cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.qjvv8u
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dorstenia poinsettifolia var. achoundongiana Cheek & Bygrave"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042652-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/9068253
title: Augmented_intense_1
DOI: 10.17632/rp3f7mdjxz.1
title: Data for: Spatial Characteristics and Future Forecasting of Carbon Dioxide Emissions in China: A Provincial-Level Analysis

description: The dataset includes the important data in the 'Spatial Characteristics and Future Forecasting of Carbon Diox-ide Emissions in China: A Provincial-Level Analysis'.Sheet 1 shows the economic and energy data of China's 31 provinces for training the mode. Sheet 2 shows the data for prediction. Sheet 3 shows the accounting results of carbon dioxide emissions in 31 provinces of China from 1999 to 2019 and prediction of carbon dioxide emissions by 2035.The sources and processing methods of all data have been mentioned in the paper.
DOI: 10.17632/s34kdmf5fr.1
title: Supply Chain Model

description: The model was used to simulate the experiments and produce the data.
DOI: 10.17632/ynck3f799k.1
title: FEBio Model Files for Torsion of Solid and Biphasic Mooney–Rivlin Cylinders

description: The FEBio model files provided in this Mendeley Dataset were used to produce the computational results in the paper "Poynting effect in fluid-saturated poroelastic soft materials in torsion" (published in the International Journal of Non-Linear Mechanics in March 2024). The model files were run with the open-source finite element software FEBio (Version 1.9.0).
DOI: 10.15468/dl.ybatuu
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Speleomantes sarrabusensis Lanza, Leo, Forti, Cimmaruta, Caputo & Nascetti, 2001"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042653-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22815770.v5
title: Classification and Challenges of Non-Functional Requirements in ML-Enabled Systems: A Systematic Literature Review

description: This item contains the replication package related to the paper <b>"</b><b>Classification and Challenges of Non-Functional Requirements in ML-Enabled Systems: A Systematic Literature Review</b><b>"</b> which includes the results of the various steps of our study and plots.
DOI: 10.15468/dl.jn6umx
title: Occurrence Download

description: A dataset containing 396840 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Crabronidae"
 ]
}

 The dataset includes 396840 records from 282 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042647-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/c862-0e81.75
title: US Television Coverage of Climate Change or Global Warming, 2000-2024 - June 2024

description: The Media and Climate Change Observatory Data monitors 130 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5281/zenodo.13135635
title: Interviews with editors of library science journals on transitioning to open access

description: These three files are related to qualitative, semi-structured interviews conducted in Fall 2023 with editors of Library and Information Science (LIS) journals on transitioning to open access. One subgroup consisted of participants who were editors at the time of an LIS journal when it transitioned (or flipped) to an open access model that does not charge a fee to either readers or authors (which this study refers to as equitable open access), and the other subgroup consisted of current editors (at the time) of LIS journals that have not yet transitioned (or unflipped) to an equitable open access model. Two of the files are the interview protocols for each group of flipped and unflipped editors, and the third file is the codebook the researchers used to analyze the interview transcripts. Interview transcripts are not being publicly shared to ensure confidentiality for interview participants.

The interview protocols were created based on the findings of a prior research study:

Borchardt, R., Dawson, D., & Schultz, T. (2024). Financial and other perceived barriers to transitioning to an equitable no-publishing fee open access model: A survey of LIS journal editors. College & Research Libraries, 85(1). https://doi.org/10.5860/crl.85.1.96

The codebook was created iteratively based on the researchers' review and analysis of the interview transcripts.
DOI: 10.5281/zenodo.13135636
title: Interviews with editors of library science journals on transitioning to open access

description: These three files are related to qualitative, semi-structured interviews conducted in Fall 2023 with editors of Library and Information Science (LIS) journals on transitioning to open access. One subgroup consisted of participants who were editors at the time of an LIS journal when it transitioned (or flipped) to an open access model that does not charge a fee to either readers or authors (which this study refers to as equitable open access), and the other subgroup consisted of current editors (at the time) of LIS journals that have not yet transitioned (or unflipped) to an equitable open access model. Two of the files are the interview protocols for each group of flipped and unflipped editors, and the third file is the codebook the researchers used to analyze the interview transcripts. Interview transcripts are not being publicly shared to ensure confidentiality for interview participants.

