cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1210974.10fu
title: SH1210974.10FU

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/sh1210978.10fu
title: SH1210978.10FU

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/sh1210979.10fu
title: SH1210979.10FU

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: 10.15468/dl.94u6jq
title: Occurrence Download

description: A dataset listing the 718538 species recorded in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 718538 records were derived from 14311 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071515-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pzyach
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Brazil, Australia)",
 "OccurrenceStatus is Present",
 "TaxonKey is Phyllostictina vaccinii"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010305-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18356892
title: Replication Data for: DOE GREET Models and Data

description: Quoted from the original:  https://www.energy.gov/cmei/greet (accessed 1/23/2026) - 

“The Department of Energy (DOE) developed the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) life cycle analysis to assess the environmental impacts associated with technologies, fuels, products, and energy systems across various stages of the supply chain. 

For any given energy or transportation system, GREET can calculate: 





Total energy consumption (non-renewable and renewable) 




Fossil fuel energy use (petroleum, natural gas, coal)




Greenhouse gas emissions 




Air pollutant emissions 




Water consumption.







The Argonne National Laboratory R&D GREET Model is used to evaluate energy use and emissions output of transportation and energy sector technologies to assess research and development progress and inform RD&D direction.R&D GREET is available both as a Microsoft Excel file as well as a .NET tool.



BACKGROUND

The GREET suite of models was developed by Argonne National Laboratory (Argonne) in 1994, with the first version released in 1995. Its development and applications have been an integral part of DOE’s RD&D efforts to pursue energy and material technologies for energy efficiency, affordability, and environmental sustainability.

USE CASES

GREET models are developed for specific use cases, aiming to guide decision-making, research and development, and regulations related to the transportation and energy sectors.

Users are responsible for ensuring they have selected the correct model for their intended purpose. Stakeholders seeking a GREET model for purposes of compliance with a given regulatory program should review guidance specific to that program to ascertain the appropriate version of GREET to use.

For example, annual releases of R&D GREET are comprehensive in order to inform the life cycle analysis technical community and elicit stakeholder feedback. R&D GREET may not be the version of GREET adopted by independent regulatory programs (e.g., tax credits). 

Learn to use the GREET Model for Emissions Life Cycle Analysis in our H2IQ Hour webinar. 

Access additional GREET resources from Argonne.”
DOI: 10.5281/zenodo.18356893
title: Replication Data for: DOE GREET Models and Data

description: Quoted from the original:  https://www.energy.gov/cmei/greet (accessed 1/23/2026) - 

“The Department of Energy (DOE) developed the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) life cycle analysis to assess the environmental impacts associated with technologies, fuels, products, and energy systems across various stages of the supply chain. 

For any given energy or transportation system, GREET can calculate: 





Total energy consumption (non-renewable and renewable) 




Fossil fuel energy use (petroleum, natural gas, coal)




Greenhouse gas emissions 




Air pollutant emissions 




Water consumption.







The Argonne National Laboratory R&D GREET Model is used to evaluate energy use and emissions output of transportation and energy sector technologies to assess research and development progress and inform RD&D direction.R&D GREET is available both as a Microsoft Excel file as well as a .NET tool.



BACKGROUND

The GREET suite of models was developed by Argonne National Laboratory (Argonne) in 1994, with the first version released in 1995. Its development and applications have been an integral part of DOE’s RD&D efforts to pursue energy and material technologies for energy efficiency, affordability, and environmental sustainability.

USE CASES

GREET models are developed for specific use cases, aiming to guide decision-making, research and development, and regulations related to the transportation and energy sectors.

Users are responsible for ensuring they have selected the correct model for their intended purpose. Stakeholders seeking a GREET model for purposes of compliance with a given regulatory program should review guidance specific to that program to ascertain the appropriate version of GREET to use.

For example, annual releases of R&D GREET are comprehensive in order to inform the life cycle analysis technical community and elicit stakeholder feedback. R&D GREET may not be the version of GREET adopted by independent regulatory programs (e.g., tax credits). 

Learn to use the GREET Model for Emissions Life Cycle Analysis in our H2IQ Hour webinar. 

Access additional GREET resources from Argonne.”
DOI: 10.15468/dl.e2rvsr
title: Occurrence Download

description: A dataset containing 14737 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonId is not null",
 "GbifId is not null",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2026-01-04",
 "EventDate is less than or equal to 2026-02-03",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 14737 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010304-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17782066
title: Acinetobacter baylyi RNAseq data for wildtype and ddaA mutant treated with mitomycin C
DOI: 10.5281/zenodo.17782067
title: Acinetobacter baylyi RNAseq data for wildtype and ddaA mutant treated with mitomycin C
DOI: 10.15468/dl.32wnh8
title: Occurrence Download

description: A dataset containing 2689 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Erythronium montanum"
 ]
}

