cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/st4tynxwb7
title: Sand Dam Suitability Assessment Using Integrated Geospatial and Multi-Criteria Decision Analysis to Strengthen Water Security in Arid and Semi-Arid Regions: A Case of the Lower Awash Basin, Ethiopia

description: Water security is a crucial issue in arid and semi-arid regions like the Lower Awash Basin, Ethiopia, where increasing population and economic development put pressure on limited water resources. This study evaluates the suitability of sand dam sites using a multi-criteria evaluation approach combined with geospatial techniques. Meteorological data were carefully tested for consistency and homogeneity through double mass curves, Pettitt’s test, and Mann-Kendall analysis. Key biophysical factors such as slope, stream order, soil type, land use/land cover (LULC), runoff depth, and proximity to roads were reclassified and weighted according to their importance for sand dam feasibility. Runoff depths ranged from 682-934 mm, with 69% of the basin receiving 820-930 mm, indicating abundant water availability. Slope analysis showed that 47.4% of the land has gentle gradients (0–5.23°), suitable for dam stability. However, limited feasibility was observed due to stream networks, with only 4.78% of the basin being moderately or highly suitable. Soil assessment identified Fluvisols (21.91%) and Regosols (2.5%) as ideal, whereas Leptosols (43.06%) were unsuitable. LULC mapping revealed that rangelands dominate (71.6%) and provide moderate suitability, while water bodies and flooded vegetation (~2.3%) are highly favorable. Areas more than 4,000 meters from roads (79.6%) were considered optimal to reduce flooding risks near infrastructure. Overall, the integrated analysis found only 1.2% (36,855 ha) of the basin as highly suitable and 10.96% as moderately suitable for sand dam construction, while 47.74% was unsuitable. Results show limited ideal sites and stress the need for localized assessments to ensure sustainable sand dam development.
DOI: 10.17632/st4tynxwb7.1
title: Sand Dam Suitability Assessment Using Integrated Geospatial and Multi-Criteria Decision Analysis to Strengthen Water Security in Arid and Semi-Arid Regions: A Case of the Lower Awash Basin, Ethiopia

description: Water security is a crucial issue in arid and semi-arid regions like the Lower Awash Basin, Ethiopia, where increasing population and economic development put pressure on limited water resources. This study evaluates the suitability of sand dam sites using a multi-criteria evaluation approach combined with geospatial techniques. Meteorological data were carefully tested for consistency and homogeneity through double mass curves, Pettitt’s test, and Mann-Kendall analysis. Key biophysical factors such as slope, stream order, soil type, land use/land cover (LULC), runoff depth, and proximity to roads were reclassified and weighted according to their importance for sand dam feasibility. Runoff depths ranged from 682-934 mm, with 69% of the basin receiving 820-930 mm, indicating abundant water availability. Slope analysis showed that 47.4% of the land has gentle gradients (0–5.23°), suitable for dam stability. However, limited feasibility was observed due to stream networks, with only 4.78% of the basin being moderately or highly suitable. Soil assessment identified Fluvisols (21.91%) and Regosols (2.5%) as ideal, whereas Leptosols (43.06%) were unsuitable. LULC mapping revealed that rangelands dominate (71.6%) and provide moderate suitability, while water bodies and flooded vegetation (~2.3%) are highly favorable. Areas more than 4,000 meters from roads (79.6%) were considered optimal to reduce flooding risks near infrastructure. Overall, the integrated analysis found only 1.2% (36,855 ha) of the basin as highly suitable and 10.96% as moderately suitable for sand dam construction, while 47.74% was unsuitable. Results show limited ideal sites and stress the need for localized assessments to ensure sustainable sand dam development.
DOI: 10.15468/dl.8p5v2w
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Saperda candida",
 "OccurrenceStatus is Absent"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026629-250811113504898/datasets/export for details.
DOI: 10.15468/dl.tfkstc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus",
 "Country is Dominican Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026628-250811113504898/datasets/export for details.
DOI: 10.17632/cr3jbtgddk
title: National Dairy Nutritionist Survey on Byproduct Feed Usage in the United States in 2024

description: This dataset compiles the results of a survey sent to US dairy cow nutritionists inquiring about the types and amounts of byproducts incorporated into dairy cattle diets during 2024, the number of lactating cows, dry cows and heifers serviced, the amount of milk produced by these lactating cows, and the states where these animals were located. The dataset provides quantitative estimates of each byproduct feed included in dairy cattle diets nationally and within four regions (Midwest, Northeast, South, and West) of the United States. This dataset represents a second independent assessment of byproduct feeds used in dairy cattle diets similar to that reported previously for 2019 (Ondarza and Tricarico, 2021; doi.org/10.1016/j.dib.2021.107358). This dataset is useful for scientists in the public and private sectors seeking to understand the type and quantity of byproduct feed usage by dairy farms in the United States.
DOI: 10.17632/cr3jbtgddk.1
title: National Dairy Nutritionist Survey on Byproduct Feed Usage in the United States in 2024

