cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3pbhfhnh2g
title: Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina

description: This dataset originates from a research entitled: "Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina" , this study investigates the initial evolution of volcanic ash deposited by the Chaitén volcano in the Andean-Patagonian Region of Argentina and how different vegetation types influence its transformation. The research is part of a broader project titled "Soil neoformation and edaphic changes associated with conifer plantation in areas affected by recent volcanic eruptions."

To conduct this study, four sampling sites were selected along a west-east transect, where pine ponderosa plantations border native Cordillera cypress forests. Fifteen years later of the eruption undisturbed soil profile samples were collected for micromorphological analyses, while disturbed ash samples underwent physical, chemical, and biological assessments. Additionally, two ash samples from the May 2008 eruption were preserved and utilized as reference materials.

The dataset provides a description of the micromorphological characteristics of the ash and soil under different vegetation (cypress forests and pine plantations). Data obtained from the physical-chemical and biological analyses of the ash at the time of fall and fifteen years after its deposition are also provided. These data contribute valuable insights into post-eruption soil formation processes and the role of vegetation in modifying volcanic deposits.

For accessibility, the dataset has been deposited in Mendelay Data repository, ensuring transparency and reproducibility for future research. Proper citation and linking within academic publications facilitate integration into broader studies on soil evolution and volcanic ash dynamics.
DOI: 10.17632/3pbhfhnh2g.2
title: Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina

description: This dataset originates from a research entitled: "Evolution of recent volcanic ash deposits under native and planted temperate forests in Patagonia, Argentina" , this study investigates the initial evolution of volcanic ash deposited by the Chaitén volcano in the Andean-Patagonian Region of Argentina and how different vegetation types influence its transformation. The research is part of a broader project titled "Soil neoformation and edaphic changes associated with conifer plantation in areas affected by recent volcanic eruptions."

To conduct this study, four sampling sites were selected along a west-east transect, where pine ponderosa plantations border native Cordillera cypress forests. Fifteen years later of the eruption undisturbed soil profile samples were collected for micromorphological analyses, while disturbed ash samples underwent physical, chemical, and biological assessments. Additionally, two ash samples from the May 2008 eruption were preserved and utilized as reference materials.

The dataset provides a description of the micromorphological characteristics of the ash and soil under different vegetation (cypress forests and pine plantations). Data obtained from the physical-chemical and biological analyses of the ash at the time of fall and fifteen years after its deposition are also provided. These data contribute valuable insights into post-eruption soil formation processes and the role of vegetation in modifying volcanic deposits.

For accessibility, the dataset has been deposited in Mendelay Data repository, ensuring transparency and reproducibility for future research. Proper citation and linking within academic publications facilitate integration into broader studies on soil evolution and volcanic ash dynamics.
DOI: 10.34740/kaggle/dsv/13735966
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17632/fhrht9g289
title: Azathioprine-loaded Beads

description: Scanning Electron Microscopy Images for the colon-targeted beads (microparticles) loaded with the immunosuppressive agent Azathioprine, to locally treat IBDs.
DOI: 10.17632/fhrht9g289.1
title: Azathioprine-loaded Beads

description: Scanning Electron Microscopy Images for the colon-targeted beads (microparticles) loaded with the immunosuppressive agent Azathioprine, to locally treat IBDs.
DOI: 10.15468/dl.vpfzez
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinella pyrrhomelas",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033925-251025141854904/datasets/export for details.
DOI: 10.5281/zenodo.17572585
title: "A High-Resolution Coupled Physical-Biogeochemical Model of the Northeastern US Continental Shelf: MOM6-COBALT-NEUS25v1.0" - auxiliary datasets

description: This dataset contains:1. Model configuration files (grid and grid related files, and forcing datasets that are relatively small)2. Processed model output used to generate all manuscript figuresDue to size constraints, some model input files must be generated by users:- Atmospheric forcing fields - Lateral boundary conditions- River files- Sponge and nudging files----------------------------------------------------------

Scripts to download and preprocess these datasets are available at:https://github.com/dksasaki/mom6_neus25_utils (v1.0.0, commit 391115e)

Configurations of MOM6-COBALT-NEUS25 are available at:https://https://github.com/dksasaki/MOM6_COBALT_NEUS25 (v1.0.0, commit 5da354b)  