 The dataset includes 2689 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010308-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wgvcss
title: Occurrence Download

description: A dataset containing 204363 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The reptiles and amphibians collection (RA) of the Muséum national d'Histoire Naturelle (MNHN - Paris)"
 ]
}

 The dataset includes 204363 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010292-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00012484.0
title: Available datapackage for study 'Leveraging Social Networks to Increase COVID-19 Testing Uptake: A Comparison of Credible Messenger and Chain Referral Recruitment Approaches'

description: This two-year project will adapt and conduct a trial examining the ability of two recruitment strategies, chain-referral and credible messenger, to reach those who use opioids and other substances in order to increase their uptake of onsite point of care COVID-19 testing that will be delivered in two community based organizations (CBOs): Alliance for Positive Change and Argus Health Inc. In Phase 1, Adapt two implementation strategies to support COVID-19 testing uptake and sustainability, adapting elements of existing efficacious social network-based interventions via a CBPR approach. In Phase 2, we will examine and compare the efficacy of two sets of implementation strategies on (i) reach, (ii) testing uptake, (iii) service delivery (i.e. quarantine, medical care, contact tracing) and (iv) sustainability for individuals who use opioids and other drugs. In Phase 3, Elucidate and compare the system/organizational-, staff-, and individual-level factors that influence implementation (i.e. fidelity, acceptability, feasibility, sustainability) of the strategies to develop a plan for dissemination and scale-up in other CBOs who serve opioid and other substance using individuals in NYC.
DOI: 10.5281/zenodo.18474314
title: MODERN METHODS IN IMPLANTOLOGY AND THEIR CLINICAL SIGNIFICANCE

description: The article explores innovative methods used in modern implantology and their significance in clinical practice. The impact of new techniques such as digital technologies (CBCT, CAD/CAM), immediate loading, regenerative surgery, and robotic-assisted methods on treatment efficacy and patients' quality of life is analyzed. Research indicates that modern methods increase the success rate of implantation and reduce the risk of complications. The article also discusses clinical cases and future development directions. This article can serve as a valuable resource for dentists, implantologists, and medical researchers.
DOI: 10.5281/zenodo.18474315
title: MODERN METHODS IN IMPLANTOLOGY AND THEIR CLINICAL SIGNIFICANCE

description: The article explores innovative methods used in modern implantology and their significance in clinical practice. The impact of new techniques such as digital technologies (CBCT, CAD/CAM), immediate loading, regenerative surgery, and robotic-assisted methods on treatment efficacy and patients' quality of life is analyzed. Research indicates that modern methods increase the success rate of implantation and reduce the risk of complications. The article also discusses clinical cases and future development directions. This article can serve as a valuable resource for dentists, implantologists, and medical researchers.
DOI: 10.15468/dl.w2yn97
title: Occurrence Download

description: A dataset containing 405 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Phenology of Plants of Ekaterinburg"
 ]
}

 The dataset includes 405 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010310-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15239063
title: Data for E. faecium ISL3 project: long-read Enterococcus genome resource + preprocessed data for manuscript analyses

description: # NOTE: This project and associated manuscript are WIP under review; publication information will be updated shortly.
# Please contact the authors for more information.

1. Resource: long-read clinical Enterococcus genome assemblies

The gzipped tarball ente_isolate_assemblies.tar.gz contains 282 new long-read genome assemblies from Enterococcus clinical isolates.



Bloodstream infection isolates were collected between 2020-2024 at Stanford Hospitals.

Isolates were sequenced (Oxford Nanopore, R10.4.1 chemistry) and assembled (Flye 2.9.1) in 2024.

Included genomes: 107 E. faecium, 167 E. faecalis, 8 other enterococci.


See the associated manuscript's Methods section for more detail.

2. Preprocessed source data for manuscript analyses

The package analyses_preprocessed_source_data.zip contains preprocessed source data files that can be used to reproduce analyses and figures from the associated manuscript. More instructions can be found on our GitHub repository.
DOI: 10.21949/ph7t-4944
title: Inclusive Wayfinding Through NaviLens [supporting datasets]

description: MTA NaviLens Feedback Survey: Survey responses include overall satisfaction, agreement ratings about ease of use and information quality, recommendations, interest in expanding code coverage, comparisons to other wayfinding/travel apps, and open-ended comments. The survey also includes optional demographic questions (e.g., age range, typical transit use frequency, Access-A-Ride customer status, and disability identification) to help contextualize feedback. This survey supports evaluation of the NaviLens deployment and related project reporting, including work funded through the USDOT SMART Grant.

