cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17985982
title: Boron Theranostic Nanoplatform Utilizing a GO@Carborane@Au Hybrid Framework for Targeted Delivery

description: Raw data for a project "Boron Theranostic Nanoplatform Utilizing a GO@Carborane@Au Hybrid Framework for Targeted Delivery." Data include images from electron microscopy (SEM and TEM) and data obtained from Molecular spectroscopy imaging.
DOI: 10.21227/xbxt-bm95
title: "Digital Marketing Companies in Hyderabad: Driving Business Growth in the Digital Age"

description: "In today\u2019s competitive business environment, having a strong online presence is no longer optional it is essential."
DOI: 10.15468/56jwra
title: The Herptile (reptiles and amphibians) Collection of the University Museum of Bergen

description: Our collections of amphibians and reptiles at the University Museum of Bergen, Norway are relatively limited in size: in total about 1200 specimens. Much of this material are whole animals preserved in ethanol. Even if the collection contains numerous species from exotic parts of the world, our main targets today are the limited number of species found in Norwegian fauna.Today there is no active collecting of herptiles at the University Museum and new material are mainly animals that have been found dead for various reasons.
DOI: 10.5281/zenodo.17986052
title: Sinitic between Altaic and Mainland Southeast Asia

description: Szeto & Yurayong: Sinitic between Altaic and Mainland Southeast Asia
DOI: 10.5281/zenodo.17986053
title: Sinitic between Altaic and Mainland Southeast Asia

description: Szeto & Yurayong: Sinitic between Altaic and Mainland Southeast Asia
DOI: 10.17026/ar/k0k1v2
title: PAN-00182718 - ceramic sling bullet, eye-shaped

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00182718&lt;/p&gt;
description: Modified: 2025-11-17T10:31:36+01:00
DOI: 10.15468/dl.w8qaxq
title: Occurrence Download

description: A dataset containing 123 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.18_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 123 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060213-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p3grer
title: Occurrence Download

description: A dataset containing 12533 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gaillardia aristata",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12533 records from 180 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060214-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.en9qs9
title: Occurrence Download

description: A dataset containing 11352 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucalyptus polyanthemos",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 11352 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060216-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2zcgf9
title: Occurrence Download

description: A dataset containing 3551 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tracheophyta)",
 "Geometry POLYGON ((13.0116 47.522, 13.0466 47.522, 13.0466 47.557, 13.0116 47.557, 13.0116 47.522))"
 ]
}

 The dataset includes 3551 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060218-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30919357
title: Characterising the high spatial heterogeneity of urban flood resilience under extreme rainfall using mobile signal data

description: Characterisation of the spatial heterogeneity of urban flood resilience (UFR) under extreme rainfall events can support decision-making in urban planning and emergency management. Traditional flood-resilience assessment methods based on socioeconomic or infrastructure statistics, face challenges in capturing urban operational efficiency (UOE; e.g. traffic mobility), especially its loss and recovery time. To overcome such challenges, we propose a new framework of UFR heterogeneity that: (1) utilises 800-m spatial and day-time resolution mobile signal big data as a dynamic metric for UOE; (2) presents a resilience matrix to quantitatively measure both the loss and recovery of UOE, achieving a unified UFR representation during extreme events; and (3) offers a spatial attention-based machine learning method to attribute the heterogeneity of UFR. An empirical study of the July 2021 extreme rainfall event in Zhengzhou, China, reveals that robust/high resilience, medium resilience, and low resilience grid cells account for 25%, 67%, and 8% of the samples; among them, the administrative core mainly comprises robust and high-resilience categories, whereas the county boundary exhibits low-resilience. Infrastructural transportation characteristics (28%), social-economic factors (25%), and spatial attributes (21%) are tracked as critical drivers by the XGBoost-SHAP framework.
DOI: 10.6084/m9.figshare.30919357.v1
title: Characterising the high spatial heterogeneity of urban flood resilience under extreme rainfall using mobile signal data

