Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

75

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

75 results for “gender studies”

Learn how ShareScore rates datasets ↗
zenodo44/100

Dataset for "Gender and Gender Research in a Research Community: CSTT as a Case Study"

<p>This is the dataset used for and generated during our research for the following publication:<br>Francis Borchardt, Hanna Tervanotko and Saana Sv&auml;rd&nbsp; "Gender and Gender Research in a Research Community: CSTT as a Case Study." In: Changes in Sacred Texts and Traditions: Methodological Encounters and Debates, eds. Martti Nissinen and Jutta M. Jokiranta. Resources for Biblical Study 106. SBL Press; Atlanta, USA. Pp. 517-544. 2024.<br><br></p>

opencc-by-4.0Jan 2024View details →
zenodo40/100

Gender distribution in chemistry studies in Finland (2011–2022)

<p>In Finland the government produces high level up-to-date statistical data via open data service site called Vipunen - Education Statistics Finland. It a reporting portal administered jointly by the Ministry of Education and Culture and the Finnish National Agency for Education. Read more: <a href="https://vipunen.fi/en-gb">https://vipunen.fi/en-gb</a>.</p> <p>This xlsx dataset is gathered from Vipunen. It includes chemistry university students gender distribution in terms of overall students, new students and completed degrees in bachelor, master&#39;s and doctoral levels from 2011 to 2022.</p>

opencc-by-4.0Feb 2023View details →
zenodo40/100

Aggregated data issued from the JOBIM 2021 'Gender equality observational study'

<p>JOBIM 2021 Gender analysis</p> <p>This repository contains data and script related to our observation study of gender impact on asking behavior during JOBIM 2021. In agreement with our <a href="https://research.pasteur.fr/en/project/jobim-2021-pilot-project-gender-speaking-differences-in-academia/">data policy and RGPD regulations</a>, only aggregated, anonymous and/or publicly available information are posted in this repository. Zoom exports, registration survey and observation files containing names of askers and their accompanying scripts remains private.</p> <p>Citation</p> <p>If you wish to use our data please cite our manuscript: .https://www.biorxiv.org/content/10.1101/2022.03.07.483337v3</p>

opencc-by-4.0May 2023View details →
zenodo36/100

Code repository that supports the research presented in the paper "The gender gap in higher STEM studies: a Systematic Literature Review"

<p>Resources for the Systematic Literature Review (SLR) carries out as part of PhD thesis about the gender gap in STEM studies in higher education by Sonia Verdugo-Castro and supervised by Alicia Garc&iacute;a-Holgado and M&ordf; Cruz S&aacute;nchez G&oacute;mez.</p> <p>The SLR covers papers in WoS and Scopus from 2015 to 2021.</p> <p>All the papers retrieved and the different steps in the SLR selection process are contained and documented in:</p> <ul> <li><a href="https://docs.google.com/spreadsheets/d/1ldml-Mg-oguX9gXayllojBRtZ1kjdD4WRSqYwf1yZ0o/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1ldml-Mg-oguX9gXayllojBRtZ1kjdD4WRSqYwf1yZ0o/edit?usp=sharing</a></li> </ul>

openother-openDec 2021View details →
zenodo36/100

Population-based, Age- and Gender- Stratified Sero-Survey Study for SARS-CoV-2 in Uganda

<p>Results of population-based age stratified seroepidemiological investigation in Uganda</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Exploring Gender Bias in Remote Pair Programming among Software Engineering Students: The Twincode Original Study and First External Replication (datasets)

<p>This repository contains the datasets of the original experiment (University of Seville, December 2021) and its first external replication (University of California, Berkeley, May 2022) of the Twincode exploratory study on the effects of gender bias in remote pair programming among software engineering students.</p>

opencc-by-4.0Jun 2022View details →
zenodo36/100

Supplementary Material of the research study "Towards Gender Parity: Analyzing the Women Participation in STEM"

