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452 results for “usability”
Data associated with the following publication: Developing the Playground Play Value and Usability Audit Tool (PVUA): An Evaluation of Content Validity via an Expert Panel
<p>This data set contains the supporting data associated with the following publication:</p> <p>Morgenthaler, T., Loebach, J., Lynch, H., Pentland, D., Kottorp, A., & Schulze, C. (in press). Developing the Playground Play Value and Usability Audit Tool (PVUA): An Evaluation of Content Validity via an Expert Panel. Children, Youth and Environments. [DOI was not yet available when the data set was published]</p> <p>The data set includes the following files:</p> <ul> <li>read me file [contains all relevant information to understand and reuse this data set] </li> <li>13 additional files [for description, see read me file]</li> </ul> <p>For more information, please contact the lead researcher, Thomas Morgenthaler (tom.morgenthaler@gmail.com or 121101888@umail.ucc.ie)</p> <p> </p>
User-centered Usability Analysis of 41 Open Government Data Portals
<p>The data were collected during the user-centered analysis of usability of 41 open government data portals including EU27, applying a common methodology to them, considering aspects such as specification of open data set, feedback and requests, further broken down into 14 sub-criteria. Each aspect was assessed using a three-level Likert scale (fulfilled - 3, partially fulfilled - 2, and unfulfilled – 1), that belongs to the acceptability tasks. This dataset summarises a total of 1640 protocols obtained during the analysis of the selected portals carried out by 40 participants, who were selected on a voluntary basis. This is complemented with 4 summaries of these protocols, which include calculated average scores by category, aspect and country. These data allow comparative analysis of the national open data portals, help to find the key challenges that can negatively impact users’ experience, and identifies portals that can be considered as an example for the less successful open data portals.</p>
An Integrated Usability Framework for Evaluating Open Government Data Portals and Analysis of EU and GCC OGD Portals
<p><span>This dataset contains data collected during a study (<em><strong>"<a href="https://arxiv.org/ftp/arxiv/papers/2403/2403.08451.pdf">An Integrated Usability Framework for Evaluating Open Government Data Portals: Comparative Analysis of EU and GCC Countries</a>"</strong></em>) conducted by Fillip Molodtsov and Anastasija Nikiforova (University of Tartu).</span></p> <p><span> </span><span>It being made public both to act as supplementary data for the paper and in order for other researchers to use these data in their own work potentially contributing to the improvement of current data ecosystems and develop user-friendly, collaborative, robust, and sustainable open data portals.</span></p> <p><span>***Purpose of the study***</span></p> <p><span>This paper develops an integrated framework for evaluating OGD portal effectiveness that accommodates user diversity (regardless of their data literacy and language), evaluates collaboration and participation, and the ability of users to explore and understand the data provided through them. </span></p> <p><span>The framework is validated by applying it to 33 national portals across European Union (EU) and Gulf Cooperation Council (GCC) countries, as a result of which we rank OGD portals, identify some good practices that lower-performing portals can learn from, and common shortcomings.</span></p> <p><span>***Methodology***</span></p> <p><span>(1) systematic literature review to establish a knowledge base and identify frameworks have been used to evaluate OGD portals, we conducted a systematic literature review - Dataset_ Usability_Framework_SLR;</span></p> <p><span>(2) development of the Integrated Usability Framework for Evaluating Open Government Data Portals, which content is based on the outputs of the first step, along with selected articles of experts in portal design, and an exploratory assessment of the French, Irish, Estonian and Spanish portals - Dataset_Integrated_Usability_Framework;</span></p> <p><span>(3) data collection, that is a completion of the protocol developed in the previous step by analysing 34 national OGD portals of the EU and GCC countries. When all individual protocols were collected, the total score are calculated using the weighting system. The average scores are calculated for the EU and GCC. The portals are ranked. The top portals (best performers) are determined for each dimension - Dataset_EU_GCC_OGDportal_Usability_results_clustering.