The interview protocols were created based on the findings of a prior research study:

Borchardt, R., Dawson, D., & Schultz, T. (2024). Financial and other perceived barriers to transitioning to an equitable no-publishing fee open access model: A survey of LIS journal editors. College & Research Libraries, 85(1). https://doi.org/10.5860/crl.85.1.96

The codebook was created iteratively based on the researchers' review and analysis of the interview transcripts.
DOI: 10.15468/dl.guzhe7
title: Occurrence Download

description: A dataset containing 131 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Madhuca pasquieri (Dubard) H.J.Lam"
 ]
}

 The dataset includes 131 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042655-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hy9ggu
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material sample, Specimen)",
 "Country is Bangladesh",
 "OccurrenceStatus is Present",
 "TaxonKey is Ficus L.",
 "Year 2000-2024"
 ]
}

 The dataset includes 41 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042656-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.43cugc
title: Occurrence Download

description: A dataset containing 26244 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-99.29791 18.81436,-99.32373 18.72851,-99.16883 18.70048,-99.16946 18.81138,-99.29791 18.81436))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 26244 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042654-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8k8m9h
title: Occurrence Download

description: A dataset containing 6149 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Hongos del estado de Veracruz"
 ]
}

 The dataset includes 6149 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042657-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13135862
title: Males following a terminal investment strategy can fake their body odors to females, yet they cannot fake the odor of their microbiome

description: Terminal investment and dishonesty are likely the only strategies by which sick males in our study could attract females to reproduce. We show that immunocompromised male yellow mealworm beetles (Tenebrio molitor) employing a terminal investment strategy can fake their bodily sex pheromones to females, yet they cannot fake the fecal odor of their microbiome. The results of this study have important methodological recommendations for future studies in the field of terminal investment strategy, showing the need to consider the role of sex odors and signals produced by the microbiome.
DOI: 10.5281/zenodo.13135863
title: Males following a terminal investment strategy can fake their body odors to females, yet they cannot fake the odor of their microbiome

description: Terminal investment and dishonesty are likely the only strategies by which sick males in our study could attract females to reproduce. We show that immunocompromised male yellow mealworm beetles (Tenebrio molitor) employing a terminal investment strategy can fake their bodily sex pheromones to females, yet they cannot fake the fecal odor of their microbiome. The results of this study have important methodological recommendations for future studies in the field of terminal investment strategy, showing the need to consider the role of sex odors and signals produced by the microbiome.
DOI: 10.15468/dl.9eqz84
title: Occurrence Download

description: A dataset containing 1278 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salamandrina perspicillata (Savi, 1821)"
 ]
}

 The dataset includes 1278 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042658-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/4c3b-b819.75
title: World Newspaper Coverage of Climate Change or Global Warming, 2004-2024 - June 2024

description: The Media and Climate Change Observatory Data monitors 127 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.6084/m9.figshare.26406205
title: Abundance and occupancy data for invertebrate species associated to intertidal mussel patches

description: This file contains data on the abundance and occupancy of invertebrate species found in intertidal mussel patches in Nova Scotia, Canada.
DOI: 10.26300/crq0-ge81
title: Data documentation for "From Diagnosis to Displacement: The Unique Migration Patterns of Dementia Patients"
DOI: 10.25810/k55w-7a04.75
title: World Radio Coverage of Climate Change or Global Warming, 2000-2024 - June 2024

description: The Media and Climate Change Observatory Data monitors 130 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.15468/dl.s43rn7
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dorstenia poinsettifolia var. etugeana B.J.Pollard"
 ]
}

 The dataset includes 16 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042659-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12772405
title: Data cleaning using unstructured data

description: In this project, we work on repairing three datasets:



Trials design: This dataset was obtained from the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) register and the ground truth was created from external registries. In the dataset, multiple countries, identified by the attribute country_protocol_code, conduct the same clinical trials which is identified by eudract_number. Each clinical trial has a title that can help  find informative details about the design of the trial.