<p><span>The files present data considered in the analysis of students graduated in Brazil, from 2010 to 2019, with the purpose of contrasting STEM and Not STEM courses. </span></p> <p><span>The data was derived from Higher Education Census [Inep,2021].</span></p> <p><span>For the classification of courses as STEM courses, it was used the definition given by the SAGA methodology [UNESCO, 2016, 2017b], which refers to the International Standard Classification of Education (ISCED). </span></p> <p><span>ISCED was then related to the International Standard Classification of Education for Graduate and Specialized Courses in Brazil (Cine Brazil) [Inep, 2021], which classifies Brazilian undergraduate courses and is referenced by the official classification of courses in the Higher Education Census [Inep,2021].</span></p> <p>&nbsp;</p> <p><strong><span>References</span></strong></p> <p><span>Inep (2021). </span><em><span>Censo da Educa&ccedil;&atilde;o Superior</span></em><span>. </span><span>Bras</span><span>&iacute;</span><span>lia, DF. Available at https://www.gov.br/inep/pt-br/areasde-atuacao/pesquisas-estatisticas-e-indicadores/censo-daeducacao-superior/censo-da-educacao-superior.</span></p> <p><span>&nbsp;</span><span>Inep (2021). </span><em><span>Cine Brasil</span></em><span>. Bras</span><span>&iacute;</span><span>lia, DF. </span><span>Available at https://www.gov.br/inep/pt-br/areas-eatuacao/</span></p> <p><span>pesquisas-estatisticas-e-indicadores/cinebrasil/cine-brasil.</span></p> <p><span>&nbsp;</span><span>UNESCO (2016). Measuring Gender Equality in Science and Engineering: the SAGA Science, Technology and Innovation Gender Objective List (STI GOL). Technical Report SAGA Working Paper 1, UNESCO, Paris.</span></p> <p><span>&nbsp;</span><span>UNESCO (2017b). Measuring Gender Equality in Science and Engineering: the SAGA Toolkit. Technical Report SAGA Working Paper 2, UNESCO, Paris.</span></p>

opencc-by-4.0May 2024View details →
zenodo36/100

Dataset for the study on Family Educational Role in Facing Gender-Based Violence in Early Childhood: Implications for Primary Education

<p>The dataset for the study "Family Educational Role in Facing Gender-Based Violence in Early Childhood: Implications for Primary Education" comprises comprehensive survey data collected from 340 fathers and 340 mothers in Amman, Jordan. The data include detailed responses on parental knowledge of gender-based violence (GBV), practical strategies employed to prevent GBV, and perceptions influenced by educational qualifications, employment types, and family size. The dataset is instrumental in understanding the family's role in combating GBV in early childhood and highlights the need for targeted educational programs. This dataset is archived with Zenodo, providing valuable insights for researchers, educators, and policymakers.</p>

opencc-by-4.0Aug 2024View details →
dryad36/100

ECG and EEG stress features for: ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study

<p>Mental health, especially stress, plays a crucial role in the quality of life. During different phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different responses to stress from men. This, therefore, may have an impact on stress detection and classification accuracy of machine learning models that genders are not taken into account. However, this has never been investigated before. In addition, only a handful of stress detection devices are scientifically validated. To this end, this work proposes stress detection and multilevel stress classification models for unspecified and specified genders through ECG and EEG signals. Models for stress detection are achieved through developing and evaluating multiple individual classifiers. On the other hand, stacking technique is employed to obtain models for multilevel stress classification. ECG and EEG features extracted from 40 subjects (21 females and 19 males) were used to train and validate the models. In the low&amp;high combined stress condition, RBF-SVM and kNN yielded the highest average classification accuracy for females (79.81%) and males (73.77%), respectively. Combining ECG and EEG, the average classification accuracy increased to at least 87.58% (male, high stress) and up to 92.70% (female, high stress). For multilevel stress classification from ECG and EEG, the accuracy for females was 62.60% and for males was 71.57%. This study shows that the difference in genders influences the classification performance for both the detection and multilevel classification of stress. The developed models can be used for both personal (through ECG) and clinical (through ECG and EEG) stress monitoring with and without taking genders into account.</p>

opencc-zeroMar 2023View details →
ClinicalTrials.gov36/100

GRACE: A Study to Compare the Effectiveness, Safety and Tolerability of PREZISTA (Darunavir)/Ritonavir by Gender and Race When Administered With Other Antiretroviral Medications in Human Immunodeficie