description: This dataset compiles the results of a survey sent to US dairy cow nutritionists inquiring about the types and amounts of byproducts incorporated into dairy cattle diets during 2024, the number of lactating cows, dry cows and heifers serviced, the amount of milk produced by these lactating cows, and the states where these animals were located. The dataset provides quantitative estimates of each byproduct feed included in dairy cattle diets nationally and within four regions (Midwest, Northeast, South, and West) of the United States. This dataset represents a second independent assessment of byproduct feeds used in dairy cattle diets similar to that reported previously for 2019 (Ondarza and Tricarico, 2021; doi.org/10.1016/j.dib.2021.107358). This dataset is useful for scientists in the public and private sectors seeking to understand the type and quantity of byproduct feed usage by dairy farms in the United States.
DOI: 10.15468/dl.gumv9h
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Serrasalmus nalseni)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026630-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/sg4dmc7pff
title: Research data for “Stomatal Conductance Modeling from the Perspective of a Land Surface Model”

description: This dataset contains simulated results of the Variable Infiltration Capacity Plus (VIC+) land surface model in the research “Stomatal Conductance Modeling from the Perspective of a Land Surface Model”. It consists of simulated results of six stomatal conductance schemes at the Blodgett site and the Duke site, respectively. The observed data used in this research are also included.
DOI: 10.17632/sg4dmc7pff.1
title: Research data for “Stomatal Conductance Modeling from the Perspective of a Land Surface Model”

description: This dataset contains simulated results of the Variable Infiltration Capacity Plus (VIC+) land surface model in the research “Stomatal Conductance Modeling from the Perspective of a Land Surface Model”. It consists of simulated results of six stomatal conductance schemes at the Blodgett site and the Duke site, respectively. The observed data used in this research are also included.
DOI: 10.17632/6kdsysrc89
title: Survey Data on Consumer Purchase Intention in Shopee's Short Video Feature

description: The uploaded dataset contains 311 total survey responses. However, consistent with the associated research publication, only 300 valid responses were used for analysis. The remaining entries were excluded due to incomplete answers or failure to meet inclusion criteria during data cleaning and preprocessing.
This dataset contains anonymized responses from Shopee users in Indonesia who have used the platform’s short video feature. Respondent email addresses have been anonymized, and phone number information has been removed to ensure confidentiality.
The survey was conducted between March 16, 2025, and July 24, 2025, and assessed consumer perceptions and behavioral intentions regarding Shopee’s short video feature.
It includes variables related to:
- Demographics
- System Quality (SQ)
- Content Quality (CQ)
- Technology Adoption & Usefulness (TAU)
- User Engagement (UE)
- Purchase Intention (PI)
This dataset supports the research article titled: “Key Drivers of Consumer Purchase Intention in Shopee's Short Video Feature.”
Refer to the included README file for full variable descriptions.
DOI: 10.17632/6kdsysrc89.1
title: Survey Data on Consumer Purchase Intention in Shopee's Short Video Feature

description: The uploaded dataset contains 311 total survey responses. However, consistent with the associated research publication, only 300 valid responses were used for analysis. The remaining entries were excluded due to incomplete answers or failure to meet inclusion criteria during data cleaning and preprocessing.
This dataset contains anonymized responses from Shopee users in Indonesia who have used the platform’s short video feature. Respondent email addresses have been anonymized, and phone number information has been removed to ensure confidentiality.
The survey was conducted between March 16, 2025, and July 24, 2025, and assessed consumer perceptions and behavioral intentions regarding Shopee’s short video feature.
It includes variables related to:
- Demographics
- System Quality (SQ)
- Content Quality (CQ)
- Technology Adoption & Usefulness (TAU)
- User Engagement (UE)
- Purchase Intention (PI)
This dataset supports the research article titled: “Key Drivers of Consumer Purchase Intention in Shopee's Short Video Feature.”
Refer to the included README file for full variable descriptions.
DOI: 10.17632/47wxjbtf97
title: Advantages of foredune soft protection: the case of Pehuén Co Beach, Argentina

