cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.g3pjke
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "Geometry POLYGON((-108.71310 -22.17767,-20.28690 -22.17767,-20.28690 13.17767,-108.71310 13.17767,-108.71310 -22.17767))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Knodus breviceps (Eigenmann, 1908)"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019410-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.szgxev
title: Occurrence Download

description: A dataset containing 4143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Myanmar",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Poaceae"
 ]
}

 The dataset includes 4143 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011116-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvp4lf
title: Occurrence Download

description: A dataset containing 26038 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Megaptera novaeangliae (Borowski, 1781)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 26038 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042936-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57934/0b01e410805bdf01
title: Gemeente-, wijk- en buurtcodes van een verblijfsobject
DOI: 10.1594/pangaea.975870
title: Master tracks in different resolutions of POLARSTERN cruise PS18/4, Cape Town - Bremerhaven, 1991-03-30 - 1991-05-13, Version 2, 2025-02-17

description: Raw data acquired by position sensors on board RV Polarstern during expedition ANT-IX/4 was processed to receive a validated master track which can be used as reference of further expedition data. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
description: This dataset contains the master track in 10 min resolution, for other resolutions please see "Other version" references.The original version (doi:10.1594/PANGAEA.855926) was found to be erroneous (at the profile which was run at around latitude 0°) and was therefore replaced.
DOI: 10.57934/0b01e410805cd47f
title: Personen in donorregister
DOI: 10.1594/pangaea.979861
title: Branched glycerol dialkyl glycerol tetraether (brGDGTs) from the NGaoundaba peat deposit (Tropical Africa) covering the Holocene

description: This dataset includes lipid biomarker data from a peat sequence (named NGBA19) collected at the NGaoundaba peat deposit in 2019. The NGaoundaba peat deposit is located in North East Cameroon (N 7.135°, E 13.690°, 1175 m a.s.l). The 6-meter core was collected using a Russian peat corer. The core was subsampled at 2.5-cm intervals. Analyses were performed on 73 samples. Measurements were performed between 2020 and 2024 at the LGL-TPE (ENS de Lyon and University Claude Bernard Lyon 1). The NGBA19 core covers the last 10 ka (detail on the datation method and results are given in Schaaff et al. (2023, doi:10.1016/j.orggeochem.2023.104589). This dataset is associated to a publication: Sensitivity to climate and vegetation dynamics of a peatland record from Central Cameroon during the African Humid Period (QSR). The publication details the full method used to obtain the data. The study focus on paleoclimatic and paleoenvironmental reconstructions particularly during and after the African Humid Period. Branched glycerol dialkyl glycerol tetraethers (brGDGTs) peak areas (to be quantified using the peat area of the internal strandard C-46 of Hopmans et al. (2016, doi:10.1016/j.orggeochem.2006.05.008). These analyses were performed using HPLC-MS.
DOI: 10.1594/pangaea.979862
title: General lipid biomarker from the NGaoundaba peat deposit (Tropical Africa) covering the Holocene

description: This dataset includes lipid biomarker data from a peat sequence (named NGBA19) collected at the NGaoundaba peat deposit in 2019. The NGaoundaba peat deposit is located in North East Cameroon (N 7.135°, E 13.690°, 1175 m a.s.l). The 6-meter core was collected using a Russian peat corer. The core was subsampled at 2.5-cm intervals. Analyses were performed on 73 samples. Measurements were performed between 2020 and 2024 at the LGL-TPE (ENS de Lyon and University Claude Bernard Lyon 1). The NGBA19 core covers the last 10 ka (detail on the datation method and results are given in Schaaff et al. (2023, doi:10.1016/j.orggeochem.2023.104589). This dataset is associated to a publication: Sensitivity to climate and vegetation dynamics of a peatland record from Central Cameroon during the African Humid Period (QSR). The publication details the full method used to obtain the data. The study focus on paleoclimatic and paleoenvironmental reconstructions particularly during and after the African Humid Period. This file contains long-chain n-alkane data (n-C29, n-C31, n-C33 alkanes): relative abundance and concentration for each compounds and ratios (carbon preference index - CPI, average chain length - ACL and Paq). These data were collected using GC-MS (compound identification and quantification). The file also includes a ratio based on brGDGTs: the methylation of branched tetraethers (MBT'5Me) ratio and brGDGT-based temperature reconstructions using 4 different calibrations presented in the associated article.
DOI: 10.57934/0b01e410805ceb8c
title: Het innovatie onderzoek bevat gegevens over product-, en procesinnovatie activiteiten van bedrijven.
DOI: 10.1594/pangaea.979864
title: Raw pollen counts from the NGaoundaba peat deposit (Tropical Africa) covering the Holocene

