cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11171863
title: Unfair Inequality in Education: A Benchmark for AI-Fairness Research (Aequitas WP7 Use Case S2)

description: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

This dataset proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students' performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.

Structure

benchmark contains:



the proposed dataset (dataset.csv), and

the mask for dealing with missing values (missing_mask.csv).


raw_data includes:



the original dataset (original.csv), and

the intermediate stages of the pre-processing pipeline (split and pre_processed).


res contains the documentation, including:



the transformation mapping each column of the original dataset to the proposed one, along with the missingness category and original text (meta_data_mapping.csv), and

the value type and domains of each column of the original, intermediate-stage, and proposed datasets (rispectively, meta_data_original.json and meta_data_merged.json and meta_data_final.json).


src contains the source code for running the pre-processing and corresponding analysis:



pre_processing and statscontain the code for the two corresponding tasks, and

pre_processing.py and split.py are two entry points.


Finally, Dockerfile and requirements.txt set up the environment for running the applications across multiple platforms and with Python, respectively.
DOI: 10.5281/zenodo.15546628
title: Unfair Inequality in Education: A Benchmark for AI-Fairness Research (Aequitas WP7 Use Case S2)

description: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

This dataset proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students' performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.

Structure

benchmark contains:



the proposed dataset (dataset.csv), 

the mask for dealing with missing values (missing_mask.csv), and





the meta-columns providing grouping criteria and sample weights for each student (meta_cols.csv).




raw_data includes:



the original dataset (original.csv), and

the intermediate stages of the pre-processing and validation pipelines (split, pre_processed, and validation).


res contains the documentation, including:



the transformation mapping each column of the original dataset to the proposed one, along with the missingness category and original text (meta_data_mapping.csv),

the value type and domains of each column of the proposed datasets (meta_data_stats.json), and





the statistical indices of the validation pipeline  (bias_preservation_results.json).




src contains the source code for running the pre-processing and corresponding analysis:



pre_processing and statscontain the code for the two corresponding tasks, and

pre_processing.py and split.py are two entry points.


Finally, Dockerfile and requirements.txt set up the environment for running the applications across multiple platforms and with Python, respectively.
DOI: 10.5281/zenodo.13956530
title: Raw data for physiological assays

description: Raw data used to generate all main and supplemental figures.
DOI: 10.5281/zenodo.13956531
title: Raw data for physiological assays

description: Raw data used to generate all main and supplemental figures.
DOI: 10.15468/dl.66ddnm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Myzomela rubratra (R.Lesson, 1827))",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015440-250525065834625/datasets/export for details.
DOI: 10.15468/dl.wkjcqq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Myzomela rubratra (R.Lesson, 1827))",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015441-250525065834625/datasets/export for details.
DOI: 10.15468/dl.pnzusy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Myzomela rubratra (R.Lesson, 1827))",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015442-250525065834625/datasets/export for details.
DOI: 10.7910/dvn/mrdlod
title: National Survey of Academic Researchers

description: This dataset contains responses from the National Survey of Academic Researchers. A detailed description of the survey can be found at https://arxiv.org/abs/2312.01442
DOI: 10.15468/dl.cwbhqv
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((14.8 -35.1,33.1 -35.1,33.1 -17.2,14.8 -17.2,14.8 -35.1))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Megachile semiflava Cockerell, 1937",
 "Year 1970-2024"
 ]
}

 The dataset includes 207 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011724-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/00002829
title: A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Multicenter Study to Determine the Safety and Efficacy of Natalizumab in Subjects With Relapsing-Remitting Multiple Sclerosis

description: The purpose of this study is to determine the safety and efficacy of natalizumab in the treatment of individuals who have been diagnosed with relapsing remitting multiple sclerosis (MS). It is hoped that natalizumab will prevent certain types of white blood cells from moving out of the bloodstream into organs, including the brain, that are being damaged by autoimmune disease (a disease in which the body's own immune system attacks certain organs). These white blood cells are thought to cause inflammation that can result in lesions (small areas of damage) in the brain. These lesions are thought to be the cause of relapses and disability in MS.
DOI: 10.25934/00002830
title: A Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Multicenter Study to Determine the Safety and Efficacy of Natalizumab, When Added to Avonex® (Interferon Beta-1a), in Subjects With Relapsing-Remitting Multiple Sclerosis