description: This dataset aims to demonstrate that the use of Big Bags is effective in mitigating erosion caused by low-height waves, which for many coastal areas can represent a practical and cost-effective means of containing recurrent wave conditions. For the study area analyzed in this paper, given that the most frequent wave heights are low (&gt; 86%), they function as a mitigation method during calm states and regular tides. For this reason, the results of their implementation were beneficial for the study area by maintaining the dune toe line in a stable position during the study period, mitigating the rapid and significant retreat of previous years. However, during storm events and extraordinary water level rises, where the water column exceeds one meter in height at the dune toe, the bags are overtopped, and the upper parts of the foredune are exposed to erosion.
DOI: 10.17632/47wxjbtf97.1
title: Advantages of foredune soft protection: the case of Pehuén Co Beach, Argentina

description: This dataset aims to demonstrate that the use of Big Bags is effective in mitigating erosion caused by low-height waves, which for many coastal areas can represent a practical and cost-effective means of containing recurrent wave conditions. For the study area analyzed in this paper, given that the most frequent wave heights are low (&gt; 86%), they function as a mitigation method during calm states and regular tides. For this reason, the results of their implementation were beneficial for the study area by maintaining the dune toe line in a stable position during the study period, mitigating the rapid and significant retreat of previous years. However, during storm events and extraordinary water level rises, where the water column exceeds one meter in height at the dune toe, the bags are overtopped, and the upper parts of the foredune are exposed to erosion.
DOI: 10.17632/5hy8fnsnnt.2
title: Experimental Data for UHMWPE Fiber Laminates Subjected to Shaped Charge UNDEX Loading

description: This section presents the experimental data on the response of ultra-high-molecular-weight polyethylene (UHMWPE) fiber laminates subjected to underwater explosion (UNDEX) loading from a shaped charge. The data primarily encompass three types of loads: the shock wave, metal jet, and bubble pulsation. The aim is to provide valuable reference data for researchers studying fluid-structure-interaction (FSI) between shaped charge UNDEX events and UHMWPE laminates.
DOI: 10.17632/rmb9rkkj2d.3
title: Supplemental Material for Vrcan et al., Genome-wide analyses to identify genomic regions associated with udder morphology traits in dairy sheep

description: Supplementary Tables associated to research paper Vrcan et al., Genome-wide analyses to unravel genetic mechanisms governing udder morphology traits in dairy sheep.
DOI: 10.17632/grkv36gg2t
title: Fault Pattern Dataset for a 33 kV Power Distribution Network

description: This dataset contains historical fault records collected from a 33 kV power distribution network situated within the 104101–104291 zip code region of Lagos State, in the southwest of Nigeria (representing an area characterized by rapid residential and industrial growth) over a 7.58-year period (April 2017 to December 2024). It consists of 23 medium-voltage (33 kV) feeders. Of the 23 feeders, seven supply power to the primary 33 kV/11 kV injection substations that serve as the main distribution nodes, while the remaining sixteen are dedicated to supplying 33 kV/415 V distribution transformers for localized load centers. The data was compiled as part of a study on fault pattern analysis and predictive maintenance using association rule mining. The dataset includes 5,955 fault transaction entries and 7,058 fault occurrences, with detailed attributes such as:

Fault type and cause
Load loss (in MW)
Time of fault occurrence and restoration
Mean Time to Restore (MTTR)
Seasonal classification (dry/rainy)

Derived features include categorized MTTR levels (optimal, acceptable, suboptimal), load loss severity (minimum, moderate, high), and seasonal variations. The dataset supports research in predictive maintenance, reliability analysis, and data-driven fault diagnostics in power distribution systems.

This dataset was used in the paper titled "Fault Pattern Analysis for Enhancing Predictive Maintenance in Power Distribution Systems using Apriori Association Rule Mining" (submitted to Electric Power Systems Research).
DOI: 10.17632/grkv36gg2t.2
title: Fault Pattern Dataset for a 33 kV Power Distribution Network

description: This dataset contains historical fault records collected from a 33 kV power distribution network situated within the 104101–104291 zip code region of Lagos State, in the southwest of Nigeria (representing an area characterized by rapid residential and industrial growth) over a 7.58-year period (April 2017 to December 2024). It consists of 23 medium-voltage (33 kV) feeders. Of the 23 feeders, seven supply power to the primary 33 kV/11 kV injection substations that serve as the main distribution nodes, while the remaining sixteen are dedicated to supplying 33 kV/415 V distribution transformers for localized load centers. The data was compiled as part of a study on fault pattern analysis and predictive maintenance using association rule mining. The dataset includes 5,955 fault transaction entries and 7,058 fault occurrences, with detailed attributes such as:

Fault type and cause
Load loss (in MW)
Time of fault occurrence and restoration
Mean Time to Restore (MTTR)
Seasonal classification (dry/rainy)

Derived features include categorized MTTR levels (optimal, acceptable, suboptimal), load loss severity (minimum, moderate, high), and seasonal variations. The dataset supports research in predictive maintenance, reliability analysis, and data-driven fault diagnostics in power distribution systems.

