cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8fwwjpm79y.13
title: ShinyFMBN, a Shiny app to access FoodMicrobionet

description: This data set contains the ShinyFMBN app and the FoodMicrobionet database v5.1.2
The ShinyFMBN app allows you to access FoodMicrobionet 5.1.2, a repository of data on food microbiome studies including data for both bacteria and fungi which can be used to retrieve and analyze data on the fungal and bacterial microbiota of a large variety of foods. To run the app you need to install R and R Studio. Data are available in R (.rds) format. The FoodMicrobionet database and related scripts are available on GitHub (https://github.com/ep142/FoodMicrobionet)

This compressed folder contains folder shiny_FMBN_4_light: this includes the app folder, the runShinyFMBN_4.R script (a R script to install all needed packages and run the app) and the app manual in .html and .md format
Note that an online version of the app is also available at https://ep142.shinyapps.io/ShinyFMBN_4_light/

This version includes a few fixes: an inconsistency with study 308 was fixed and the text in the about and welcome panes was made more self explainatory. A .md version of the manual was added.
DOI: 10.17632/ft7tvdr7z8
title: Air velocity and tracer gas concentration datasets of a naturally ventilated pig barn measured in a large atmospheric boundary layer wind tunnel

description: The experimental datasets present high resolution measurements of airflow and tracer gas concentration downwind a 1:50 scaled model of a naturally ventilated pig barn with an outdoor exercise yard. The measurements were conducted in a large atmospheric boundary wind tunnel in Germany, which simulated a moderately rough atmospheric boundary layer flow, representing a grassland or farmland terrain. Boundary layer wind profile as well as air velocity and tracer gas concentration in six measurement campaigns with different opening sizes and roof structures of the pig barn were measured in the wind tunnel. Both air velocity and gas concentration were conducted at four vertical planes including 490 measurement points in each measurement campaign. All instantaneous air velocities were measured using a two-dimensional Laser Doppler Anemometer system at a sampling number of 40,000 at each measurement point. The concentration of the tracer gas ethane was measured using a Fast Response Flame Ionisation Detector at a sampling number of 30,000. Time-averaged and instantaneous fluctuations of air velocity as well as the time-averaged gas concentration data are included in the dataset. The experimental dataset can be used for researchers and engineers for validation and refinement of computational fluid dynamics models, especially for comparing time-series turbulence statistics and transient structures. The dataset can also be used in architectural and engineering applications to evaluate and mitigate the environmental impact of the livestock buildings.
DOI: 10.17632/ft7tvdr7z8.1
title: Air velocity and tracer gas concentration datasets of a naturally ventilated pig barn measured in a large atmospheric boundary layer wind tunnel

description: The experimental datasets present high resolution measurements of airflow and tracer gas concentration downwind a 1:50 scaled model of a naturally ventilated pig barn with an outdoor exercise yard. The measurements were conducted in a large atmospheric boundary wind tunnel in Germany, which simulated a moderately rough atmospheric boundary layer flow, representing a grassland or farmland terrain. Boundary layer wind profile as well as air velocity and tracer gas concentration in six measurement campaigns with different opening sizes and roof structures of the pig barn were measured in the wind tunnel. Both air velocity and gas concentration were conducted at four vertical planes including 490 measurement points in each measurement campaign. All instantaneous air velocities were measured using a two-dimensional Laser Doppler Anemometer system at a sampling number of 40,000 at each measurement point. The concentration of the tracer gas ethane was measured using a Fast Response Flame Ionisation Detector at a sampling number of 30,000. Time-averaged and instantaneous fluctuations of air velocity as well as the time-averaged gas concentration data are included in the dataset. The experimental dataset can be used for researchers and engineers for validation and refinement of computational fluid dynamics models, especially for comparing time-series turbulence statistics and transient structures. The dataset can also be used in architectural and engineering applications to evaluate and mitigate the environmental impact of the livestock buildings.
DOI: 10.17632/p3f7bc28cm
title: Comparison of toe clearance characteristics between simulated obstacle crossing using visual height cues and actual obstacle crossing

description: Research Hypothesis
The study initially hypothesized that a simplified simulated obstacle-crossing environment, utilizing floor-based visual height cues, would demonstrate high biomechanical fidelity by evoking gait patterns and obstacle-negotiation strategies similar to those observed in actual environments.