ClinicalTrials.gov study NCT00381303. IPD Sharing: Not stated. Countries: 3. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad36/100

ECG and EEG stress features for: ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study

Open the record for dataset details and reuse information.

publicMar 2023View details →
zenodo32/100

Deccan region, Madras, India. Genus Vandeleuria is masculine, so widely used specific name oleracea has been changed for gender agreement. Vandeleuria oleraceusis possibly a composite of species. Polytypic, but subspecific taxonomy requires reassessment. Distribution. Widespread in S Asia (India, Nepal, Bhutan, Bangladesh, and Sri Lan-ka), S China (W & S Yunnan), and mainland SE Asia N of the Isthmus of Kra. Descriptive notes. Head-body 68 mm, tail 105 mm, ear 13 mm, hindfoot 17 mm; weight 10 g. The Indomalayan Long-tailed Climbing Mouse is small, with flat nail on outer finger and outertoe; tail is slender, brown, twice as long as head-body length, and lacks distal tuft. Dorsal pelageis silky and salmon in color; venter is white, with fulvous hues. Habitat. Tall cane and tangled vines in primary and secondary forest such as bamboo forest, moist deciduous forest, temperate forests, montane wet zone, and disturbed secondary forests, and perhaps agricultural areas at elevations of 150-1500 m. Food and Feeding. Indomalayan [Long-tailed Climbing Mice eat fruits, buds, and flowers. Breeding. Litters of the Indomalayan Long-tailed Climbing Mouse have 3-6 young. Activity patterns. Indomalayan Long-tailed Climbing Mice are arboreal and nocturnal, although one individual was caught duringthe day. Movements, Home range and Social organization. Indomalayan Long-tailed Climbing Mice build nests in tall bushes or cane to rear their young. Status and Conservation. Classified as Least Concern on The IUCN Red Last (as V. olacea). The Indomalayan Long-tailed Climbing Mouse occurs in several habitats and a wide distribution that includes national parks. Further taxonomical studies are required to assess conservation status ofthis potentially diverse species complex. Bibliography. Corbet & Hill (1992), Dang Huy Huynh et al. (1994), Ellerman (1941), Marshall (1977b), Musser & Carleton (2005), Osgood (1932), Phillips (1980), Wang Yingxiang (2003). in Muridae

Deccan region, Madras, India. Genus Vandeleuria is masculine, so widely used specific name oleracea has been changed for gender agreement. Vandeleuria oleraceusis possibly a composite of species. Polytypic, but subspecific taxonomy requires reassessment. Distribution. Widespread in S Asia (India, Nepal, Bhutan, Bangladesh, and Sri Lan-ka), S China (W &amp; S Yunnan), and mainland SE Asia N of the Isthmus of Kra. Descriptive notes. Head-body 68 mm, tail 105 mm, ear 13 mm, hindfoot 17 mm; weight 10 g. The Indomalayan Long-tailed Climbing Mouse is small, with flat nail on outer finger and outertoe; tail is slender, brown, twice as long as head-body length, and lacks distal tuft. Dorsal pelageis silky and salmon in color; venter is white, with fulvous hues. Habitat. Tall cane and tangled vines in primary and secondary forest such as bamboo forest, moist deciduous forest, temperate forests, montane wet zone, and disturbed secondary forests, and perhaps agricultural areas at elevations of 150-1500 m. Food and Feeding. Indomalayan [Long-tailed Climbing Mice eat fruits, buds, and flowers. Breeding. Litters of the Indomalayan Long-tailed Climbing Mouse have 3-6 young. Activity patterns. Indomalayan Long-tailed Climbing Mice are arboreal and nocturnal, although one individual was caught duringthe day. Movements, Home range and Social organization. Indomalayan Long-tailed Climbing Mice build nests in tall bushes or cane to rear their young. Status and Conservation. Classified as Least Concern on The IUCN Red Last (as V. olacea). The Indomalayan Long-tailed Climbing Mouse occurs in several habitats and a wide distribution that includes national parks. Further taxonomical studies are required to assess conservation status ofthis potentially diverse species complex. Bibliography. Corbet &amp; Hill (1992), Dang Huy Huynh et al. (1994), Ellerman (1941), Marshall (1977b), Musser &amp; Carleton (2005), Osgood (1932), Phillips (1980), Wang Yingxiang (2003).