This dataset was used in the paper titled "Fault Pattern Analysis for Enhancing Predictive Maintenance in Power Distribution Systems using Apriori Association Rule Mining" (submitted to Electric Power Systems Research).
DOI: 10.15468/dl.ceu4ge
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus",
 "Country is Ecuador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026631-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/446vz2thw3
title: Chapas metalicas - Defeitos na Pintura

description: Dataset de peças metálicas com defeitos e sem defeitos na pintura.
DOI: 10.17632/446vz2thw3.1
title: Chapas metalicas - Defeitos na Pintura

description: Dataset de peças metálicas com defeitos e sem defeitos na pintura.
DOI: 10.17632/5yjbsnm8fg
title: Estampas de Fundo de Roupeiro

description: O Dataset é composto por 208 imagens de estampas de fundo de roupeiro fabricados em aço. Dessas imagens 101 são dentro do padrão de conformidade exigido pelo projeto da peça e 107 imagens são fora do padrão.
DOI: 10.17632/5yjbsnm8fg.1
title: Estampas de Fundo de Roupeiro

description: O Dataset é composto por 208 imagens de estampas de fundo de roupeiro fabricados em aço. Dessas imagens 101 são dentro do padrão de conformidade exigido pelo projeto da peça e 107 imagens são fora do padrão.
DOI: 10.17632/zjyx33c33x
title: A Graph-Theoretic Framework for Quantitative Analysis of Angiogenic Networks

description: This dataset includes some tube formation assay images and a Python-based analysis pipeline for evaluating tube formation microscopy images through graph-theoretic methods. The images are endothelial cell tube formation under different conditions and can been processed into skeletonized forms for graph extraction using the provided script. The accompanying Python script calculates 11 key graph metrics such as node degree, clustering coefficient, global efficiency, tortuosity, network density, connectivity index and radial zone distributions to assess angiogenic network morphology. Other metrics are also included for extra information purposes.

The provided code relies on the following Python packages:

networkx (for graph analysis)

scipy (for spatial and statistical computations)

skimage (for image processing and skeletonization)

matplotlib (for data visualization)

pandas (for data handling and results export)

This dataset allows users to reproduce the analysis pipeline described in our manuscript, visualize the network structure, and quantify the topological features of angiogenic networks. The script is ready to be used with microscopy images of endothelial cell tube formation assays to extract and analyze angiogenic growth patterns.
DOI: 10.17632/zjyx33c33x.1
title: A Graph-Theoretic Framework for Quantitative Analysis of Angiogenic Networks

description: This dataset includes some tube formation assay images and a Python-based analysis pipeline for evaluating tube formation microscopy images through graph-theoretic methods. The images are endothelial cell tube formation under different conditions and can been processed into skeletonized forms for graph extraction using the provided script. The accompanying Python script calculates 11 key graph metrics such as node degree, clustering coefficient, global efficiency, tortuosity, network density, connectivity index and radial zone distributions to assess angiogenic network morphology. Other metrics are also included for extra information purposes.

The provided code relies on the following Python packages:

networkx (for graph analysis)

scipy (for spatial and statistical computations)

skimage (for image processing and skeletonization)

matplotlib (for data visualization)

pandas (for data handling and results export)

This dataset allows users to reproduce the analysis pipeline described in our manuscript, visualize the network structure, and quantify the topological features of angiogenic networks. The script is ready to be used with microscopy images of endothelial cell tube formation assays to extract and analyze angiogenic growth patterns.
DOI: 10.15468/dl.67985k
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus",
 "Country is Egypt",
 "HasCoordinate is true"
 ]
}

 The dataset includes 29 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026633-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6s94mxdt5t.1
title: Analysis of Factors Affecting Continuance Intention in Indonesian Digital Banks

description: This research was guided by several hypotheses examining the relationships between system quality, service quality, information quality, perceived advantage, effort expectancy, and digital ecosystem on user satisfaction and continuance intention in digital banking applications. Specifically, the hypotheses tested whether:

System quality, service quality, and information quality positively influence user satisfaction.

Perceived advantage, effort expectancy, and digital ecosystem positively affect user satisfaction.

User satisfaction positively influences continuance intention to use digital banking applications.

System quality, service quality, and information quality may also have a direct effect on continuance intention.

The dataset was collected via a structured questionnaire using Google Forms, distributed through colleagues, academic peers, and social media networks. Responses were analyzed using SmartPLS v.4 with Partial Least Squares Structural Equation Modeling (PLS-SEM)
DOI: 10.15468/dl.pd9vx6
title: Occurrence Download

description: A dataset containing 2631 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Scolopendra morsitans",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2631 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026632-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.