</span></p> <p><span>(4) identification of relationships and patterns among different portals based on their performance metrics as a result of the cluster analysis. By calculating the average dimensional scores of portals from both types of clusters, their performance across multiple dimensions is evaluated - Dataset_EU_GCC_OGDportal_Usability_results_clustering.</span></p> <p> </p> <p><strong><em><span>For more details see Molodtsov, F., Nikiforova, A. (2024). “An Integrated Usability Framework for Evaluating Open Government Data Portals: Comparative Analysis of EU and GCC Countries”. In Proceedings of the 25th Annual International Conference on Digital Government Research (DGO 2024), June 11--14, 2024, Taipei, Taiwan, 10.1145/3657054.3657159</span></em></strong></p> <p><span>***Format of the file***</span></p> <p><span>.xls, .csv</span></p> <p><span>***Licenses or restrictions***</span></p> <p><span>CC-BY</span></p>
Experimental data for the study: "Naturalistic visualization of reaching movements using head-mounted displays improves movement quality and proves high usability compared to conventional computer screens"
<p>The datasets contains the motor performance metrics and the questionnaire responses for two experiments involving a motor task with a VR controller (experiment 1, healthy old participants) or a rehabilitation assistive device (experiment 2, brain-injured patients) and three visualization technologies: an immersive virtual reality (IVR) head-mounted display (HMD), an augmented reality (AR) HMD, and a computer screen (2D screen). The study was performed in the Motor Learning and Neurorehabilitation Laboratory at the University of Bern. All data are stored in “csv” files. The variables inside the files are explained in “DataFrameDescription.rtf”. For questions, please contact L.MarchalCrespo@tudelft.nl.</p>
Systematic Evaluation and Usability Analysis of Formal Tools for Railway System Design - Technical Annexes
<p>This package includes additional data for the paper ``Systematic Evaluation and Usability Analysis of Formal Methods Tools for Railway Signalig System Design'', by Alessio Ferrari, Franco Mazzanti, Davide Basile, and Maurice ter Beek, CNR-ISTI, Italy, accepted for publication in the IEEE Transactions on Software Engineering, DOI: 10.1109/TSE.2021.3124677</p> <p>The paper concerns the systematic evaluation and usability analysis of 14 formal tools for system design, namely CADP (2020-g), FDR4(4.2.7), NuSMV(1.1.1), ProB(1.9.3), Atelier B (4.5.1), Simulink (R2020a), SPIN (6.4.9), UMC (4.8), UPPAAL (4.1.4), mCLR2 (202006.0), SAL (3.3), TLA+ (2) and CPN Tools (4.0). The current package includes the following content:</p> <ol> <li>Tool Evaluation Template and .pdf: a document including the reference evaluation template, and the evaluation sheet of each tool. </li> <li>Tool Evaluation Table.xlsx: a table summarizing the results of the evaluation.</li> <li>System Usability Test - SUS Results.xlsx: an excel file with multiple sheets with all the raw results of the usability test for the tools.</li> </ol>
Usability of Open Data Portals
<p><span>This dataset reports on the usability of Open Data Portals as reported by the European public. Knowledge of open science and data concepts is also reported. </span></p>
ImUnipen image data set for writer identification (N=208) - vectorial handwriting converted to usable images
<p><br> ==============<br> Terms of Usage<br> ==============</p> <p>The ImUnipen data set is intended for non-commercial, scientific use,<br> and is distributed under auspices of the Unipen Foundation.</p> <p>Please always refer to the following paper in IEEE PAMI when using<br> the ImUnipen data set:</p> <p> Bulacu, M.; Schomaker, L.<br> Text-Independent Writer Identification and Verification<br> Using Textural and Allographic Features<br> Pattern Analysis and Machine Intelligence, IEEE Transactions on<br> Volume 29, Issue 4, April 2007 Page(s):701 - 717</p> <p>The ImUnipen data set is derived from the Unipen (unipen.org)<br> data set of on-line (i.e., vectorial, xy) handwriting.