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

description: A dataset containing 319 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anseriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((60 -60,90 -60,90 -30,60 -30,60 -60))"
 ]
}

 The dataset includes 319 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063613-250920141307145/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.30312532
title: Data for: Distinguishing On-Year and Off-Year Improves Remote Sensing Estimation Accuracy of Aboveground Biomass in Moso Bamboo Forests.

description: This study proposes a biomass estimation method that integrates Moso bamboo's on-year/off-year growth cycle characteristics by combining Sentinel-2 remote sensing data with machine learning technology. The research first achieved high-precision identification of bamboo forest growth cycles using the Support Vector Machine (SVM) algorithm based on multispectral imagery. Subsequently, through PLSR variable importance analysis, the red-edge, near-infrared, and short-wave infrared bands were identified as key spectral features for biomass estimation, and a hybrid PLSR-CNN estimation model was developed. Comparative results between observed and predicted values demonstrate that incorporating the on-year/off-year stratification strategy significantly improves model accuracy compared to conventional non-stratified estimation models.
DOI: 10.6084/m9.figshare.30312532.v1
title: Data for: Distinguishing On-Year and Off-Year Improves Remote Sensing Estimation Accuracy of Aboveground Biomass in Moso Bamboo Forests.

description: This study proposes a biomass estimation method that integrates Moso bamboo's on-year/off-year growth cycle characteristics by combining Sentinel-2 remote sensing data with machine learning technology. The research first achieved high-precision identification of bamboo forest growth cycles using the Support Vector Machine (SVM) algorithm based on multispectral imagery. Subsequently, through PLSR variable importance analysis, the red-edge, near-infrared, and short-wave infrared bands were identified as key spectral features for biomass estimation, and a hybrid PLSR-CNN estimation model was developed. Comparative results between observed and predicted values demonstrate that incorporating the on-year/off-year stratification strategy significantly improves model accuracy compared to conventional non-stratified estimation models.
DOI: 10.15468/dl.qkkc7f
title: Occurrence Download

description: A dataset containing 2687935 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anseriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((120 -60,150 -60,150 -30,120 -30,120 -60))"
 ]
}

 The dataset includes 2687935 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063555-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ex3aq4
title: Occurrence Download

description: A dataset containing 428 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Donax hanleyanus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 428 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063614-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.29qpcw
title: Occurrence Download

description: A dataset containing 714196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Procellariiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-150 30,-120 30,-120 60,-150 60,-150 30))"
 ]
}

 The dataset includes 714196 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063546-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17299249
title: SEM Withered Plant (BSE Series) — Kikoh Matsuura (Art–Science Archive)

description: Parent (series) record for *SEM Withered Plant (BSE)* by Kikoh Matsuura.  This record serves as the hub for all child datasets in the series.

**Files included:**- A series overview (TXT) documenting scope, naming rules, citation style, and file policy- A machine-readable index (CSV) that will be updated to list child datasets (DOIs, imaging parameters, etc.)

Each child dataset contains raw, uncompressed BMP images (≈13 per set, number varies) acquired with a personally owned TECHNEX TinySEM M3-i using the BSE detector under high-vacuum conditions.  Child records provide detailed READMEs with exact parameters (accelerating voltage, working distance, vacuum, pixel size, field of view, frame time, coating).

This parent provides a stable concept DOI for the entire *SEM Withered Plant (BSE)* series.  Child datasets link back via *IsPartOf*, and this parent enumerates them via *HasPart*.  