description: The purpose of this study is to determine if natalizumab in combination with AVONEX is safe and effective in delaying progression of individuals diagnosed with relapsing remitting Multiple Sclerosis (MS).
DOI: 10.25934/00002844
title: A Randomized, Multicenter, Double-Blind, Placebo-Controlled, Dose-Comparison Study to Determine the Efficacy and Safety of BG00012 in Subjects With Relapsing-Remitting Multiple Sclerosis

description: To determine if treatment with BG00012 can decrease the number of MS relapses during a certain time period. To determine if, over time, BG00012 treatment can decrease the number of certain types of brain lesions commonly seen in MS patients and slow down the time it takes for the disease to get worse. The purpose of this study is also to determine the safety of BG00012 and how well it is tolerated. Another goal is to see what effect BG00012 may have on tests and evaluations used to assess MS.
DOI: 10.25934/00002846
title: A Randomized, Multicenter, Placebo-Controlled and Active Reference (Glatiramer Acetate) Comparison Study to Evaluate the Efficacy and Safety of BG00012 in Subjects With Relapsing-Remitting Multiple Sclerosis

description: To determine if treatment with BG00012 can decrease the number of MS relapses during a certain time period. Other goals of the study are to determine if, over time, BG00012 treatment can decrease the number of certain types of brain lesions commonly seen in MS patients and slow down the time it takes for MS to get worse. Other objectives of the study are to determine the safety and tolerability of BG00012, as well as the effect it may have on tests and evaluations used to assess MS. Additionally, glatiramer acetate is being used to compare its benefits and risks with placebo and BG00012.
DOI: 10.25934/00002883
title: A Dose-Frequency Blinded, Multicenter, Extension Study to Determine the Long-Term Safety and Efficacy of PEGylated Interferon Beta-1a (BIIB017) in Subjects With Relapsing Multiple Sclerosis

description: The primary objective of this study is to evaluate the long-term safety and tolerability of peginterferon beta-1a (BIIB017) in participants originally treated in Study 105MS301 (NCT00906399) who continue peginterferon beta-1a treatment. The secondary objective of this study is to describe long-term multiple sclerosis (MS) outcomes in participants originally treated in Study 105MS301 (NCT00906399) who continue peginterferon beta-1a treatment.
DOI: 10.25934/00003226
title: A Multicenter, Randomized, Double-Blind, Parallel-Group, Placebo-Controlled Study to Evaluate the Efficacy and Safety of PEGylated Interferon Beta-1a (BIIB017) in Subjects With Relapsing Multiple Sclerosis

description: The primary objective of this study is to determine the efficacy of peginterferon beta-1a in reducing the annualized relapse rate (ARR) in participants with relapsing multiple sclerosis (RMS) at 1 year. The secondary objectives of this study are to determine whether peginterferon beta-1a, at 1 year when compared with placebo, is effective in reducing the total number of new or newly enlarging T2 hyperintense lesions on brain magnetic resonance imaging (MRI) scans, reducing the proportion of participants who relapse, and slowing the progression of disability.
DOI: 10.25934/pr00007645
title: A Phase 3 Randomized, Rater-Blinded Study Comparing Two Annual Cycles of Intravenous Alemtuzumab to Three-Times Weekly Subcutaneous Interferon Beta-1a (Rebif®) in Treatment-Naïve Patients With Relapsing-Remitting Multiple Sclerosis

description: The purpose of this study was to establish the efficacy and safety of alemtuzumab (Lemtrada™) as a treatment for relapsing-remitting multiple sclerosis (MS), in comparison with subcutaneous (SC) interferon beta-1a (Rebif®). The study had enrolled participants who had not previously received MS disease-modifying therapies. Participants had monthly laboratory tests and comprehensive testing every 3 months.
DOI: 10.25934/pr00009298
title: A Dose-Blind, Multicenter, Extension Study to Determine the Long-Term Safety and Efficacy of Two Doses of BG00012 Monotherapy in Subjects With Relapsing-Remitting Multiple Sclerosis

description: The primary objective of this study is to evaluate the long-term safety profile of BG00012 (dimethyl fumarate). Secondary objectives of this study are to evaluate the long-term efficacy of BG00012 using clinical endpoints and disability progression, to evaluate further the long-term effects of BG00012 on multiple sclerosis (MS) brain lesions on magnetic resonance imaging (MRI) scans in participants who had MRI scans as part of Studies 109MS301 (NCT00420212) and 109MS302 (NCT00451451) and to evaluate the long-term effects of BG00012 on health economics assessments and the visual function test.
DOI: 10.25934/pr00010441
title: Examining Heterogeneity in Response to Disease-Modifying Therapy in Multiple Sclerosis