description: Characterisation of the spatial heterogeneity of urban flood resilience (UFR) under extreme rainfall events can support decision-making in urban planning and emergency management. Traditional flood-resilience assessment methods based on socioeconomic or infrastructure statistics, face challenges in capturing urban operational efficiency (UOE; e.g. traffic mobility), especially its loss and recovery time. To overcome such challenges, we propose a new framework of UFR heterogeneity that: (1) utilises 800-m spatial and day-time resolution mobile signal big data as a dynamic metric for UOE; (2) presents a resilience matrix to quantitatively measure both the loss and recovery of UOE, achieving a unified UFR representation during extreme events; and (3) offers a spatial attention-based machine learning method to attribute the heterogeneity of UFR. An empirical study of the July 2021 extreme rainfall event in Zhengzhou, China, reveals that robust/high resilience, medium resilience, and low resilience grid cells account for 25%, 67%, and 8% of the samples; among them, the administrative core mainly comprises robust and high-resilience categories, whereas the county boundary exhibits low-resilience. Infrastructural transportation characteristics (28%), social-economic factors (25%), and spatial attributes (21%) are tracked as critical drivers by the XGBoost-SHAP framework.
DOI: 10.15468/dl.zchn6y
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.19_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060219-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17985736
title: Experimental data used in the article 'Quantum Correlations in Three-Beam Symmetric Gaussian States Accessed via Photon-Number-Resolving Detection and Quantum Universal Invariants'

description: The (experimental) data obtained by the maximum-likelihood approach are in the files whose names end with capital letter M, the results of the multi-mode Gaussian model are contained in the files whose names end with capital letter G. Also the number of a figure is encoded in the name of the file including subfigures denotes by letters a-h. Figures involved in Supplemental Material are indicated by capital letters SM. The 70 files contain the data appropriate to Figs. 2a-d and 3a,b of the main text of the article and Figs. SM4a-d, SM5a-b, SM6a-d, SM7a-h, SM8a-f, and SM8a-c of Supplemental Material.
DOI: 10.5281/zenodo.17985735
title: Experimental data used in the article 'Quantum Correlations in Three-Beam Symmetric Gaussian States Accessed via Photon-Number-Resolving Detection and Quantum Universal Invariants'

description: Additional 18 files were added during the revision giving the data appropriate to Figs. 9 and 11 in the revised version.

The (experimental) data obtained by the maximum-likelihood approach are in the files whose names end with capital letter M, the results of the multi-mode Gaussian model are contained in the files whose names end with capital letter G. Also the number of a figure is encoded in the name of the file including subfigures denotes by letters a-h. Figures involved in Supplemental Material are indicated by capital letters SM. The 70 files contain the data appropriate to Figs. 2a-d and 3a,b of the main text of the article and Figs. SM4a-d, SM5a-b, SM6a-d, SM7a-h, SM8a-f, and SM8a-c of Supplemental Material.
DOI: 10.5281/zenodo.17986011
title: Experimental data used in the article 'Quantum Correlations in Three-Beam Symmetric Gaussian States Accessed via Photon-Number-Resolving Detection and Quantum Universal Invariants'

description: Additional 18 files were added during the revision giving the data appropriate to Figs. 9 and 11 in the revised version.

The (experimental) data obtained by the maximum-likelihood approach are in the files whose names end with capital letter M, the results of the multi-mode Gaussian model are contained in the files whose names end with capital letter G. Also the number of a figure is encoded in the name of the file including subfigures denotes by letters a-h. Figures involved in Supplemental Material are indicated by capital letters SM. The 70 files contain the data appropriate to Figs. 2a-d and 3a,b of the main text of the article and Figs. SM4a-d, SM5a-b, SM6a-d, SM7a-h, SM8a-f, and SM8a-c of Supplemental Material.
DOI: 10.15468/dl.ctg4ze
title: Occurrence Download

description: A dataset containing 520 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.20_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 520 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060223-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.17615.20644
title: Nyong basin hydro climatic data set, gridded data, monthly flow rates, GIS layers
DOI: 10.17028/rd.lboro.27927432
title: Data for: Long-term (37-year) changes in coastal dune slack plant communities

description: Plant community data from plots/releves in dune slacks at Ainsdale Sand Dunes NNR. Dataset contains data for plots surveryed in 1985 and in 2022. Dataset also contains data on environmental variabiles for the site for each year between 1980 - 2022: air temperature (mean daily maximum, minimum and mean), precipitation, water table depth, compilation of rabbit abundance data.
DOI: 10.17028/rd.lboro.27927432.v1
title: Data for: Long-term (37-year) changes in coastal dune slack plant communities

description: Plant community data from plots/releves in dune slacks at Ainsdale Sand Dunes NNR. Dataset contains data for plots surveryed in 1985 and in 2022. Dataset also contains data on environmental variabiles for the site for each year between 1980 - 2022: air temperature (mean daily maximum, minimum and mean), precipitation, water table depth, compilation of rabbit abundance data.
DOI: 10.15468/dl.8dsmhb
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 2cd829bb-b713-433d-99cf-64bef11e5b3e",
 "TaxonKey is Mantidactylus pauliani"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060225-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fx6jvr
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 2cd829bb-b713-433d-99cf-64bef11e5b3e",
 "TaxonKey is Mantidactylus pauliani"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060226-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14222666
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.r6eexk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.21_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060227-251120083545085/datasets/export for details.
DOI: 10.15468/dl.jhf4hd
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Greece",
 "TaxonKey is Alphitophagus bifasciatus"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060228-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b2wcx7
title: Occurrence Download

description: A dataset containing 264134 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Meetnet Agrarische Soorten - Monitoring of birds and mammals in agricultural areas in Flanders, Belgium"
 ]
}

