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.
400
datasets available to search
ShareScore release 0.9.0
Dataset results
400 results for “trust”
Dataset for: Buffer Management for Trust Computation in Resource-constrained IoT Networks
<p>Dataset for Buffer Management for Trust Computation in Resource-constrained IoT Networks</p>
Data from: Economic trust in young children
Mutually beneficial interactions often require trust that others will reciprocate. Such interpersonal trust is foundational to evolutionarily-unique aspects of human social behavior, such as economic exchange. In adults, interpersonal trust is often assessed using the 'trust game,' in which a lender invests resources in a trustee who may or may not repay the loan. This game captures two crucial elements of economic exchange: the potential for greater mutual benefits by trusting in others, and the moral hazard that others may betray that trust. While adults across cultures can trust others, little is known about the developmental origins of this crucial cooperative ability. We developed the first version of the trust game for use with young children that addresses these two components of trust. Across three experiments, we demonstrate that 4- and 6-year-olds recognize opportunities to invest in others, sharing more when reciprocation is possible than in a context measuring pure generosity. Yet children become better with age at investing in trustworthy over untrustworthy partners, indicating that this cooperative skill emerges later in ontogeny. Together, our results indicate that young children can engage in complex economic exchanges involving judgments about interpersonal trust and show increasing sensitivity to appropriate partners over development.
Dataset for article: Take the money and run: Psychopathic behavior in the trust game
<p>Dataset for article: Take the money and run: Psychopathic behavior in the trust game</p>
TRUST 3D Dust RT Slab Benchmark Data
<p>Output global SEDs and images at selected wavelengths for the Slab benchmark of the TRUST collaboration. TRUST is a suite of benchmarks for 3D dust radiative transfer codes in astronomy. </p> <p>Paper describing the TRUST Slab benchmark is Gordon et al. (2017, A&A, 603, 114; http://adsabs.harvard.edu/abs/2017A&A...603A.114G)</p> <p>More details on TRUST at http://ipag.osug.fr/RT13/RTTRUST/.</p> <p>Code to make plots using this data at: https://github.com/karllark/trust_slab</p>
iCAREdata: Improving Care And Research Electronic Data Trust Antwerp
<p>The main aim of the iCAREdata-project (Improving Care And Research Electronic Data Trust Antwerp) is to develop a central, clinical research database in out-of-hours (OOH) care in Belgium.</p> <p>With this project, the research team of CHA-ELIZA is developing a state-of-the-art database, in sync with the most recent legal, ethical and privacy aspects present in Belgium and Europe.</p> <p>One crucial aspect of the project is the unique way it links data between different health care services. Subsequently, we are able to study the chain of care that patients follow in OOH care. This gives a broader view on what is exactly happening with patients suffering an unplanned medical problem.</p> <p>Weekly results of aggregated data are available at https://icare.uantwerpen.be (Dutch and English)</p> <p> </p>
Replication Package for "Trust and State Effectiveness: The Political Economy of Compliance"
<p>There is a README file that provides information on the data used in the paper titled “Trust and State Effectiveness: The Political Economy of Compliance” by Tim Besley and Sacha Dray, and steps to replicate its results.<br>DATA SOURCES:<br>Raw datasets needed for replication are in the folder "data/raw".<br>1/ IVS_clean.dta : dataset based on the Integrated Values Survey 1981-2021, which can be accessible from the World Values Survey or European Values Survey website.<br>-<br>EVS (2022): EVS Trend File 1981-2017. GESIS Data Archive, Cologne. ZA7503 Data file Version 3.0.0, doi:10.4232/1.14021.<br>-<br>2/ UK_C19_cohorts: dataset from the COVID-19 Survey in Five National Longitudinal Cohort Studies.<br>-<br>Centre for Longitudinal Studies. (2020). COVID-19 survey in five national longitudinal cohort studies: Millennium Cohort Study, Next Steps, 1970 British Cohort Study and 1958 National Child Development Study, 2020–2021 [data collection].</p>
Data for "Visual Analytics for Enhancing Quality and trust in Genome-Wide Expression Clustering and Annotation"