MOM6-COBALT from NOAA-GFDL CEFI-regional-MOM6 framework(commit 214d998, https://github.com/NOAA-GFDL/CEFI-regional-MOM6)after checking out the specific commit, use `git submodule update --recursive`----------------------------------------------------------See README.md for detailed instructions.
DOI: 10.5281/zenodo.17572586
title: "A High-Resolution Coupled Physical-Biogeochemical Model of the Northeastern US Continental Shelf: MOM6-COBALT-NEUS25v1.0" - auxiliary datasets

description: This dataset contains:1. Model configuration files (grid and grid related files, and forcing datasets that are relatively small)2. Processed model output used to generate all manuscript figuresDue to size constraints, some model input files must be generated by users:- Atmospheric forcing fields - Lateral boundary conditions- River files- Sponge and nudging files----------------------------------------------------------

Scripts to download and preprocess these datasets are available at:https://github.com/dksasaki/mom6_neus25_utils (v1.0.0, commit 391115e)

Configurations of MOM6-COBALT-NEUS25 are available at:https://https://github.com/dksasaki/MOM6_COBALT_NEUS25 (v1.0.0, commit 5da354b)  

MOM6-COBALT from NOAA-GFDL CEFI-regional-MOM6 framework(commit 214d998, https://github.com/NOAA-GFDL/CEFI-regional-MOM6)after checking out the specific commit, use `git submodule update --recursive`----------------------------------------------------------See README.md for detailed instructions.
DOI: 10.5281/zenodo.17612644
title: Hotel Booking Reservation

description: This dataset contains detailed information about hotel bookings, including reservation dates, customer demographics, stay duration, deposit types, cancellation status, and other booking-related attributes. It is an updated and cleaned version of the original UCI “Hotel Booking Demand” dataset, prepared for machine learning and data analytics tasks.

The dataset is suitable for classification, regression, and clustering projects such as:

Predicting booking cancellations

Forecasting demand and occupancy

Understanding guest behavior and stay patterns

Analyzing customer segmentation

Data Summary

Instances: 119,390

Attributes: 33

Features (Inputs): 32

Target Variable: is_canceled

Missing Values: Yes (some in children, agent, company)

File Type: CSV (21.28 MB)

Use Cases

Machine learning classification (predicting cancellations)

Regression (predicting ADR or lead time)

Clustering (customer segmentation)

Time-series analysis (seasonal trends)

Business intelligence dashboards
DOI: 10.5281/zenodo.17612645
title: Hotel Booking Reservation

description: This dataset contains detailed information about hotel bookings, including reservation dates, customer demographics, stay duration, deposit types, cancellation status, and other booking-related attributes. It is an updated and cleaned version of the original UCI “Hotel Booking Demand” dataset, prepared for machine learning and data analytics tasks.

The dataset is suitable for classification, regression, and clustering projects such as:

Predicting booking cancellations

Forecasting demand and occupancy

Understanding guest behavior and stay patterns

Analyzing customer segmentation

Data Summary

Instances: 119,390

Attributes: 33

Features (Inputs): 32

Target Variable: is_canceled

Missing Values: Yes (some in children, agent, company)

File Type: CSV (21.28 MB)

Use Cases

Machine learning classification (predicting cancellations)

Regression (predicting ADR or lead time)

Clustering (customer segmentation)

Time-series analysis (seasonal trends)

Business intelligence dashboards
DOI: 10.5281/zenodo.17611829
title: Forest Aboveground Biomass 2000-2024 for Maryland, USA

description: This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 2000-2024. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance (Hurtt et al., 2024). This dataset reports AGB in unit of kg C/m2.

This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.

This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the Global Forest Change (Hansen et al 2013), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2024.

This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.

For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.

This work was supported by contract from the Maryland Department of the Environment. We also gratefully acknowledge the support of NASA Carbon Monitoring System project (80NSSC21K1059).
DOI: 10.5281/zenodo.17611830
title: Forest Aboveground Biomass 2000-2024 for Maryland, USA

description: This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 2000-2024. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance (Hurtt et al., 2024). This dataset reports AGB in unit of kg C/m2.

This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.

This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the Global Forest Change (Hansen et al 2013), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2024.

This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.

For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.

This work was supported by contract from the Maryland Department of the Environment. We also gratefully acknowledge the support of NASA Carbon Monitoring System project (80NSSC21K1059).
DOI: 10.15468/dl.9z8psd
title: Occurrence Download

description: A dataset containing 588 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 {
 "or" : [
 "Year is 2017",
 "Year is 2018",
 "Year is 2019",
 "Year is 2020",
 "Year is 2021",
 "Year is 2022",
 "Year is 2023",
 "Year is 2024",
 "Year is 2016",
 "Year is 2015"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Material sample, Machine Observation)",
 "StateProvince is one of (Cundinamarca, Boyacá)",
 "TaxonKey is one of (Elmidae [GBIF Backbone Taxonomy])"
 ]
 }
 ]
}

 The dataset includes 588 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033926-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uq458b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinella spiloptera",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033927-251025141854904/datasets/export for details.
DOI: 10.15468/dl.3ewue2
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phanaeus zapotecus"
 ]
}