opennotspecifiedNov 2017View details →
zenodo32/100

Data set for the study "Perception Disparity between Women and Men on the Gender Gap in STEM at a Spanish University"

<p>Database for the study "Perception" carried out in the project "Engineering with a gender perspective" financed by the Women's Institute of the Ministry of Equality of the Spanish Government, call for proposals PAC 2021 INMUJERES (reference number 37/7ACT/21).<br>An adaptation of the GENCE 2.0 questionnaire (DOI: 10.5281/zenodo.2550690) was used to collect the data.&nbsp;</p>

opencc-by-4.0May 2024View details →
dryad32/100

Towards a simultaneously speaking bilingual robot: Primary study on the effect of gender and pitch of the robot's voice

<p>With fast and reliable international transportation, more people with different language backgrounds can interact now. As a result, the need for communicative agents fluent in several languages to assist those people is highlighted. The high cost of hiring human attendants fluent in several languages makes using social robots a more affordable alternative in international gatherings. A social robot capable of presenting a piece of information in more than one language at the same time to its audience is the goal of this line of study. However, the negative effect of background noise on speech comprehension in humans is well-established. Hence, presenting a piece of information in two different languages at the same time by the robot creates an adverse listening condition for both individuals listening to the speech of such a bilingual robot. In this study, we investigated whether manipulating the pitch and gender of the robot's voice could affect human subjects' memory of the presented information in the presence of background noise. The results indicate that the pitch and gender of the speaking voice do indeed affect our memory of the presented information. when a male voice was used, a higher pitch resulted in significantly better memory performance than a lower pitch. Contrarily, when a female voice was used, a lower pitch resulted in significantly better memory in participants than a higher pitch. Both male and female subjects performed significantly better with a female voice in a noisy background. In nutshell, the result of this study suggests using a female voice for robots in noisy conditions, as in the case of simultaneously speaking robots, can significantly improve the retrieval of presented information in human subjects.</p>

opencc-zeroDec 2022View details →
zenodo32/100

Assesing gender differences for non-predictable Breakthrough Cancer Pain Phenomenon: a secondary analysis from IOPS-MS Study

<p>IOPS-MS was a big multicentric study with the aim of characterizing BTcP in a large number of patients belonging to different settings and assessing possible factors influencing its development. Moreover, NP-BTcP topic was addressed elsewhere [https://doi.org/10.3390/cancers13164018].</p> <p>One key difference is related to the hormonal (gender related characteristics) differences between men and women. For example, estrogen and progesterone can affect pain sensitivity, with some studies suggesting that women may be more sensitive to pain during certain stages of the menstrual cycle. Similarly, testosterone may have analgesic effects in men, which could contribute to differences in pain sensitivity between genders.</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2023View details →
ClinicalTrials.gov32/100

A Study on Prevalence, Protection and Recovery From COVID-19 in Seasoned Yoga Practitioners in Comparison to Age and Gender Matched Controls

ClinicalTrials.gov study NCT04498442. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

A Clinical Study to Assess the Effect of Food and Gender on the Pharmacokinetics of SRT2104 Administered as an Oral Suspension or Capsule Formulation to Normal Healthy Volunteers

ClinicalTrials.gov study NCT00938275. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Influence of Gender Specific Differences of Saliva Composition on the Development of Dental Erosion - an In-situ Study

ClinicalTrials.gov study NCT02780973. IPD Sharing: NO. Countries: 1. Publications: 8.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

A Study to Investigate the Effect of Food, Gender, and Age on the Pharmacokinetic Profile of SUVN-D4010 in Healthy Subjects

ClinicalTrials.gov study NCT03031574. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Gender Bias in the Overuse Studies Conducting in Primary Care

ClinicalTrials.gov study NCT05233852. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record