description: This dataset includes pollen data from a peat sequence (named NGBA19) collected at the NGaoundaba peat deposit in 2019. The NGaoundaba peat deposit is located in North East Cameroon (N 7.135°, E 13.690°, 1175 m a.s.l). The 6-meter core was collected using a Russian peat corer. The core was subsampled at 2.5-cm intervals. Pollen analyses were performed on 60 samples. Measurements were performed at the IASCE paleoecology laboratory (University of South Florida). The NGBA19 core covers the last 10 ka (detail on the datation method and results are given in Schaaff et al. (2023, doi:10.1016/j.orggeochem.2023.104589). This dataset is associated to a publication: Sensitivity to climate and vegetation dynamics of a peatland record from Central Cameroon during the African Humid Period (QSR). The publication details the full method used to obtain the data. The study focus on paleoclimatic and paleoenvironmental reconstructions particularly during and after the African Humid Period. Pollen were prepared following standard methods, based on a treatment with 10% KOH followed by pollen retrieval using density separation. Pollen were counted using binocular microscope. Two tablets of Lycopodium sp. spores were added to each sample to allow quantification. Results are given in raw counts.
DOI: 10.15468/dl.unhbam
title: Occurrence Download

description: A dataset containing 18253 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Guazuma ulmifolia Lam.",
 "Year 2021-2025"
 ]
}

 The dataset includes 18253 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001555-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jkeuzz
title: Occurrence Download

description: A dataset containing 206 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-80.68805 35.39873,-77.90717 35.39873,-77.90717 37.90834,-80.68805 37.90834,-80.68805 35.39873))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vulpes vulpes (Linnaeus, 1758)"
 ]
}

 The dataset includes 206 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045348-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13896332
title: Example view data for running M-VIDIA

description: We provide three example data for running MVIDIA-DEA (views.zip),
                     MVIDIA-Patient Diagnosis (train.zip, test.zip) and for MVIDIA-Cell Clustering (sc.zip).
                     If each data can only be used for its corresponding task as the data
                     should be organized in the correct formats. Please visit our
                     webserver (http://www.ai4pro.tech:3838/) to learn more about our M-VIDIA.
DOI: 10.5281/zenodo.13896333
title: Example view data for running M-VIDIA

description: We provide three example data for running MVIDIA-DEA (views.zip),
                     MVIDIA-Patient Diagnosis (train.zip, test.zip) and for MVIDIA-Cell Clustering (sc.zip).
                     If each data can only be used for its corresponding task as the data
                     should be organized in the correct formats. Please visit our
                     webserver (http://www.ai4pro.tech:3838/) to learn more about our M-VIDIA.
DOI: 10.15468/dl.fhgrmd
title: Occurrence Download

description: A dataset containing 2844 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anopheles darlingi Root, 1926"
 ]
}

 The dataset includes 2844 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045349-240906103802322/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.27176475
title: GaMD for ANP-bound GC-A

description: Topology file: step5_input.parm7 (AMBER format)Initial coordinate file: step5_input.rst7 (AMBER format)GaMD equilibration input file: md.inGaMD production input file: gamd-restart.inFinal snapshot of GaMD simulations (500ns): run1-gamd-500ns.pdb (simulation 1);run2-gamd-500ns.pdb (simulation 2);run3-gamd-500ns.pdb (simulation 3).
DOI: 10.6084/m9.figshare.27176475.v1
title: GaMD for ANP-bound GC-A

description: Topology file: step5_input.parm7 (AMBER format)Initial coordinate file: step5_input.rst7 (AMBER format)GaMD equilibration input file: md.inGaMD production input file: gamd-restart.inFinal snapshot of GaMD simulations (500ns): run1-gamd-500ns.pdb (simulation 1);run2-gamd-500ns.pdb (simulation 2);run3-gamd-500ns.pdb (simulation 3).
DOI: 10.6084/m9.figshare.27176445
title: GaMD simulation for apo GC-A

description: Topology file: step5_input.parm7 (AMBER format)Initial coordinate file: step5_input.rst7 (AMBER format)GaMD equilibration input file: md.inGaMD production input file: gamd-restart.inFinal snapshot of GaMD simulations (500ns):run1-gamd-500ns.pdb (simulation 1);run2-gamd-500ns.pdb (simulation 2);run3-gamd-500ns.pdb (simulation 3)
DOI: 10.6084/m9.figshare.27176436
title: Data for: Post-fire Vegetation Dynamic Patterns and Drivers in Greater Hinggan Mountains: Insights from Long-term Remote Sensing Data Analysis

description: The compressed package includes the foundational data, code, and the open-source GWR model installer used in this study. The foundational data encompasses EVI, driving factor data, and derivative results obtained from trend analysis. The code, primarily used for some of the trend analyses in this study, is written in MATLAB.
DOI: 10.6084/m9.figshare.27176436.v1
title: Research Data.rar

description: The compressed package includes the foundational data, code, and the open-source GWR model installer used in this study. The foundational data encompasses EVI, driving factor data, and derivative results obtained from trend analysis. The code, primarily used for some of the trend analyses in this study, is written in MATLAB.
DOI: 10.15468/dl.qjwj4a
title: Occurrence Download

description: A dataset containing 6046 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bursera simaruba (L.) Sarg."
 ]
}

