cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/brnd8yc4b7.2
title: Concrete Core Test Results - Sudan (2015-2021)

description: This file consists of 629 concrete core test results collected from three different laboratories: 1) The University of Khartoum Concrete and Materials Laboratory (UofK CML): where 464 results are collected; 2) Building and Roads Research Institute Laboratory (BRRI) where 136 results are collected; and 3) Engineering Services and Design Laboratory (ESD) where 29 results are collected. The contributor make this data available in order to be used by researcher in the future research work in Sudan or around the globe.

The data collection time-frame is between 2015 to 2021 (6 years).
DOI: 10.17632/77m52yvm9b
title: RSEI data

description: RSEI data from 2001 to 2022.
DOI: 10.17632/77m52yvm9b.1
title: RSEI data

description: RSEI data from 2001 to 2022.
DOI: 10.15468/dl.4y33bb
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eucometis penicillata stictothorax"
 ]
}

 The dataset's 2 records were derived from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022605-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/27czn6v75d
title: Dataset for "Corporate Green Innovation and Financial Performance Under Environmental Regulation: Evidence from Moderated Mediation Approach"

description: This study examines the impact of environmental regulation stringency (ERS) on firms' financial performance, along with the mechanisms driving these effects, within a command-and-control regulatory framework. Using a sample of 4,874 listed firms in China from 2016 to 2020, we document a positive relationship between ERS and firm financial performance. Moreover, we find that the positive effect of ERS on financial performance can be mediated by a reduction in green innovation activities, which are typically associated with high costs that firms may struggle to afford under greater regulatory pressures for pollution control. Further evidence suggests that green bond issuance can significantly mitigate the inhibitory effect of ERS on green innovation, whereas environmental subsidy is ineffective.
DOI: 10.15468/dl.5ekmxp
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus mykiss",
 "Country is Lesotho",
 "HasCoordinate is true"
 ]
}

 The dataset includes 55 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022623-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/27czn6v75d.1
title: Dataset for "Corporate Green Innovation and Financial Performance Under Environmental Regulation: Evidence from Moderated Mediation Approach"

description: This study examines the impact of environmental regulation stringency (ERS) on firms' financial performance, along with the mechanisms driving these effects, within a command-and-control regulatory framework. Using a sample of 4,874 listed firms in China from 2016 to 2020, we document a positive relationship between ERS and firm financial performance. Moreover, we find that the positive effect of ERS on financial performance can be mediated by a reduction in green innovation activities, which are typically associated with high costs that firms may struggle to afford under greater regulatory pressures for pollution control. Further evidence suggests that green bond issuance can significantly mitigate the inhibitory effect of ERS on green innovation, whereas environmental subsidy is ineffective.
DOI: 10.15468/dl.26bzrr
title: Occurrence Download

description: A dataset containing 9233 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Andropogon virginicus, Andropogon virginicus virginicus, Andropogon glaucescens, Andropogon virginicus decipiens, Andropogon vaginatus, Andropogon macrourus glaucopsis, Andropogon pauciflorus, Anatherum virginicum, Andropogon eriophorus, Holcus virginicus, Andropogon dissitiflorus vaginatus, Andropogon virginicus genuinus, Anatherum virginicum, Andropogon virginicus scabriglumus, Andropogon pauciflorus, Andropogon tetrastachyus, Dimeiostemon tetrastachys, Andropogon dissitiflorus vaginatus, Dimeiostemon vaginatus, Andropogon virginicus genuinus, Dimeiostemon vaginatus, Andropogon dissitiflorus, Dimeiostemon tetrastachys, Andropogon macrourus viridis, Andropogon curtisianus, Andropogon louisianae, Andropogon virginicus viridis, Andropogon decipiens, Andropogon virginicus vaginatus, Andropogon virginicus vaginatus, Sorghum virginicum, Cymbopogon glaucus, Andropogon virginicus tetrastachyus, Anatherum virginicum tetrastachyum, Cinna lateralis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 9233 records from 163 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022624-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16276296
title: A Systematic Literature Review on Cybersecurity Threats and Mitigation Strategies in Industrial Control Systems

description: A Systematic Literature Review on Cybersecurity Threats and Mitigation Strategies in Industrial Control Systems
DOI: 10.5281/zenodo.16276297
title: A Systematic Literature Review on Cybersecurity Threats and Mitigation Strategies in Industrial Control Systems