*This series visualizes the hidden order and chance in withered plants through SEM-BSE, leaving a unique trace at the boundary between art and science.*
DOI: 10.15468/dl.fxnn8m
title: Occurrence Download

description: A dataset containing 17646 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anseriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((30 -60,60 -60,60 -30,30 -30,30 -60))"
 ]
}

 The dataset includes 17646 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063615-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rsj9ds
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhadinopsylla pentacantha",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063616-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x9b6sk
title: Occurrence Download

description: A dataset containing 4205 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Neolitsea sericea)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4205 records from 114 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063619-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fmb64
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anseriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-30 -60,0 -60,0 -30,-30 -30,-30 -60))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063620-250920141307145/datasets/export for details.
DOI: 10.6084/m9.figshare.29937992.v1
title: Supplementary of tableS1 and method

description: <b>A Favorable SNP Allelic Variation and DUF538 Protein Confer Partial Resistance to </b><b>Empoasca onukii</b><b>in Tea</b>
DOI: 10.15468/dl.2e966j
title: Occurrence Download

description: A dataset containing 372 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hydrangea hypoglauca"
 ]
}

 The dataset includes 372 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063624-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzr6du
title: Occurrence Download

description: A dataset containing 1078345 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-08-13",
 "EventDate is less than or equal to 2025-09-12",
 {
 "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)"
 ]
 }
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1078345 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063592-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xd5s9c
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Donax pulchellus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is one of (Absent)"
 ]
 }
 }
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063622-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b9sgj5
title: Occurrence Download

description: A dataset containing 1186 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 (CAST(occurrence.taxonkey AS INTEGER) = 2436602 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 2436602 OR CAST(occurrence.kingdomkey AS INTEGER) = 2436602 OR CAST(occurrence.phylumkey AS INTEGER) = 2436602 OR CAST(occurrence.classkey AS INTEGER) = 2436602 OR CAST(occurrence.orderkey AS INTEGER) = 2436602 OR CAST(occurrence.familykey AS INTEGER) = 2436602 OR CAST(occurrence.genuskey AS INTEGER) = 2436602 OR CAST(occurrence.specieskey AS INTEGER) = 2436602)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 1186 records were derived from 138 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063585-250920141307145/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.29937992.v2
title: Supplementary of tableS1 and method

description: <b>A Favorable SNP Allelic Variation and DUF538 Protein Confer Partial Resistance to </b><b>Empoasca onukii</b><b>in Tea</b>
DOI: 10.6084/m9.figshare.30284752
title: <b>How Digital Financial Inclusion can Drive the Revitalisation of Rural Industries: Taking the Agricultural Product Processing Industry as an Example</b>

description: Digital inclusive finance provides a new opportunity to alleviate the contradiction between financial supply and demand in the agricultural product processing industry, which is of great significance in boosting the revitalisation of rural industries. Based on China’s provincial panel data from 2011-2022, the effects and mechanisms of digital inclusive finance on different agricultural product processing industries are analysed. The study shows that digital inclusive finance has a significant positive impact on the agricultural product processing industry, and this impact effect is more significant in the central and western regions of China as well as the main grain producing areas. Digital financial inclusion has a significant positive impact on the food and timber processing industry, while the impact on the clothing, rubber and paper products processing industry is not significant, digital financial inclusion significantly and positively affects the agricultural products processing industry by promoting technological innovation and improving the degree of marketisation in these two paths. It is recommended to strengthen the construction of the digital inclusive financial system, promote the high-quality development of the agro-processing industry through the promotion of technological innovation and the improvement of marketisation, and improve and formulate the support policies for regional differentiation and industrial differentiation.
DOI: 10.6084/m9.figshare.30284752.v1
title: <b>How Digital Financial Inclusion can Drive the Revitalisation of Rural Industries: Taking the Agricultural Product Processing Industry as an Example</b>

description: Digital inclusive finance provides a new opportunity to alleviate the contradiction between financial supply and demand in the agricultural product processing industry, which is of great significance in boosting the revitalisation of rural industries. Based on China’s provincial panel data from 2011-2022, the effects and mechanisms of digital inclusive finance on different agricultural product processing industries are analysed. The study shows that digital inclusive finance has a significant positive impact on the agricultural product processing industry, and this impact effect is more significant in the central and western regions of China as well as the main grain producing areas. Digital financial inclusion has a significant positive impact on the food and timber processing industry, while the impact on the clothing, rubber and paper products processing industry is not significant, digital financial inclusion significantly and positively affects the agricultural products processing industry by promoting technological innovation and improving the degree of marketisation in these two paths. It is recommended to strengthen the construction of the digital inclusive financial system, promote the high-quality development of the agro-processing industry through the promotion of technological innovation and the improvement of marketisation, and improve and formulate the support policies for regional differentiation and industrial differentiation.
DOI: 10.15468/dl.2kttqq
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Archaeopsylla erinacei",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 61 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063626-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5q5ar5
title: Occurrence Download