Trials population: This dataset delineates the demographic origins of participants in clinical trials primarily conducted across European countries. This dataset include structured attributes indicating whether the trial pertains to a specific gender, age group or healthy volunteers. Each of these categories is labeled as (`1') or (`0') respectively denoting whether it is included in the trials or not. It is important to note that the population category should remain consistent across all countries conducting the same clinical trial identified by an eudract_number. The ground truth samples in the dataset were established by aligning information about the trial populations provided by external registries, specifically the CT.gov database and the German Trials database.  Additionally, the dataset comprises other unstructured attributes that categorize the inclusion criteria for trial participants such as inclusion.

Allergens: This dataset contains information about products and their allergens. The data was collected from the German version of the `Alnatura' (Access date: 24 November, 2020), a free database of food products from around the world `Open Food Facts', and the websites: `Migipedia', 'Piccantino', and  `Das Ist Drin'. There may be overlapping products across these websites.  Each product in the dataset is identified by a unique code.  Samples with the same code represent the same product but are extracted from a differentb source. The allergens are indicated by (‘2’) if present, or (‘1’) if there are traces of it, and (‘0’) if it is absent in a product. The dataset also includes information on ingredients in the products. Overall, the dataset comprises categorical structured data describing the presence, trace, or absence of specific allergens, and unstructured text describing ingredients. 


N.B: Each '.zip' file contains a set of 5 '.csv' files which are part of the afro-mentioned datasets:



"{dataset_name}_train.csv": samples used for the ML-model training. (e.g "allergens_train.csv")

"{dataset_name}_test.csv": samples used to test the the ML-model performance. (e.g "allergens_test.csv")

"{dataset_name}_golden_standard.csv": samples represent the ground truth of the test samples. (e.g "allergens_golden_standard.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used for the ML-model training. (e.g "allergens_parker_train.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used to test the the ML-model performance. (e.g "allergens_parker_test.csv")
DOI: 10.5281/zenodo.12772406
title: Data cleaning using unstructured data

description: In this project, we work on repairing three datasets:



Trials design: This dataset was obtained from the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) register and the ground truth was created from external registries. In the dataset, multiple countries, identified by the attribute country_protocol_code, conduct the same clinical trials which is identified by eudract_number. Each clinical trial has a title that can help  find informative details about the design of the trial.

Trials population: This dataset delineates the demographic origins of participants in clinical trials primarily conducted across European countries. This dataset include structured attributes indicating whether the trial pertains to a specific gender, age group or healthy volunteers. Each of these categories is labeled as (`1') or (`0') respectively denoting whether it is included in the trials or not. It is important to note that the population category should remain consistent across all countries conducting the same clinical trial identified by an eudract_number. The ground truth samples in the dataset were established by aligning information about the trial populations provided by external registries, specifically the CT.gov database and the German Trials database.  Additionally, the dataset comprises other unstructured attributes that categorize the inclusion criteria for trial participants such as inclusion.

Allergens: This dataset contains information about products and their allergens. The data was collected from the German version of the `Alnatura' (Access date: 24 November, 2020), a free database of food products from around the world `Open Food Facts', and the websites: `Migipedia', 'Piccantino', and  `Das Ist Drin'. There may be overlapping products across these websites.  Each product in the dataset is identified by a unique code.  Samples with the same code represent the same product but are extracted from a differentb source. The allergens are indicated by (‘2’) if present, or (‘1’) if there are traces of it, and (‘0’) if it is absent in a product. The dataset also includes information on ingredients in the products. Overall, the dataset comprises categorical structured data describing the presence, trace, or absence of specific allergens, and unstructured text describing ingredients. 