description: A Systematic Literature Review on Cybersecurity Threats and Mitigation Strategies in Industrial Control Systems
DOI: 10.15468/dl.96zdrw
title: Occurrence Download

description: A dataset containing 72 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CollectionKey is one of (741f12d3-ebfc-48e7-9d8c-180d41b0a582)",
 "DatasetName is one of (Herbier Louis-Marie (QFA) - Collection de plantes vasculaires, Herbier Louis-Marie (QFA) - Collection de bryophytes)",
 {
 "or" : [
 "RecordedBy ~Brantford",
 "RecordedBy ~Brousseau, Pierre"
 ]
 },
 "EventDate 1977-07-20-1988-08-15"
 ]
}

 The dataset includes 72 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022625-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2rh74898z7.1
title: Codes for A Cutting-Edge Conceptual Reservoir Operation-Based Deep Learning Framework

description: Training and analysing code for A Cutting-Edge Conceptual Reservoir Operation-Based Deep Learning Framework (CRO-LSTM)
DOI: 10.17632/b73p83csty
title: Do social preferences explain health inequality aversion?

description: This code accompanies the paper Robson, Doran, O'Donnell and Van Ourti (2025), "Do social preferences explain health inequality aversion?". In the paper, we design and run an online experiment, with a sample of the UK adult population, to estimate health inequality aversion at the individual level. We additionally elicit social preferences over own and others' health, alongside a rich set of socio-demographics, to explain variation in health inequality aversion. Here, we provide data and code of the experiment and our analysis. The Experiment folder contains an R-Shiny app to run our experiment. The Stata folder contains experimental data and analytical code. Note that we have removed some variables from the dataset, due to data privacy. Please contact us if you have any questions or want to request the full dataset.
DOI: 10.17632/b73p83csty.1
title: Do social preferences explain health inequality aversion?

description: This code accompanies the paper Robson, Doran, O'Donnell and Van Ourti (2025), "Do social preferences explain health inequality aversion?". In the paper, we design and run an online experiment, with a sample of the UK adult population, to estimate health inequality aversion at the individual level. We additionally elicit social preferences over own and others' health, alongside a rich set of socio-demographics, to explain variation in health inequality aversion. Here, we provide data and code of the experiment and our analysis. The Experiment folder contains an R-Shiny app to run our experiment. The Stata folder contains experimental data and analytical code. Note that we have removed some variables from the dataset, due to data privacy. Please contact us if you have any questions or want to request the full dataset.
DOI: 10.57760/sciencedb.j00167.00031
title: CL AGN candidate catalog and comfirmed CL AGNs
title: CL AGN candidate catalog and comfirmed CL AGNs

description: This dataset includes (1) a table of 211 CLAGN candidates with their basic properties (Table 3), and (2) a machine-readable figure set showing the light curves and spectra for each confirmed CLAGN (Figure 4). For detailed descriptions, see Table 3 and Figure 4 in the accompanying publication.
description: This dataset includes (1) a table of 211 CLAGN candidates with their basic properties (Table 3), and (2) a machine-readable figure set showing the light curves and spectra for each confirmed CLAGN (Figure 4). For detailed descriptions, see Table 3 and Figure 4 in the accompanying publication.
DOI: 10.17632/3n6ghvszjb.1
title: A Forecast Panel Dataset of GDP Growth from ADB, EBRD, and World Bank

description: This dataset contains GDP growth forecasts compiled from the Asian Development Bank (ADB), the European Bank for Reconstruction and Development (EBRD), and the World Bank (WB). The dataset spans forecast vintages from 1989 to 2024 along with realized values. It covers 45 countries for ADB, 38 for EBRD, and 150 for WB as of Fall 2024, with varying availability over time.
DOI: 10.15468/dl.r9y4np
title: Occurrence Download

description: A dataset containing 33115 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Genista hispanica"
 ]
}

 The dataset includes 33115 records from 362 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022626-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18512933
title: Research data for " Competing magnetic instabilities and self-doping effects in KFe2As2 under pressure"
DOI: 10.5281/zenodo.18512932
title: Research data for " Competing magnetic instabilities and self-doping effects in KFe2As2 under pressure"
DOI: 10.15468/dl.pnkptn
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Luzula elegans",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 38 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017956-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u6gej4
title: Occurrence Download

description: A dataset containing 9384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trachemys scripta",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 1999"
 ]
}