<br> The xy-coordinates and a line-generator algorithm are used<br> to generate a raster image, as if the data were optically scanned.</p> <p>Contents: for 208 writers, there are two PNG images per writer of<br> an artificially constructed table of naturally written words (49MByte).<br> These words are pasted onto a white page. For systematics reasons,<br> we call such a page a Paragraph, see below.</p> <p>The file names are organized as (example):</p> <p> Writ990221.Doc01.Par00.png<br> Writ990221.Doc01.Par01.png</p> <p> meaning: writer number 990221, document 01 (there exists only Doc01)<br> and the image with artificial "paragraph" of isolated words "Par00"<br> and "Par01".</p> <p>The Par00 and Pa01 images are typically used as the query<br> and best match in a leave-one-out setting for writer identification.<br> For instance, Par00 is the query, and Par01 is added to the total set<br> of all other images as the attractor for an identification search.</p> <p>For these experiments, word labels are not given in this data set,<br> on purpose, as the goal is to test recognition-free writer identification<br> methods.</p> <p>For a description of the regular<br> Unipen data set, please visit http://unipen.org</p> <p>Lambert Schomaker constructed this set in 2005</p>
Usability Testing Data for Web Application Prototype: Enhancing Efficiency and Transparency in Ghana's Rental Housing Market
<p><span>The dataset includes both quantitative and qualitative responses from participants who tested the web application prototype designed to enhance decision-making in Ghana's rental housing market. The testing focused on evaluating the user interface, ease of use, satisfaction levels, and the effectiveness of key functionalities.</span></p>
Usability Evaluation of the Agriculture Product Types Ontology (APTO)
<p><strong>Recommended citation</strong>:<br><br>Soares, F. M., Saraiva, A. M., Pires, L. F., Drucker, D. P., Braghetto, K. R., Santos, L. O. B. D. S., Moreira, D. D. A., Corrêa, F. E., & Delbem, A. C. B. (2025). A novel ux-based approach for ontology evaluation: Applying tree testing to the agricultural product types ontology. <em>IEEE Access</em>, 13, <a href="https://doi.org/10.1109/ACCESS.2025.3595447">https://doi.org/10.1109/ACCESS.2025.3595447</a><br><br>In evaluating the APTO ontology, we selected tree testing as the primary UX measuring protocol. We believe tree testing is particularly suitable for ontology evaluation as it combines various metrics, such as time on task and task success, to assess how users navigate and understand a hierarchy of concepts. This method allows us to trace user paths through the ontology's structure, identifying which aspects of the modeling may be confusing or inaccurate from the user's perspective. By analyzing these user interactions, we can gain valuable insights into how the ontology's design impacts usability, ultimately guiding improvements to better align with user needs.<br><br>Update in this version: images of pietrees.<br><br><br></p>
IIIF: raising awareness of the user benefits for scholarly editions - usability testing results
<p>Usability testing results of the bachelor's thesis titled <a href="https://doc.rero.ch/record/306498/"><em>"The International Image Interoperability Framework (IIIF): raising awareness of the user benefits for scholarly editions"</em></a><a href="https://doc.rero.ch/record/306498/">.</a></p> <p>Remote and in-person usability tests on the <a href="http://universalviewer.io/">Universal Viewer</a> and <a href="http://projectmirador.org/">Mirador</a>, two IIIF-compliant clients, took place between March and May 2017. The tests were conducted with Loop11 (remote testing) and Morae (in-person testing).</p> <p>The dataset is composed of Excel files, screenshots (tasks and heat maps) as well as videos.</p>
Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial'