 The dataset includes 6046 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045351-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vfw44z
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scaphiophryne spinosa Steindachner, 1882"
 ]
}

 The dataset includes 41 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045352-240906103802322/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.27176562
title: Informing the cannabis policy debate: a cross-sectional study of current and former cannabis users in Ireland

description: Cannabis is the most widely used illicit drug with considerable international discourse regarding its legal status. This study sought to examine the wellbeing, experiences, and attitudes of adults who have used cannabis to inform policy debates. A national, cross-sectional survey was completed. Data related to demographics and attitudes was collected along with validated questionnaires to measure level of dependence and wellbeing. Respondents (<i>n</i> = 732) were primarily males (61%) with a median age of 21. Three-quarters (75%) consumed cannabis more than 100 days with few regretting their cannabis use. Additionally, 60% reported previous use of both cocaine and MDMA and three-quarters currently use tobacco. While strongly in favor of more liberal cannabis policies they were ambivalent about decriminalizing all drugs. Depending on the cutoff used, 14.6% to 32.2% of respondents potentially meet the criteria for cannabis dependence. Wellbeing was overall good; however, women were at significantly higher odds of poor wellbeing (OR = 2.59; 95% CI = 1.78, 3.76). Findings suggest unanimity among cannabis users toward more liberal legal policies but have discord regarding other drugs. Harm reduction, particularly in relation to tobacco, other substances, and women is indicated.
DOI: 10.15468/dl.ca4evg
title: Occurrence Download

description: A dataset containing 42394 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample, Observation, Machine Observation, Human Observation, Material citation, Fossil, Living Specimen, Occurrence evidence)",
 "TaxonKey is Astrocaryum G.Mey."
 ]
}

 The dataset includes 42394 records from 320 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045353-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-09.2894754/2456124
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894755/2456125
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894759/2456126
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894760/2456127
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894761/2456128
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894762/2456129
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894763/2456130
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894764/2456131
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894767/2456132
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894768/2456133
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894769/2456134
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894770/2456135
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894771/2456136
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894772/2456137
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894773/2456138
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894774/2456139
title: Data for EMSL Project 51287 from September 2023
DOI: 10.5281/zenodo.13896350
title: Datasets used for case studies in M-VIDIA paper

description: We provide the extracted view data from the datasets we used for our case studies.
                     There are three datasets, including the Thyroid Nodule Classification (TNC) dataset, 
                     the Single Mouse Oocytes (SMO) dataset, and the Pick-up Single-cell Proteomic Analysis (PiSPA) dataset.
                     The TNC dataset is used to test the performance of applying M-VIDIA 
                     for patient diagnosis. The SMO and PiSPA are used to test the performance
                      of M-VIDIA in cell clustering.
DOI: 10.5281/zenodo.13896351
title: Datasets used for case studies in M-VIDIA paper

description: We provide the extracted view data from the datasets we used for our case studies.
                     There are three datasets, including the Thyroid Nodule Classification (TNC) dataset, 
                     the Single Mouse Oocytes (SMO) dataset, and the Pick-up Single-cell Proteomic Analysis (PiSPA) dataset.
                     The TNC dataset is used to test the performance of applying M-VIDIA 
                     for patient diagnosis. The SMO and PiSPA are used to test the performance
                      of M-VIDIA in cell clustering.
DOI: 10.25582/data.2023-09.2894775/2456140
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894776/2456141
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894777/2456142
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894778/2456143
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894779/2456144
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894781/2456145
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894782/2456146
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894783/2456147
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894785/2456148
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894786/2456149
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894787/2456150
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894788/2456151
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894789/2456152
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894790/2456153
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894791/2456154
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894792/2456155
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894793/2456156
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894794/2456157
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894795/2456158
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894800/2456159
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894801/2456160
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894802/2456161
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894803/2456162
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894804/2456163
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894806/2456164
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894807/2456165
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894808/2456166
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894809/2456167
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894816/2456168
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894820/2456169
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894821/2456170
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894822/2456171
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894823/2456172
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894824/2456173
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894825/2456174
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894826/2456175
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894828/2456176
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894829/2456177
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894832/2456178
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894837/2456179
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894839/2456180
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894840/2456181
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894842/2456182
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894843/2456183
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894844/2456184
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894846/2456185
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894847/2456186
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894850/2456187
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894851/2456188
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894857/2456189
title: Data for EMSL Project 51287 from September 2023
DOI: 10.15468/dl.bv45ew
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Saksenaea vasiformis S.B.Saksena"
 ]
}

 The dataset includes 73 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045354-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-09.2894858/2456190
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894859/2456191
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894860/2456192
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894861/2456193
title: Data for EMSL Project 51287 from September 2023
DOI: 10.25582/data.2023-09.2894862/2456194
title: Data for EMSL Project 51287 from September 2023