 The dataset includes 9384 records from 159 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017957-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7swusa
title: Occurrence Download

description: A dataset containing 182 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Marsippospermum gracile",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 182 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017959-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qe9vqv
title: Occurrence Download

description: A dataset containing 926 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "TaxonKey is Prosopis juliflora"
 ]
}

 The dataset includes 926 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017958-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18513909
title: SARS-CoV-2 Infektionen in Deutschland

description: Im Datensatz "SARS-CoV-2 Infektionen in Deutschland" des Robert Koch-Instituts werden die Daten basierend auf Meldungen zu SARS-CoV-2 Infektionen nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Darin enthalten sind Informationen auf Landkreisebene zu bestätigten Infektionen, Todesfällen und Genesungen, differenziert nach Altersgruppen und Geschlecht. Diese Daten dienen als Grundlage für epidemiologische Bewertungen und gesundheitspolitische Maßnahmen.
DOI: 10.15468/dl.q3e3w2
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Patosia clandestina",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 17 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017960-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tqe7xs
title: Occurrence Download

description: A dataset containing 6969 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trachemys scripta",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2009"
 ]
}

 The dataset includes 6969 records from 250 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017961-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ccqwsr
title: Occurrence Download

description: A dataset containing 180355 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= -16.25916876999866
 AND decimallatitude &lt;= -12.166598047573723
 AND decimallongitude &gt;= 131.5426849906249
 AND decimallongitude &lt;= 138.1384255308636
 AND GBIF_Within('POLYGON ((138.138426 -16.259169, 138.138426 -12.166598, 131.542685 -12.166598, 131.542685 -16.259169, 138.138426 -16.259169))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 180355 records were derived from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017952-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zuj2bn
title: Occurrence Download

description: A dataset containing 21366 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lampyridae"
 ]
}

 The dataset includes 21366 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017962-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfaawt
title: Occurrence Download

description: A dataset containing 1042 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mayaca fluviatilis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1042 records from 161 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017963-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18513602
title: High-Resolution (30 m) Flood Susceptibility Mapping Data of Pakistan

description: Dataset Description

This dataset provides national-scale, high-resolution (30-meter) Flood Susceptibility Maps (FSM) for Pakistan. These rasters were generated using an integrated framework combining Machine Learning (ML) and Explainable AI (EAI), as detailed in the research article "High-resolution flood susceptibility mapping and exposure assessment in Pakistan" published in the International Journal of Disaster Risk Reduction.

→ Project Updates & Code:For Google Earth Engine (GEE) applications, dataset details, and related source codes, please visit the official GitHub repository:https://github.com/waleedgeo/fsm-pk





Files Included

The dataset includes two raster layers representing flood susceptibility predictions derived from Light Gradient Boosting Machine (LGBM) and eXtreme Gradient Boosting (XGBoost) models.



1. fsm_lgbm_pakistan.tif



Model: Light Gradient Boosting Machine (LGBM)

Performance: This model demonstrated the highest reliability in the study, with an Adjusted Accuracy of 0.85 and an AUC of 0.81.

Format: Unsigned 8-bit Integer (UInt8) GeoTIFF




 



2. fsm_xgboost_pakistan.tif



Model: eXtreme Gradient Boosting (XGBoost)

Performance: Adjusted Accuracy of 0.82 and an AUC of 0.81.

Format: Unsigned 8-bit Integer (UInt8) GeoTIFF






Data Values & Interpretation

The pixel values in both raster files have been classified into 5 discrete susceptibility categories based on quantile distribution:



1: Very Low

2: Low

3: Moderate

4: High

5: Very High


Methodology Note:The models were trained on a balanced inventory of 20,000 historical flood/non-flood points derived from major flood events (2010, 2014, 2022). Ten flood conditioning features were utilized, including FABDEM elevation, slope, aspect, curvature, TWI, distance to river/drainage, NDVI, rainfall frequency, and distance to roads.