 The dataset includes 264134 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060215-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14278/rodare.4170
title: Data publication: Scalable Machine Learning Model for Energy Decomposition Analysis in Aqueous Systems

description: You can find the Python scripts we developed to train a neural network model to predict the electron delocalization energies of water molecules here. The training datasets are not included but can be provided upon reasonable request.
DOI: 10.14278/rodare.4169
title: Data publication: Scalable Machine Learning Model for Energy Decomposition Analysis in Aqueous Systems

description: You can find the Python scripts we developed to train a neural network model to predict the electron delocalization energies of water molecules here. The training datasets are not included but can be provided upon reasonable request.
DOI: 10.15468/dl.53vrpd
title: Occurrence Download

description: A dataset containing 203 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.22_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 203 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060231-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kfb4b7
title: Occurrence Download

description: A dataset containing 117921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Greece",
 "DatasetKey is Herbarium Berolinense, Berlin (B)",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 117921 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060217-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vmajks
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anchoa eigenmannia",
 "Year 2000-2025"
 ]
}

 The dataset includes 28 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060232-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48677/3d680533-4835-45df-ae42-b4c46039e9b9
title: Kataster Grafik DXF Stichtag 01.10.2025

description: Die Digitale Katastralmappe (DKM) ist der grafische Datenbestand des Katasters im Koordinatensystem der Österreichischen Landesvermessung. Sie wird von den zuständigen Vermessungsämtern katastralgemeindeweise geführt. Die DKM veranschaulicht die Lage der Grundstücke und enthält:
- die Grenzen der Grundstücke
- die Grundstücksnummern
- Nutzungsgrenzen und -symbole
- die Fest-, Grenz- und Staatsgrenzpunkte mit deren Nummern
- sonstige Darstellungen
Die Konsistenz der Daten zwischen der DKM und dem Grundbuch wird über einen täglichen Abgleich der Datenbanken sichergestellt.

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
DOI: 10.15468/dl.9673n5
title: Occurrence Download

description: A dataset containing 3590 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tracheophyta)",
 "Geometry POLYGON ((13.01332 47.52045, 13.04832 47.52045, 13.04832 47.55545, 13.01332 47.55545, 13.01332 47.52045))"
 ]
}

 The dataset includes 3590 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060233-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17985947
title: Personalized Gait Patterns During Exoskeleton-Aided Training May Have Minimal Effect on User Experience. Insights from a Pilot Study

description: Dataset for experiment titled: "Personalized Gait Patterns During Exoskeleton-Aided Training May Have Minimal Effect on User Experience. Insights from a Pilot Study" - not yet published (2025-12-19)
DOI: 10.14466/cefasdatahub.191
title: Assessment product for good environmental status of marine quota fish stocks for the UK Marine Strategy 2024

description: The UK Marine Strategy assessment product for commercially exploited marine quota fish shows the Good Environmental Status (GES) for descriptor 3.  The assessment of environmental status for commercially exploited fish stocks is based on the integration of results from fishing pressure and reproductive capacity indicator assessments following a conditional method (ICES, 2016) where both indicators’ criteria need to be met for each stock. 

The 2024 UKMS assessment for marine quota fish uses a stock assessment data from 2016 to 2021 to calculate of percentage of stocks being within safe biological limits considering 6-year period where required data is available to integrate two indicators assessments, reproductive capacity (based on spawning stock biomass) and fishing pressure (based on fishing mortality), and compared with previous assessment cycles (2010-2015, 2004-2009). Full details on the UKMS assessment are published at https://moat.cefas.co.uk/pressures-from-human-activities/commercial-fish-and-shellfish. 

Details on the data set used for this assessment product are available at the following data-doi; Campón-Linares, V , McIntyre, R and Garnacho, E. (2025). Fish and shellfish stock assessments data for the UK Marine Strategy 2004 assessment of descriptor 3. Cefas, UK. V1. doi: https://doi.org/10.14466/CefasDataHub.173