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.
90
datasets available to search
ShareScore release 0.9.0
Dataset results
90 results for “Cross-Cultural”
Cross-Cultural Adaptation, Validity, and Reliability of the Wexner Questionnaire in Patients With Constipation
ClinicalTrials.gov study NCT07340203. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Urdu Translation And Cross-Cultural Validation of the Foot And Ankle Disability Index
ClinicalTrials.gov study NCT05732636. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Cross-cultural Adaptation and Validation of the Ankle Osteoarthritis Scale (AOS) for Use in French-speaking Populations
ClinicalTrials.gov study NCT02508233. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Cross-cultural Adaptation of the Chinese Version of QoLAF-Q (Quality of Life in Patients With Anal Fistula Questionnaire) ：A Multi-center Study
ClinicalTrials.gov study NCT06962228. IPD Sharing: NO. Countries: 0. Publications: 0.
Basic Life Support (BLS) and Barriers to Cross-Cultural Education
ClinicalTrials.gov study NCT00715767. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Cross-cultural Validation of the Arabic 10-Factors Big Five Scale Using Factor Analysis
<p>In Arab World, the big five aspect scale (BFAS) with 10 factors domain currently lacks validating evidence. The BFAS structure was investigated in Libyan adult sample (N = 1163). The sample completed the BFAS, and the International Personality Item Pool (IPIP) to assess the BFAS validity. Results found that The BFAS Conscientiousness, Extraversion, Introversion Openness/Intellect are correlated positively with IPIP Conscientiousness, Extraversion, Introversion, Intellect, The BFAS Neuroticism was negatively correlated with IPIP emotional stability. Results found that the BFAS scales includes its 10 domains, has good internal consistency, and is strongly related to major personality dimensions assessed by the leading questionnaire. To conclude, the findings indicate that the Arabic BFAS is reliable, valid, and comparable to the original English version. This study provides valuable insights into an individual's personality and behavior, which can have implications for personal, professional, and clinical contexts.</p>
Translation, Cross-Cultural Adaptation and Validation of the Lymphedema Quality of Life Questionnaire (LYMQOL) in German Patients with Lymphedema of the Upper or Lower Limbs
<p>Raw data collected during interviews 1 and 2.</p>
Cross-cultural adaptation and validation of a surgical neonatal nursing workload tool to the Italian context: The Italian Win-nipeg Surgical Complex Assessment of Neonatal Nursing Needs Tool
Open the record for dataset details and reuse information.
MuSe-Humor: Cross-Cultural Humor Detection Sub-Challenge (MuSe 2023)
<p><strong>Description</strong>: Predicting the presence of humor in football press conference recordings. Available modalities: audio and video, transcriptions. The dataset offers a cross-cultural setting: all press conferences in the training and development partition are held in German, all videos in the test partition are taken from English Premier League press conferences.</p> <p><strong>Important</strong>: <strong>this package does not include the recordings themselves, please find them here</strong>: <a href="https://zenodo.org/deposit/7843460">https://zenodo.org/record/7843460</a></p> <p><strong>Labels</strong>: windows of 2 seconds are given a binary label, indicating presence and absence of humor. At least 7 human annotators labelled each video.</p> <p><strong>Dataset</strong>: MuSe-Humor is based on the Passau-Spontaneous Football Coach Humor (Passau-SFCH) dataset (<a href="https://arxiv.org/pdf/2209.14272.pdf">paper</a>). It includes press conference recordings of 10 different German Bundesliga football coaches collected in 2017. Moreover, for the MuSe 2023 challenge, recordings of 6 Premier League coaches have been added. The data provided here only includes segments in which the respective coach is speaking. The training data set contains recordings of 7 German-speaking coaches, development data consists of videos of 3 German-speaking coaches; and the test data set comprises recordings of 6 English-speaking coaches (one native speaker).</p> <p><strong>General</strong>: The <a href="http://muse-challenge.org">4th Multimodal Sentiment Analysis Challenge and Workshop (MuSe) 2023</a> adresses research questions that are of interest to affective computing, machine learning and multimodal signal processing communities and encourages a fusion of their disciplines. The goal of the MuSe workshop and challenge is to gain new insights into the merits of each of the core modalities and to serve as a stimulating environment for the development and evaluation of multimodal affect recognition approaches.</p>
MuSe-Humor: Cross-Cultural Humor Detection Sub-Challenge (MuSe 2024) - Videos
<p><strong>Description</strong>: Predicting the presence of humor in football press conference recordings. Available modalities: audio and video, transcriptions. The dataset offers a cross-cultural setting: all press conferences in the training and development partition are held in German, and all videos in the test partition are taken from English Premier League press conferences.</p> <p><strong>Important</strong>: <strong>This package only contains the video recordings, please find labels, audio files, transcripts and features here</strong>: <a href="../records/11211840">https://zenodo.org/records/11211840</a></p> <p><strong>Labels</strong>: windows of 2 seconds are given a binary label, indicating the presence and absence of humor. At least 7 human annotators labeled each video.</p> <p><strong>Dataset</strong>: MuSe-Humor is based on the Passau-Spontaneous Football Coach Humor (Passau-SFCH) dataset (<a href="https://arxiv.org/pdf/2209.14272.pdf">paper</a>). It includes press conference recordings of 10 different German Bundesliga football coaches collected in 2017. Moreover, for the MuSe 2024 challenge, recordings of 6 Premier League coaches have been added. The data provided here only includes segments in which the respective coach is speaking. The training data set contains recordings of 7 German-speaking coaches, development data consists of videos of 3 German-speaking coaches, and the test data set comprises recordings of 6 English-speaking coaches (one native speaker).</p> <p><strong>General</strong>: The <a href="http://muse-challenge.org/">5th Multimodal Sentiment Analysis Challenge and Workshop (MuSe) 2024</a> addresses research questions that are of interest to affective computing, machine learning and multimodal signal processing communities and encourages a fusion of their disciplines. The goal of the MuSe workshop and challenge is to gain new insights into the merits of each of the core modalities and to serve as a stimulating environment for the development and evaluation of multimodal affect recognition approaches.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research 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.
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.
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.
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.
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.