 The dataset includes 20 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033928-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17612126
title: Circular Design Tools Database

description: This database contains a structured classification of 77 circular design tools identified through a systematic literature review on circular economy integration in the New Product Development (NPD) process. Each tool has been analysed and categorised according to multiple dimensions, including: authors, year of publication, language availability, accessibility, aim, innovation focus, relevant NPD phase, target industry sector, associated circular strategies, format, format description, and data type. The dataset also includes direct access links and concise descriptions for each tool.It was developed as part of an industrial PhD project focused on supporting companies in the adoption of circular design practices from early-stage NPD.This database offers researchers, designers, and practitioners a comprehensive overview of existing tools and methods, helping them navigate the current landscape of circular design resources and identify suitable approaches for different project needs.
DOI: 10.5281/zenodo.17612127
title: Circular Design Tools Database

description: This database contains a structured classification of 77 circular design tools identified through a systematic literature review on circular economy integration in the New Product Development (NPD) process. Each tool has been analysed and categorised according to multiple dimensions, including: authors, year of publication, language availability, accessibility, aim, innovation focus, relevant NPD phase, target industry sector, associated circular strategies, format, format description, and data type. The dataset also includes direct access links and concise descriptions for each tool.It was developed as part of an industrial PhD project focused on supporting companies in the adoption of circular design practices from early-stage NPD.This database offers researchers, designers, and practitioners a comprehensive overview of existing tools and methods, helping them navigate the current landscape of circular design resources and identify suitable approaches for different project needs.
DOI: 10.15468/dl.fq2tvx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinella venusta",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033929-251025141854904/datasets/export for details.
DOI: 10.15468/dl.wj4ymv
title: Occurrence Download

description: A dataset containing 374 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lagrezia monosperma"
 ]
}

 The dataset includes 374 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033930-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.52w4nt
title: Occurrence Download

description: A dataset containing 85302 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "TaxonKey is Araceae"
 ]
}

 The dataset includes 85302 records from 288 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033899-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6y59hd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinella whipplei",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033931-251025141854904/datasets/export for details.
DOI: 10.15468/dl.6kb7pu
title: Occurrence Download

description: A dataset containing 3388 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carollia sowelli"
 ]
}

 The dataset includes 3388 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033932-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e4mmm8
title: Occurrence Download

description: A dataset containing 11046 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Oregon Bee Atlas Survey Data: 2018"
 ]
}

 The dataset includes 11046 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033933-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.avssan
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "DatasetKey is Colección Entomológica Universidad de Antioquia",
 "GadmGid is COL.2_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Pompilidae"
 ]
}

 The dataset includes 57 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033934-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.pncbnr
title: Dataset generated from Esri tool

description: Derived dataset generated by Esri geoprocessing tool using GBIF API
DOI: 10.5281/zenodo.17576585
title: Transportation and Accident Records Dataset

description: This dataset contains structured transportation and road accident records designed forresearch, machine learning model development, and academic analysis. The data includesinformation on accident severity, date and time, location, vehicle details, driver conditions,weather parameters, and road characteristics.

The dataset was created to support projects involving accident prediction, transportation safety analysis, and smart transport alert systems. It is suitable for machine learning classification tasks (such as severity prediction), geospatial mapping, and trend analysis.

The dataset is synthetic but follows realistic patterns based on transportation conditions and accident statistics. It is fully cleaned, validated, and formatted for direct use in data science workflows.

This dataset accompanies the “Smart Transport Accident Prediction & Alert System” project using a Random Forest model.
DOI: 10.5281/zenodo.17576586
title: Transportation and Accident Records Dataset

description: This dataset contains structured transportation and road accident records designed forresearch, machine learning model development, and academic analysis. The data includesinformation on accident severity, date and time, location, vehicle details, driver conditions,weather parameters, and road characteristics.

The dataset was created to support projects involving accident prediction, transportation safety analysis, and smart transport alert systems. It is suitable for machine learning classification tasks (such as severity prediction), geospatial mapping, and trend analysis.

The dataset is synthetic but follows realistic patterns based on transportation conditions and accident statistics. It is fully cleaned, validated, and formatted for direct use in data science workflows.

This dataset accompanies the “Smart Transport Accident Prediction & Alert System” project using a Random Forest model.
DOI: 10.5517/ccdc.csd.cc2p30nh
title: CCDC 2475556: Experimental Crystal Structure Determination

description: Related Article: Daniel Werner, Zhifang Guo, Victoria L. Blair, Glen B. Deacon, Peter C. Junk|2025|New J.Chem.|49|18725|doi:10.1039/d5nj03383g
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.