<p>Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial' (trial registered at clinicaltrials.gov (<a href="https://clinicaltrials.gov/ct2/show/NCT04996654">NCT04996654</a>; date of registration: 11 July 2021), consisting of:</p> <p>(1) the original and complete data set for all primary outcomes ('Data_Primary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(2) the original and complete data set for all secondary outcomes ('Data_Secondary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(3) the original and complete data set for all other outcomes (i.e. baseline factors (demographic data, type of usual care interventions) and training heart rate; 'Data_Other-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(4) folder including the raw and processed heart rate variability (HRV) and electroencephalography (EEG) data for all participants and measurements (HRV-and-EEG_raw-and-processed-data.zip);</p> <p>(5) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.</p>
Data Extracted for the Systematic Literature Review on Non-profit Open data Intermediaries and their effects on Open data Usability Barriers
<p>The dataset contains the data extracted from the literature for the Systematic Literature Review and is referenced or used in the extended abstract titled "How do Non-profit Open data Intermediaries enhance Open data Usability? A Systematic Literature Review", submitted to the 18th International Symposium on Open Collaboration (Companion), September 6–10, 2022, Madrid, Spain. <a href="https://doi.org/10.1145/3555051.3555061" target="_blank" rel="noopener">https://doi.org/10.1145/3555051.3555061</a> </p>
Usability ratings on the MuLiMi platform expressed by Participants
<p>The database contains usability ratings for the MuLiMi platform for the screening of Dyslexia risk in multilingual children, expressed by the participants (children users). Ratings are expressed through an ad-hoc questionnaire with 12 items on a 1-to-5 point scale. NB ratings for question .1 are to be reversed in order to obtain a scale with increasing scores from the negative to the positive pole, like all other questions.</p>
usability ratings for the MuLiMi platform expressed by Examiners
<p>The database contains usability ratings for the MuLiMi web-platform for the screening of Dyslexia risk in multilingual children, expressed by Examiners on an ad-hoc Usability Questionnaire. Ratings for Questions 2 to 9 are expressed on a scale from 1 to 5, Questions from 10 to 46 are expressed on a scale from 1 to 9. NB ratings to Questions 2, 4, 7, 9 and 38 are to be reversed so as to obtain consistent ratings with increasing numbers correponding to increase from the negative to the positive pole. </p>
Evaluating the Usability of Open Source Frameworks in Energy System Modelling (Supplementary Material)
<p>Dataset and source code for analysis of the Energy System Modelling Usability Testing (ESMUT) procedure applied in the open_MODEX project.</p> <p>This is supplementary material for the publication:</p> <pre>Berendes et al. (2022). Evaluating the Usability of Open Source Frameworks in Energy System Modelling. <em>Renewable and Sustainable Energy Reviews. DOI: </em><a href="https://doi.org/10.1016/j.rser.2022.112174">https://doi.org/10.1016/j.rser.2022.112174</a></pre> <p> </p> <p> </p>
Assessing First Time Usability of a Hand Augmentation Device in a Large Sample of Diverse Users
<p>This upload provides additional information and data related to the paper "<span>Assessing First Time Usability of a Hand Augmentation Device in a Large Sample of Diverse Users</span>" (Clode et al., 2024).</p> <p>The study investigated users' first-time usage of the Third Thumb at "The Royal Society Summer Science Exhibition 2022", a large public engagement event held from July 6th to July 10th, 2022, at The Royal Society in London, England. The exhibition attracted more than 6,000 visitors.</p> <p>The Third Thumb is a supernumerary robotic finger. During the event, nearly 600 participants practiced using the Third Thumb in motor tasks aimed at different aspects of motor control. We examined how various demographic factors affected performance.</p>
Usability data (Drapebot Robot Cell/Profactor)