description: A dataset containing 4104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Neoshirakia japonica)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4104 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063629-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bhsfut
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Armadillidium depressum",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063632-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17299114
title: WRF simulates the case study of atmospheric parameters before and after the DQ-1 satellite's high spectral resolution lidar passes the ground station of the Asian dust and aerosol lidar observation network

description: The WRF mode is used to generate meteorological data with higher temporal resolution, serving as supplementary analysis data for the meteorological conditions at ground-based stations when the DQ-1 satellite passes by ground lidar stations. The introduction of its time and center point is all stated in the data file.
DOI: 10.5281/zenodo.17299115
title: WRF simulates the case study of atmospheric parameters before and after the DQ-1 satellite's high spectral resolution lidar passes the ground station of the Asian dust and aerosol lidar observation network

description: The WRF mode is used to generate meteorological data with higher temporal resolution, serving as supplementary analysis data for the meteorological conditions at ground-based stations when the DQ-1 satellite passes by ground lidar stations. The introduction of its time and center point is all stated in the data file.
DOI: 10.15468/dl.3d8d5b
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nephelium topengii)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 48 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063636-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y983v3
title: Occurrence Download

description: A dataset containing 2555 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "OccurrenceStatus is Present",
 "TaxonKey is Hippocampus erectus"
 ]
}

 The dataset includes 2555 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063633-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57687/fk2/pjgkvp/nk2opq
title: Professor Collection Data Dictionary.tab

description: :unav
DOI: 10.57687/fk2/pjgkvp/0mzlq6
title: Professor Collection Data Dictionary.tab

description: :unav
DOI: 10.57687/fk2/pjgkvp/4jrbxd
title: Professor Collection - Data Dictionary.tab

description: :unav
DOI: 10.57687/fk2/pjgkvp
title: Professor Collection

description: This collection gathers data of professors of the Tecnológico de Monterrey, from 1996 to date. Some of the categories of variables that are available in this collection are: -Sociodemographic data (age, gender, region). -Academic information (academic program, degree, GPA). -Teaching profile (academic level, job description, SNI data).
DOI: 10.6084/m9.figshare.30312571
title: Data Source of Neglected Risks in the Chinese Insurers’ Misconduct Caused by Digitalization

description: In this database, we have made publicly available partial data from an empirical study on the impact of digital transformation in insurers' misconduct. This dataset is a company-year panel data. The database mainly includes digital transformation data (extracted from annual report text analysis) and data on company financial status, internal structure, and personnel composition (obtained from the China Insurance Statistical Yearbook).To protect company privaMisconductcy, the data has been anonymized. Since the dependent variable (Misconduct) is obtained from government documents, considering the sensitivity of the data, this part is not disclosed.
DOI: 10.6084/m9.figshare.30312571.v1
title: Data Source of Neglected Risks in the Chinese Insurers’ Misconduct Caused by Digitalization

description: In this database, we have made publicly available partial data from an empirical study on the impact of digital transformation in insurers' misconduct. This dataset is a company-year panel data. The database mainly includes digital transformation data (extracted from annual report text analysis) and data on company financial status, internal structure, and personnel composition (obtained from the China Insurance Statistical Yearbook).To protect company privaMisconductcy, the data has been anonymized. Since the dependent variable (Misconduct) is obtained from government documents, considering the sensitivity of the data, this part is not disclosed.
DOI: 10.15468/dl.htn98a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Balanus amphitrite",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063637-250920141307145/datasets/export for details.
DOI: 10.15468/dl.q934rb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Balanus amphitrite",
 "Country is Korea, Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063638-250920141307145/datasets/export for details.