description: The results from clinical trials typically provide an average treatment effect which is then used in clinical decision making for an individual patient. Multiple sclerosis (MS) is a chronic neurological disease with considerable heterogeneity, or differences, in outcomes. These differences may also extend to how a person responds to an MS drug – this is called “heterogeneity of treatment effect” (HTE). For example, the effect of an MS drug might be larger for younger individuals with relapsing remitting MS (RRMS, a type of MS that's characterized by periods of symptom flare-ups, or relapses, followed by periods of recovery, or remissions) who have multiple gadolinium-enhancing lesions (areas of damage that show up more clearly when the chemical gadolinium is injected into the patient before a magnetic resonance imaging (MRI) scan)  than for older individuals with secondary progressive MS (SPMS, where disability steadily worsens)  without gadolinium-enhancing lesions. 

The traditional way of looking at HTE have serious limitations and most findings have not been replicated in many non-MS studies. New approaches to looking at HTE aim to provide prediction of someone’s treatment benefit using multiple patient factors at the same time and are important for personalizing care.

A few prior studies suggested that HTE may be present in clinical trials and affect outcomes in MS. For example, two proof-of-concept studies exploring HTE for relapses identified responders using a patient-specific score based on age, sex, the number of relapses prior to start the trial. However, these studies used an approach that is not the recommended approach to study this question. 

We plan to use rigorous, recommended approaches to understand if there are differences in outcomes based on a set of multiple characteristics to improve identification of the optimal treatment for an individual patient.

Our study will use existing data collected from multiple clinical trials designed to test how well MS drugs work in MS. In clinical trials, data are collected carefully, at regular intervals, and in large numbers of people. We will use these data and the recommended approaches to find characteristics, including comorbidities (other illness occurring at the same time) that may be associated with MS outcomes. We will also use these data to find out if HTE are present in MS clinical trials and what characteristics are associated with how well a MS drug works. We hope that this information will help people with MS and their clinicians make more informed and personalized decisions about treatment.

In the future, we expect the results of this study to encourage future trials to report HTE and allow for more personalized treatment decisions as new MS drugs become available and influence design of clinical trials of future MS drugs in MS.
DOI: 10.6069/ynmk-2329
title: Global Burden of Disease Study 2021 (GBD 2021) Unsafe Water Exposure Estimates 1990-2021

description: The Global Burden of Disease Study 2021 (GBD 2021), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations. This dataset contains unsafe water exposure estimates by for 1990-2021. Exposure to unsafe water is defined based on the primary water source used and the use of water treatment to improve water quality. Primary water sources include basic piped (fecal contaminated piped water), improved (including boreholes, tube wells, protected wells, and packaged or delivered water), and unimproved (including unprotected springs, unprotected wells, and surface water). Water treatment methods include boil/filter, solar/chlorine, and no treatment. Estimates include both the proportion of the population and number of individuals exposed.
DOI: 10.15468/dl.5es4q6
title: Occurrence Download

description: A dataset listing the 4741 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is United States of America",
 "IucnRedListCategory is one of (CR, EN, VU, NT)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 4741 records were derived from 1663 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001574-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t68art
title: Occurrence Download

description: A dataset containing 825562 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Betula pendula"
 ]
}

 The dataset includes 825562 records from 3037 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048920-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18316485
title: Villarsia Vent. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:56
DOI: 10.5281/zenodo.18316486
title: Villarsia Vent. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:56
DOI: 10.15468/dl.cbcz5a
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Etheostoma nianguae",
 "Country is United States of America",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000107-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tugkzc
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Etheostoma nianguae",
 "Country is United States of America",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000113-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6j47kb
title: Occurrence Download

description: A dataset containing 6631 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (North America, South America)",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Pterois volitans, Pterois miles)",
 "Year 1980-2026"
 ]
}

 The dataset includes 6631 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000112-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jvekd
title: Occurrence Download

description: A dataset containing 837 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Puccinia striiformis",
 "Year 1970-2026"
 ]
}

 The dataset includes 837 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000111-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.