<p><a href="https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/bb993a532f92298639b70bf7f2cd758d/raw/e2def8df7c20551e16f296c7c303308e5418c5e9/index.html">RasteredHPA23v06BloodReport (https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/bb993a532f92298639b70bf7f2cd758d/raw/e2def8df7c20551e16f296c7c303308e5418c5e9/index.html)</a></p> <p><a href="https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/087802569e028f96648dd5387bf4aba7/raw/4c9d65f96127ff9620509cbcf2b8d01435455705/index.html">RasteredHPA23v06brainReport (https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/087802569e028f96648dd5387bf4aba7/raw/4c9d65f96127ff9620509cbcf2b8d01435455705/index.html)</a></p> <p><a href="https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/bf5d7b90428a514bbdbe7e138863d04c/raw/6cb942e57d7a703e6cf78027813aa65e340b7c78/index.html">RasteredHPA23v06CellineReport (https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/bf5d7b90428a514bbdbe7e138863d04c/raw/6cb942e57d7a703e6cf78027813aa65e340b7c78/index.html)</a></p> <p><a href="https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/44315c0313299e9a8fe5d3ba3dac49fa/raw/200be056379260764b5c94064f38e7b8f33fbcc5/index.html">RasteredHPA23v06SinglecellReport (https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/44315c0313299e9a8fe5d3ba3dac49fa/raw/200be056379260764b5c94064f38e7b8f33fbcc5/index.html)</a></p> <p><a href="https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/d6ce47837daf019acc5e22baef379b79/raw/88600436126299a6a56984b3671f1e98630e6c19/index.html">RasteredHPA23v06TissueReport (https://rictjo.github.io/?https://gist.githubusercontent.com/rictjo/d6ce47837daf019acc5e22baef379b79/raw/88600436126299a6a56984b3671f1e98630e6c19/index.html)</a></p> <p>goto gist then check revision for report datestamps</p>
Relationship between the Type of Media Consumption and Political Trust in the EU: Evidence from the 94th Eurobarometer 2020/2021 Survey
<p>This is a list of supplementary materials for the article titled "Relationship between the Type of Media Consumption and Political Trust in the EU: Evidence from the 94th Eurobarometer 2020/2021 Survey". It contains the following objects:</p> <p>1) R Script (as a markdown file).</p> <p>2) Raw dataset (copyright belongs to the European Union; the original source is the Eurobarometer website; https://europa.eu/eurobarometer/).</p>
The Impact of Website Design, E-Service Quality, Satisfaction, Trust to Intention to Purchase Skin Care Products in the E-Marketplace
<p><strong><span>The study aims to identify factors influencing pricing, understand how pricing affects purchase intention and customer satisfaction, and provide valuable insights for skincare businesses to develop effective pricing strategies in Indonesia’s skincare market. The study used a purposive sampling approach, collecting data from 123 respondents who were internet users in Indonesia in January 2024. These respondents have engaged with online retailers to purchase skin care products. The results found that website design affects e-service quality, affecting customer satisfaction and trust. Customer satisfaction and trust have a significant impact on repurchase intentions. This study recommends that skincare businesses focus on website design, provide high-quality e-services, and implement customer satisfaction and loyalty programs. Future research can explore additional factors and conduct similar studies in different locations or product categories.<span> </span></span></strong></p> <p><span>Keywords—Website design, skin care, e-marketplace, purchase intention, customer satisfaction, customer trust, e-service quality.</span></p>
D1.4 LITERATURE REVIEW ON SOCIAL NETWORK ANALYSIS RELATED TO TRUST IN SCIENCE
<p>This document constitutes a part of the D1.4 Social Network Analysis and includes the literature review that was conducted to investigate the methodologies used for addressing the topic of trust in science in Online Social Networks (OSNs). This review contains studies that have approached the topic of trust in science from different perspectives in OSNs examining both data from OSNs and suveys related to OSNs providing useful insights about the factors that influence public trust in science. Important findings are derived from the literature review that affect public’s trust in science, such as the political ideology, educational level, and cultural factors. Also, different methods of the studies are described such as the analysis of the text of the messages, the reactions of users, and deep learning techniques. The findings of the literature review are provided to the final document of D1.4 as they address the further analysis of the Task 1.4 Social Network Analysis</p>
Replication Package for "Trust Enhancement Issues in Program Repair"
<p>This is the replication artifact for our work on "Trust Enhancement Issues in Program Repair". The corresponding paper has been published at the International Conference of Software Engineering (ICSE) 2022, and is available under the following URL: <a href="https://doi.org/10.1145/3510003.3510040">https://doi.org/10.1145/3510003.3510040</a>. A pre-print of our work is available on arXiv: <a href="https://arxiv.org/pdf/2108.13064.pdf">https://arxiv.org/pdf/2108.13064.pdf</a>.</p> <p>The artifacts is organized in two parts:</p> <ol> <li>the artifacts for our <strong>developer survey</strong>, and</li> <li>the artifacts for our <strong>empirical assessment</strong> of state-of-the-art automated program repair (APR) techniques.</li> </ol> <p> </p> <p><strong>1. Survey Artifacts</strong></p> <p>The <code>survey</code> folder includes:</p> <ul> <li><code>Survey_Form.pdf</code> -- It shows the PDF version of the web form of our survey.</li> <li><code>Study_Results.pdf</code> -- It shows a summary of the questions and responses.</li> <li><code>Codebooks.xlsx</code> -- It shows all created codebooks.