Citation

If you utilize this data, please cite the original research article:



Waleed, M., & Sajjad, M. (2025). High-resolution flood susceptibility mapping and exposure assessment in Pakistan: An integrated artificial intelligence, machine learning and geospatial framework. International Journal of Disaster Risk Reduction, 121, 105442. https://doi.org/10.1016/j.ijdrr.2025.105442


Contact



Portfolio: https://waleedgeo.com/

Email: waleedgeo@outlook.com
DOI: 10.5281/zenodo.18513601
title: High-Resolution (30 m) Flood Susceptibility Mapping Data of Pakistan

description: Dataset Description

This dataset provides national-scale, high-resolution (30-meter) Flood Susceptibility Maps (FSM) for Pakistan. These rasters were generated using an integrated framework combining Machine Learning (ML) and Explainable AI (EAI), as detailed in the research article "High-resolution flood susceptibility mapping and exposure assessment in Pakistan" published in the International Journal of Disaster Risk Reduction.

→ Project Updates & Code:For Google Earth Engine (GEE) applications, dataset details, and related source codes, please visit the official GitHub repository:https://github.com/waleedgeo/fsm-pk





Files Included

The dataset includes two raster layers representing flood susceptibility predictions derived from Light Gradient Boosting Machine (LGBM) and eXtreme Gradient Boosting (XGBoost) models.



1. fsm_lgbm_pakistan.tif



Model: Light Gradient Boosting Machine (LGBM)

Performance: This model demonstrated the highest reliability in the study, with an Adjusted Accuracy of 0.85 and an AUC of 0.81.

Format: Unsigned 8-bit Integer (UInt8) GeoTIFF




 



2. fsm_xgboost_pakistan.tif



Model: eXtreme Gradient Boosting (XGBoost)

Performance: Adjusted Accuracy of 0.82 and an AUC of 0.81.

Format: Unsigned 8-bit Integer (UInt8) GeoTIFF






Data Values & Interpretation

The pixel values in both raster files have been classified into 5 discrete susceptibility categories based on quantile distribution:



1: Very Low

2: Low

3: Moderate

4: High

5: Very High


Methodology Note:The models were trained on a balanced inventory of 20,000 historical flood/non-flood points derived from major flood events (2010, 2014, 2022). Ten flood conditioning features were utilized, including FABDEM elevation, slope, aspect, curvature, TWI, distance to river/drainage, NDVI, rainfall frequency, and distance to roads.



Citation

If you utilize this data, please cite the original research article:



Waleed, M., & Sajjad, M. (2025). High-resolution flood susceptibility mapping and exposure assessment in Pakistan: An integrated artificial intelligence, machine learning and geospatial framework. International Journal of Disaster Risk Reduction, 121, 105442. https://doi.org/10.1016/j.ijdrr.2025.105442


Contact



Portfolio: https://waleedgeo.com/

Email: waleedgeo@outlook.com
DOI: 10.6084/m9.figshare.26970220
title: Global Urban Tree Species (GUTS): Revealing tree species diversity across the world’s urban areas

description: Diverse tree communities can bolster urban ecosystem resilience and provide vital ecosystem services. However, existing urban tree species datasets have limited geographic coverage and contain inadequate attributes. To address those gaps, we developed the Global Urban Tree Species (GUTS) dataset by integrating data from literature, biodiversity databases, and other open sources. The new dataset encompasses 159,845 occurrence records of 10,094 tree species in 8,349 cities and 139 countries. Among them, 109,879 records were confirmed from urban areas, representing 11.18% of global tree species diversity. The dataset has been validated using multiple methods. GUTS fills critical data gaps and provides a foundation for future research and management of global urban biodiversity.
DOI: 10.6084/m9.figshare.26970220.v2
title: Global Urban Tree Species (GUTS): Revealing tree species diversity across the world’s urban areas

description: Diverse tree communities can bolster urban ecosystem resilience and provide vital ecosystem services. However, existing urban tree species datasets have limited geographic coverage and contain inadequate attributes. To address those gaps, we developed the Global Urban Tree Species (GUTS) dataset by integrating data from literature, biodiversity databases, and other open sources. The new dataset encompasses 159,845 occurrence records of 10,094 tree species in 8,349 cities and 139 countries. Among them, 109,879 records were confirmed from urban areas, representing 11.18% of global tree species diversity. The dataset has been validated using multiple methods. GUTS fills critical data gaps and provides a foundation for future research and management of global urban biodiversity.