MTA NaviLens Usage Dataset: Navilens usage data contains records of scan events (each row represents a time a NaviLens code was scanned). Scan records include the code identifier, the type of asset scanned (e.g., bus stop, bus vehicle, subway station, train car, or vehicle feature), the app used (NaviLens vs. NaviLens GO), the device language setting at time of scan, and timestamps. For certain asset types, scan events are also enriched with location fields such as bus stop identifiers and names or subway station identifiers and names. This data supports evaluation of the NaviLens deployment and related project reporting, including work funded through the USDOT SMART Grant.
description: These datasets additional data and software in a GitHub repository. This repository is accessible online: https://github.com/nymta/MTA-USDOT-SMART-Grant-Inclusive-Wayfinding-through-NaviLens-
Please cite as: Sciallis, Patrick, Philipson, M., and Singh, C. (2026). MTA NaviLens Feedback Survey [datasets]. https://doi.org/10.21949/ph7t-4944

Philipson, Mira and Singh, C. (2026). MTA NaviLens Usage Data [datasets]. doi.org/10.21949/ph7t-4944
DOI: 10.25345/c52r3p97j
title: MassIVE MSV000100700 - NSC_Lee_Heart_Mitochondria_Turnover
title: Enriched mitochondria from hearts in mice labeled with D2O.
DOI: 10.21949/neab-4771
title: Portland's SMART Delivery Zones Dataset [supporting data]

description: The US Department of Transportation (USDOT) awarded the Portland Bureau of Transportation (PBOT) a nearly $2 million Strengthening Mobility and Revolutionizing Transportation (SMART) Grant in Fall 2023. This project piloted the country’s first regulated SMART Delivery Zones (SDZ) that relied on parking permits to offer preferred curb access to encourage commercial fleets to embrace technology-enabled, innovative goods delivery models. Designed to modernize urban logistics and test new regulatory structures, the SDZ pilot utilized public- and private-sector partnerships, innovative curb management strategies, open-source data standards, alternative delivery models, and advanced sensor technologies to dramatically improve the efficiency of goods movement.
DOI: 10.25824/redu/itrhqc
title: Mapas rodovias e hidrelétricas na Amazônia Legal Brasileira

description: Dados para elaboração de mapas de rodovias e hidrelétricas na Amazônia Legal Brasileira.
DOI: 10.5281/zenodo.18469909
title: xwmb_examples datasets

description: Bite-sized example netCDF files for water mass transformations calculations.

These example files were subsampled from the following model outputs:



CM4Xp125 (the ocean model code is MOM6) – see https://doi.org/10.1029/2024MS004861

CROCO (RREX regional configuration) - see https://doi.org/10.1029/2024MS004768
DOI: 10.5281/zenodo.18469910
title: xwmb_examples datasets

description: Bite-sized example netCDF files for water mass transformations calculations.

These example files were subsampled from the following model outputs:



CM4Xp125 (the ocean model code is MOM6) – see https://doi.org/10.1029/2024MS004861

CROCO (RREX regional configuration) - see https://doi.org/10.1029/2024MS004768
DOI: 10.5281/zenodo.17352355
title: SDT files for begomovirus percent nucletotide identity comparisons

description: Files produced by SDT v1.3 comparing the percent nucleotide identities for 25 datasets of begomovirus DNA-A (or whole genome homologous to the DNA-A of bipartite begomoviruses).  These data were used to calculate averages in the manuscript "Begomovirus species demarcation based on genome-sequence identity yields non-monophyletic species: a case study of sweet potato-infecting begomoviruses."  The GenBank accession numbers for all analyzed sequences are given in the files (which can be viewed in a text editor as well as the SDT software).
DOI: 10.5281/zenodo.17352354
title: SDT files for begomovirus percent nucletotide identity comparisons

description: Files produced by SDT v1.3 comparing the percent nucleotide identities for 25 datasets of begomovirus DNA-A (or whole genome homologous to the DNA-A of bipartite begomoviruses).  These data were used to calculate averages in the manuscript "Begomovirus species demarcation based on genome-sequence identity yields non-monophyletic species: a case study of sweet potato-infecting begomoviruses."  The GenBank accession numbers for all analyzed sequences are given in the files (which can be viewed in a text editor as well as the SDT software).
DOI: 10.25611/htt0-4d34
title: Data for Exceptional optical phonon coherence in enriched cubic boron arsenide via suppression of three-phonon scattering

description: Data for figure plots and raw data in Exceptional optical phonon coherence by suppressing three-phonon scattering in enriched cubic boron arsenide.
DOI: 10.34740/kaggle/dsv/14722842
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.25934/pr00012485.0
title: Available datapackage for study 'COV-IDD: Testing for COVID-19 in High Risk Children With Intellectual and Developmental Disabilities'

description: The purpose of this study is to understand how to prevent COVID-19 spread in a school like the Mary Cariola Center (MCC) in Rochester, NY by answering questions like these: how do activities in the school alter chances of infection? Are there people infected with the COVID-19 virus who have no symptoms? How is spread of COVID-19 affected by vaccination rates? Is there any hesitancy to get the vaccine and what are the reasons? This information will be used to help keep the school open and the students and staff safe.Eligible participants are those that work at the Mary Cariola Center (MCC) and interact with the students at MCC who have a high risk of infection from COVID-19.The study lasts for up to 16 months.