</li> <li><code>CodedResults.xlsx</code> -- It shows the responses for all questions, the corresponding coding, and statistics we applied during our analysis. Additionally, it includes plots for all responses and also the plots that are included in our paper.</li> </ul> <p> </p> <p><strong>2. Experiment Artifacts</strong></p> <p>The <code>experiments</code> folder includes:</p> <ul> <li><code>tools.md</code> -- It lists and describes the APR techniques that we used in our experiments.</li> <li><code>Results.xlsx</code> -- Contains the results of the experiments for each tool we considered, configuration details, and all the data from the ManyBugs benchmark.</li> <li><code>protocols/</code> -- This folder includes the analysis protocols, which describe for each tool "how" we extracted the values for our evaluation metrics (see Table 3 in our paper).</li> <li><code>results/</code> -- Contains the log files and relevant outputs for all tools and configurations. In particular, it includes the generated patches.</li> <li><code>subjects/</code> -- Contains the subjects taken from the <a href="https://repairbenchmarks.cs.umass.edu">ManyBugs</a> benchmark. For our experiments, we made some changes to the instrumentations, test-ids, etc. The file <code>meta-data.json</code> states the configurations, relevant test cases, etc.</li> <li><code>tool-snapshots/</code> -- Contains the snapshots for the tools, which we used in our evaluation.</li> </ul>
Data set supplementing "Determinants of Laypersons' Trust in Medical Decision Aids: Randomized Controlled Trial"
<p>This is the de-identified data set used to conduct the analyses in the preprint submitted to JMIR Human Factors under the title "Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial" (<a href="https://doi.org/10.2196/35219">https://doi.org/10.2196/35219</a>).</p> <p>This dataset contains 494 respondents' appraisals of a fictitious case vignette. They received support from a decision aid (that always disagreed with participants' first appraisal) showing a mock symptom checker logo, a decision aid framed as anthropomorphic or as an AI. Their second appraisal - taking into account the symptom checker advice - was collected again. </p> <p>Additionally, the data contains participants'</p> <ul> <li>age</li> <li>gender</li> <li>education</li> <li>medical training</li> <li>propensity to trust</li> <li>eHealth Literacy</li> <li>certainty in their appraisals</li> <li>trust in the decision aid</li> </ul>
TopicTracker keywords and MeSH terms resulting from the analysis of papers on autonomy, equity, privacy, proportionality and trust in the context of Covid-19
<p>This dataset contains normalized keywords and MeSH terms contained in articles retrieved with 5 separate querioes on Covid-19 and autonomy, equity, privacy, proportionality, trust.</p>
TopicTracker Medline files and query logs generated retrieving papers on autonomy, equity, privacy, proportionality and trust in the context of Covid-19
<p>To determine the core areas of discussion about the interplay between the Core Five and the Covid-19 pandemic, we ran a set of five queries in the TopicTracker. Each query collects articles regarding Covid-19 and one of the Core Five Enduring Values, published between January 2019 and March 2022.</p>
The moderator role of trust in the link between fear and knowledge-sharing intention
<p><strong>The moderator role of trust in the link between fear and knowledge-sharing intention</strong></p>
OA Book Usage Data Trust Business Model Canvas - 2023 Discussion Draft
<p>Despite the "Business Model Canvas" (BMC) monikor, this diagram presents sustainability-model elements related to a not-for-profit International Data Space focused on open access book usage data exchange. This diagram was inspired by an initial 2021 draft version created by Murphy et al (<a href="https://doi.org/10.5281/zenodo.6227423" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.6227423</a>) and includes information known in 2023 by OA Book Usage Data Trust project team members. The BMC diagram organizes and presents information about potential partners, activites, resources, value propositions, relationships, outreach, and users alongside anticipated costs and potential cost recovery mechanisms. </p> <p>This work was made possible through the "OAeBU Data Trust: Advancing to Launch by Developing IDS Governance Building Blocks" project grant funded by The Mellon Foundation.</p>
Dataset - Flux Profile Optimization of a High-Flux Solar Simulator Using the Trust-Region Reflective Method
<p>This dataset accompanies</p> <p>DOI: 10.1080/14786451.2024.2355651</p> <p>Title: Flux Profile Optimization of a High-Flux Solar Simulator Using the Trust-Region Reflective Method</p> <p>Authors: Mohammed Hamid Hussain</p> <p>Journal: International Journal of Sustainable Energy</p> <p> </p>
From Fear to Love: Dissecting Political Trust in China
<p>The data is about the paper "From Fear to Love: Dissecting Political Trust in China"</p>
Topic Guide Trust Study
Open the record for dataset details and reuse information.
Raw data_Effect of Security_Privacy and Customer Satisfaction on E Commerce Consumer Trust
Open the record for dataset details and reuse information.
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.