barlow, J.R., DeSimone, L.A., Kulongoski, J.T., Kingsbury, J.A., Ayotte, J.D., Fleming, B.J., and Belitz, Kenneth, 2017, Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014: U.S. Geological Survey Data Series 1063, xx p., https://doi.org/10.3133/ds1063. Arnold, T.L., DeSimone, L.A., Bexfield, L.M., Lindsey, B.D., Barlow, J.R., Kulongoski, J.T., Musgrove, MaryLynn, Kingsbury, and Belitz, Kenneth, 2016, Groundwater Quality Data from the National Water Quality Assessment Project, May 2012 through December 2013: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7HQ3X18.
DOI: 10.5066/f7xk8dhk
title: Datasets from Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2015 and Previously Unpublished Data from 2013-2014
DOI: 10.5066/p9w4rr74
title: Datasets from Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2016, and Previously Unpublished Data from 2013 to 2015

description: Groundwater-quality data were collected from 648 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (514) were sampled from January through December 2016 and 60 of them were sampled in 2013 and 74 in 2014. The data were collected from seven types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; flow path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths over a horizontal distance; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some special interest constituents (arsenic speciation, chromium [VI] and perchlorate). These groundwater quality data are tabulated in this data release. Some data from environmental samples collected in 2013-14 and quality-control samples collected in 2012-15 also are included in the associated data release. Data from samples collected in 2016 are associated with networks described in this report and have not been published previously; data from samples collected between 2012 and 2015 are associated with networks described in previous reports in this data series (Arnold and others, 2016a,b, 2017a,b, 2018a,b). There are 23 data tables included in this data release and they are referenced as tables 1-13 and appendix tables 4.10-4.19 in the larger work citation. There are 36 tables that are part of the larger work citation; the 13 tables not included in the data release are summary tables derived from some of the other tables (tables 1.1, 2.2-2.3, 3.1, 4.1-4.9). A version of table 1 is included in both the text and data release.
DOI: 10.5281/zenodo.6821737
title: ERA-I version data for the paper "Role of Vertical Mixing in the Upper Ocean in the Seasonal Variation of Arctic Amplification"

description: All the data, used to draw figures in the manuscript are uploaded. The variables' description have been well defined in the manuscript.
DOI: 10.5281/zenodo.6979789
title: Data from: Extreme escalation of heat failure rates in ectotherms with global warming

description: Data from: Extreme escalation of heat failure rates in ectotherms with global warming
DOI: 10.6084/m9.figshare.16837987
title: Data: Using successional drivers to understand spatiotemporal dynamics in intertidal mudflat communities. Ecosphere

description: .zip folder containing datasets and metadata used in the manuscript. Please consult manuscript and Supplemental Figure 2 for more information about data processing workflows used. <br> .pwk files are included and can be opened using Primer statistical software. These files include data analyses conducted for data collected during the two case studies.
DOI: 10.15156/bio/sh1488363.08fu
title: SH1488363.08FU

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/sh1488364.08fu
title: SH1488364.08FU

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/sh1951826.08fu
title: SH1951826.08FU

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/sh1951827.08fu
title: SH1951827.08FU

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.