Data Gathering and Methodology
Trial-by-trial kinematic data were collected from healthy participants performing obstacle-crossing tasks.
Experiment 1 investigated the influence of target heights (3–12 cm) and walking paths (straight vs. curved) on gait patterns.
Experiment 2 compared performance between actual obstacle negotiation and a risk-free simulated environment using four height levels relative to the participant's leg length.The primary outcome measures include Minimum Toe Clearance (TCmin), Maximum Toe Clearance (TCmax), Approach Distance (AD), and Quasicoefficient of Variation (QCV).

Key Findings and Data Representation
Contrary to the initial hypothesis, the dataset reveals a significant dissociation between motor intention and execution precision. While participants successfully scaled their maximum limb elevation (TCmax) in response to obstacle height in the simulated environment, they systematically underestimated their TCmin, leading to reduced safety margins. Additionally, the data show increased motor variability (QCV) in the trail limb during simulated crossing compared to actual crossing.

Interpretation and Data Use
These results suggest that while simulation can evoke overall motor intention (gross scaling), the absence of physical risk and task-relevant sensory feedback leads the central nervous system to prioritize effort economy over the precise, fine-tuning of foot trajectories. This dataset is valuable for researchers investigating perception–action coupling and for those developing evidence-based virtual training protocols for fall prevention.
DOI: 10.17632/p3f7bc28cm.1
title: Comparison of toe clearance characteristics between simulated obstacle crossing using visual height cues and actual obstacle crossing

description: Research Hypothesis
The study initially hypothesized that a simplified simulated obstacle-crossing environment, utilizing floor-based visual height cues, would demonstrate high biomechanical fidelity by evoking gait patterns and obstacle-negotiation strategies similar to those observed in actual environments.

Data Gathering and Methodology
Trial-by-trial kinematic data were collected from healthy participants performing obstacle-crossing tasks.
Experiment 1 investigated the influence of target heights (3–12 cm) and walking paths (straight vs. curved) on gait patterns.
Experiment 2 compared performance between actual obstacle negotiation and a risk-free simulated environment using four height levels relative to the participant's leg length.The primary outcome measures include Minimum Toe Clearance (TCmin), Maximum Toe Clearance (TCmax), Approach Distance (AD), and Quasicoefficient of Variation (QCV).

Key Findings and Data Representation
Contrary to the initial hypothesis, the dataset reveals a significant dissociation between motor intention and execution precision. While participants successfully scaled their maximum limb elevation (TCmax) in response to obstacle height in the simulated environment, they systematically underestimated their TCmin, leading to reduced safety margins. Additionally, the data show increased motor variability (QCV) in the trail limb during simulated crossing compared to actual crossing.

Interpretation and Data Use
These results suggest that while simulation can evoke overall motor intention (gross scaling), the absence of physical risk and task-relevant sensory feedback leads the central nervous system to prioritize effort economy over the precise, fine-tuning of foot trajectories. This dataset is valuable for researchers investigating perception–action coupling and for those developing evidence-based virtual training protocols for fall prevention.
DOI: 10.17632/wbs8bj73tm
title: Algorithmic-Theology-raw-data

description: Title: Algorithmic Theology: Raw Data from the Article on the Competence of Artificial Intelligence Models in Teaching the Articles of Faith

1. Description / Overview This dataset contains the raw text outputs generated by three prominent Large Language Models (ChatGPT, Claude, and Gemini) in response to structured prompts concerning Islamic articles of faith. The data was compiled to evaluate the pedagogical, theological, and epistemological competence of artificial intelligence tools within the context of Islamic religious education. This dataset serves as the foundational data for the article titled "Algorithmic Theology: The Competence of Artificial Intelligence Models in Teaching the Fundamentals of Islamic Faith".

2. Data Collection Methodology During the data collection phase, the AI models were explicitly instructed to tailor their responses to a 9th-grade student level, strictly within the framework of the current Religious Culture and Moral Knowledge (DKAB) curriculum in Türkiye. Specific questions regarding the articles of faith were selected from the official curriculum and individually posed to each AI model. The generated outputs were recorded without any alteration to preserve the epistemic and theological integrity of the models' original responses.

3. Dataset Contents The dataset typically includes the following fields (columns):

Prompt/Question: The specific theological question derived from the 9th-grade DKAB curriculum.

AI Model: The specific tool used to generate the response (ChatGPT, Claude, or Gemini).

Raw Output: The exact, unedited text generated by the AI model.

 Evaluation Category: Variables indicating the pedagogical richness, theological consistency, and epistemological accuracy of the response as coded by the researchers.