N.B: Each '.zip' file contains a set of 5 '.csv' files which are part of the afro-mentioned datasets:



"{dataset_name}_train.csv": samples used for the ML-model training. (e.g "allergens_train.csv")

"{dataset_name}_test.csv": samples used to test the the ML-model performance. (e.g "allergens_test.csv")

"{dataset_name}_golden_standard.csv": samples represent the ground truth of the test samples. (e.g "allergens_golden_standard.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used for the ML-model training. (e.g "allergens_parker_train.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used to test the the ML-model performance. (e.g "allergens_parker_test.csv")
DOI: 10.5281/zenodo.13135983
title: Data cleaning using unstructured data

description: In this project, we work on repairing three datasets:



Trials design: This dataset was obtained from the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) register and the ground truth was created from external registries. In the dataset, multiple countries, identified by the attribute country_protocol_code, conduct the same clinical trials which is identified by eudract_number. Each clinical trial has a title that can help  find informative details about the design of the trial.

Trials population: This dataset delineates the demographic origins of participants in clinical trials primarily conducted across European countries. This dataset include structured attributes indicating whether the trial pertains to a specific gender, age group or healthy volunteers. Each of these categories is labeled as (`1') or (`0') respectively denoting whether it is included in the trials or not. It is important to note that the population category should remain consistent across all countries conducting the same clinical trial identified by an eudract_number. The ground truth samples in the dataset were established by aligning information about the trial populations provided by external registries, specifically the CT.gov database and the German Trials database.  Additionally, the dataset comprises other unstructured attributes that categorize the inclusion criteria for trial participants such as inclusion.

Allergens: This dataset contains information about products and their allergens. The data was collected from the German version of the `Alnatura' (Access date: 24 November, 2020), a free database of food products from around the world `Open Food Facts', and the websites: `Migipedia', 'Piccantino', and  `Das Ist Drin'. There may be overlapping products across these websites.  Each product in the dataset is identified by a unique code.  Samples with the same code represent the same product but are extracted from a differentb source. The allergens are indicated by (‘2’) if present, or (‘1’) if there are traces of it, and (‘0’) if it is absent in a product. The dataset also includes information on ingredients in the products. Overall, the dataset comprises categorical structured data describing the presence, trace, or absence of specific allergens, and unstructured text describing ingredients. 


N.B: Each '.zip' file contains a set of 5 '.csv' files which are part of the afro-mentioned datasets:



"{dataset_name}_train.csv": samples used for the ML-model training. (e.g "allergens_train.csv")

"{dataset_name}_test.csv": samples used to test the the ML-model performance. (e.g "allergens_test.csv")

"{dataset_name}_golden_standard.csv": samples represent the ground truth of the test samples. (e.g "allergens_golden_standard.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used for the ML-model training. (e.g "allergens_parker_train.csv")

"{dataset_name}_parker_train.csv": samples repaired using Parker Engine used to test the the ML-model performance. (e.g "allergens_parker_test.csv")
DOI: 10.17632/h2t5tdjckt.1
title: Interdisciplinary Teaching About Refugee and Migrant Policy and Experiences Using Simulation and Story

description: Anonymous pre- and post-survey responses were collected on the first and last day of class that gauged student knowledge of refugee and migrant definitions, issues, contemporary numerical figures, as well as their understanding of refugee and migrant stories and the impact of narrative on their learning. Statistical analysis using a repeated measures ANOVA and a paired samples t-test were conducted to test three null hypotheses: that after the interdisciplinary pedagogical interventions there would be no change in student 1) confidence, 2) knowledge, or 3) perception. The results of the tests for the 13 questions indicated a significant effect of the interdisciplinary pedagogical intervention on student confidence in their ability to discuss the material and in their knowledge about refugee and migrant laws and policies (hypothesis 1). But results did not show a significant effect on their actual knowledge of laws, policies, and numbers (hypothesis 2).