4. Value of the Data / Potential Use Cases This dataset provides empirical material for researchers studying the intersection of theology, education, and artificial intelligence. It can be utilized to analyze AI bias in religious contexts, compare the alignment of different LLMs with specific religious curricula, and explore the ethical dimensions of using AI as an epistemic authority in religious education.
DOI: 10.17632/wbs8bj73tm.1
title: Algorithmic-Theology-raw-data

description: Title: Algorithmic Theology: Raw Data from the Article on the Competence of Artificial Intelligence Models in Teaching the Articles of Faith

1. Description / Overview This dataset contains the raw text outputs generated by three prominent Large Language Models (ChatGPT, Claude, and Gemini) in response to structured prompts concerning Islamic articles of faith. The data was compiled to evaluate the pedagogical, theological, and epistemological competence of artificial intelligence tools within the context of Islamic religious education. This dataset serves as the foundational data for the article titled "Algorithmic Theology: The Competence of Artificial Intelligence Models in Teaching the Fundamentals of Islamic Faith".

2. Data Collection Methodology During the data collection phase, the AI models were explicitly instructed to tailor their responses to a 9th-grade student level, strictly within the framework of the current Religious Culture and Moral Knowledge (DKAB) curriculum in Türkiye. Specific questions regarding the articles of faith were selected from the official curriculum and individually posed to each AI model. The generated outputs were recorded without any alteration to preserve the epistemic and theological integrity of the models' original responses.

3. Dataset Contents The dataset typically includes the following fields (columns):

Prompt/Question: The specific theological question derived from the 9th-grade DKAB curriculum.

AI Model: The specific tool used to generate the response (ChatGPT, Claude, or Gemini).

Raw Output: The exact, unedited text generated by the AI model.

 Evaluation Category: Variables indicating the pedagogical richness, theological consistency, and epistemological accuracy of the response as coded by the researchers.

4. Value of the Data / Potential Use Cases This dataset provides empirical material for researchers studying the intersection of theology, education, and artificial intelligence. It can be utilized to analyze AI bias in religious contexts, compare the alignment of different LLMs with specific religious curricula, and explore the ethical dimensions of using AI as an epistemic authority in religious education.
DOI: 10.17632/wd55vcryt9
title: Reproducibility package (code + published tables only; no redistributed cohort data) for: Temperature variability and mortality among older adults in China: effect modification by functional status in two national cohorts

description: This dataset contains a reproducibility package (analysis code and published summary result tables) for the study:

"Temperature variability and mortality among older adults in China: effect modification by functional status in two national cohorts".

The analyses use two national cohort studies in China (CHARLS and CLHLS). No restricted or licensed cohort microdata are redistributed in this upload. In particular, this upload does not include any downloaded CHARLS/CLHLS datasets (in whole or in part), nor any participant-level records or identifiers. The original cohort data must be obtained directly from the official data providers under their application procedures and data-use agreements.

The package includes: (i) curated analysis scripts, (ii) documentation/manifests for file integrity, and (iii) small numeric tables that correspond to values already shown in the manuscript/appendix.
DOI: 10.15468/dl.rvgadv
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "TaxonKey is Hyporthodus nigritus"
 ]
}

 The dataset includes 166 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004404-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/wd55vcryt9.3
title: Reproducibility package (code + published tables only; no redistributed cohort data) for: Temperature variability and mortality among older adults in China: effect modification by functional status in two national cohorts

description: This dataset contains a reproducibility package (analysis code and published summary result tables) for the study:

"Temperature variability and mortality among older adults in China: effect modification by functional status in two national cohorts".

The analyses use two national cohort studies in China (CHARLS and CLHLS). No restricted or licensed cohort microdata are redistributed in this upload. In particular, this upload does not include any downloaded CHARLS/CLHLS datasets (in whole or in part), nor any participant-level records or identifiers. The original cohort data must be obtained directly from the official data providers under their application procedures and data-use agreements.

The package includes: (i) curated analysis scripts, (ii) documentation/manifests for file integrity, and (iii) small numeric tables that correspond to values already shown in the manuscript/appendix.
DOI: 10.17632/26ftwwy9b3.1
title: Pertanyaan dan Hasil Persentase Evaluasi Heuristik

description: 28 pertanyaan berdasarkan 10 prinsip evaluasi heuristik dan hasil data skala likert berupa persentase.
DOI: 10.15468/dl.cj4ps2
title: Occurrence Download

description: A dataset containing 632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anthoxanthum odoratum",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 632 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004405-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rbwyfhvb9k
title: Digital Capability and Green Innovation as Drivers of Sustainable SME Performance

description: This study employs a quantitative research design to examine the relationships among Smart Digital Capability, Green Innovation, and Sustainable Performance in small and medium enterprises located in West Java, Indonesia. A survey method was chosen because it enables systematic measurement of latent constructs and testing of structural relationships in digital transformation and sustainability research.
The population consists of SMEs operating in manufacturing, creative industries, food processing, and service sectors in West Java. These sectors were selected due to their significant contribution to the regional economy and increasing exposure to digital transformation and sustainability pressures. Data were collected from SME owners or managers who are directly involved in operational and strategic decision making.
The minimum sample size was determined based on Partial Least Squares Structural Equation Modeling requirements. According to the ten times rule, the minimum sample should be at least ten times the largest number of structural paths directed at a latent construct or ten times the largest number of indicators used to measure a single construct. In this study, the largest construct contains five indicators, and the maximum number of structural paths directed at one endogenous construct is two. Therefore, the minimum required sample size exceeds fifty respondents. To enhance statistical power and robustness of the model estimation, the final sample size was set substantially above this minimum threshold.
All constructs were modeled as reflective constructs and measured using a five point Likert scale ranging from strongly disagree to strongly agree. Smart Digital Capability was measured using five indicators reflecting digital integration, system connectivity, data utilization, process automation, and digital responsiveness, adapted from digital capability and digital transformation literature. Green Innovation was measured using five indicators representing environmentally oriented innovation practices including eco friendly process improvement, energy efficiency, waste reduction, cleaner production, and environmentally oriented product or service development, adapted from eco innovation literature. Sustainable Performance was measured using five indicators reflecting resource efficiency, environmental impact reduction, operational sustainability, long term performance stability, and sustainable competitiveness, based on sustainability and environmental management research
DOI: 10.5281/zenodo.18749212
title: Theory of Constitutive Intelligence (TCI)
title: Formal Proposal for a Unified Theory of Science (Proposal for discussion and development by the scientific community)

description: A review and reformulation of official theories.
DOI: 10.17632/rbwyfhvb9k.1
title: Digital Capability and Green Innovation as Drivers of Sustainable SME Performance

description: This study employs a quantitative research design to examine the relationships among Smart Digital Capability, Green Innovation, and Sustainable Performance in small and medium enterprises located in West Java, Indonesia. A survey method was chosen because it enables systematic measurement of latent constructs and testing of structural relationships in digital transformation and sustainability research.
The population consists of SMEs operating in manufacturing, creative industries, food processing, and service sectors in West Java. These sectors were selected due to their significant contribution to the regional economy and increasing exposure to digital transformation and sustainability pressures. Data were collected from SME owners or managers who are directly involved in operational and strategic decision making.
The minimum sample size was determined based on Partial Least Squares Structural Equation Modeling requirements. According to the ten times rule, the minimum sample should be at least ten times the largest number of structural paths directed at a latent construct or ten times the largest number of indicators used to measure a single construct. In this study, the largest construct contains five indicators, and the maximum number of structural paths directed at one endogenous construct is two. Therefore, the minimum required sample size exceeds fifty respondents. To enhance statistical power and robustness of the model estimation, the final sample size was set substantially above this minimum threshold.
All constructs were modeled as reflective constructs and measured using a five point Likert scale ranging from strongly disagree to strongly agree. Smart Digital Capability was measured using five indicators reflecting digital integration, system connectivity, data utilization, process automation, and digital responsiveness, adapted from digital capability and digital transformation literature. Green Innovation was measured using five indicators representing environmentally oriented innovation practices including eco friendly process improvement, energy efficiency, waste reduction, cleaner production, and environmentally oriented product or service development, adapted from eco innovation literature. Sustainable Performance was measured using five indicators reflecting resource efficiency, environmental impact reduction, operational sustainability, long term performance stability, and sustainable competitiveness, based on sustainability and environmental management research
DOI: 10.5281/zenodo.18749211
title: Theory of Constitutive Intelligence (TCI)
title: Formal Proposal for a Unified Theory of Science (Proposal for discussion and development by the scientific community)

description: A review and reformulation of official theories.
DOI: 10.15468/dl.nbdnj5
title: Occurrence Download

description: A dataset containing 938 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "TaxonKey is Hyporthodus niveatus"
 ]
}

 The dataset includes 938 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004406-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rff3zpbcbx
title: Norm Elicitation and Field Experiment Data on Zero-Price Effects Across Contexts

description: The Role of Social Norms in Zero Price effects