<p>In the Drapebot project, a worker collaborates with a large industrial manipulator in two tasks: collaborative transport of carbon fibre patches and collaborative draping.</p> <h3>Data collection</h3> <p>At the Profactor work cell the draping task was simulated with reusable cut pieces. The participant would occupy a safe zone outside the reach of the robot, when the robot was in motion. One task repetition consisted of the robot retrieving a large and narrow cut piece from a table and placing it on the mould, holding it at the seeding point. The participant would then approach the robot and perform the draping motions after which they retreated to the safe area of the HRC cell and signaled to proceed to the next repetition.</p> <p>At this test site each participant performed the task repeatably in two sessions where we compared two methods of signaling the robot. In the first session they repeated the task ten times, communicating to the robot to retrieve the next cut piece by stepping on a pedal in the safe area of the work cell (NoNUI condition). In the second session the participants performed five task repetitions, signaling the robot using a gesture input by reaching up towards the robot (Gesture condition).</p> <p>The usability questionnaires, SUS and UMUX, as well as trust questionnaires were administered after each session, after both gesture and non-NUI conditions. The NASA TLX and UTAUT were only administered once after both sessions were concluded.</p> <h3>Data organization</h3> <p>The data consists of an Excel file with six sheets:</p> <p>1. SUS: Results from Standard Usability Scale (Brooke et al. 1996)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, Gesture)</li> <li>Column 4-13: SUS items</li> <li>Column 14: SUS score between 1-100</li> </ul> <p>2. UMUX: Results from Usability Metric for User Experience (Finstad 2010)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, Gesture)</li> <li>Column 4-7: UMUX items</li> <li>Column 8: UMUX score between 1-100</li> </ul> <p>3. Trust: Results from Trust perception scale - HRI (Schaefer 2016)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, Gesture)</li> <li>Column 4-17: Questionnaire items</li> <li>Column 8: Trust score between 1-100</li> </ul> <p>4. Trust: Results from Trust in industrial human robot collaboration (Charalambous, et.al. 2016)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, Gesture)</li> <li>Column 4-13: Questionnaire items</li> <li>Column 8: Trust score between 1-100</li> </ul> <p>5. NASA TLX: Results from Task Load Index (Hart 1986)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3-20: Questionnaire items</li> <li>Column 21: TLX score between 1-100</li> </ul> <p>6. UTAUT: Results from Unified Theory of Acceptance and Use of Technology (Venkatesh et al. 2003)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3-33: Questionnaire items</li> <li>Column 34-41: Subcategory scores from 1-100</li> </ul> <h3>References:</h3> <p>J. Brooke et al., “Sus-a quick and dirty usability scale,” Usability evaluation in industry, vol. 189, no. 194, pp. 4–7, 1996</p> <p>G. Charalambous, S. Fletcher, and P. Webb, “The development of a scale to evaluate trust in industrial human-robot collaboration,” International Journal of Social Robotics, vol. 8, pp. 193–209, 2016.</p> <p>S. G. Hart, “Nasa task load index (tlx),” 1986.</p> <p>K. Finstad, “The usability metric for user experience,” Interacting with computers, vol. 22, no. 5, pp. 323–327, 2010</p> <p>K. E. Schaefer, Measuring Trust in Human Robot Interactions: Development of the “Trust Perception Scale-HRI”. Boston, MA: Springer US, 2016, pp. 191–218.</p> <p>V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS quarterly, pp. 425–478, 2003.</p> <p> </p>
Usability data (Drapebot Robot Cell/DLR)
<p>In the Drapebot project, a worker collaborates with a large industrial manipulator in two tasks: collaborative transport of carbon fibre patches and collaborative draping.</p> <h3>Data collection</h3> <p>At the DLR work cell one task repetition consisted of the robot retrieving a 30x30 cm cut piece from a table and placing it on the mould, holding it at the seeding point. The participant would then approach the robot from the safe zone and drape the cut piece on the mould, deforming it. When the participant had finished the draping, they retreated to the safe zone and signaled to proceed to the next repetition, and the robot retrieved the next cut piece. With 10 repetitions each piece was positioned and draped at different positions along the mould, starting at one end and evenly spread along the length of the mould.</p> <p>In the first session participants did the draping task ten times and signaled the robot by pressing a button mounted to their hip (NoNUI condition). In the second and third session they signaled the robot five times using one of two NUI in counter-balanced order (voice condition and gesture condition).</p> <p>The usability questionnaires, SUS and UMUX were administered after each session, the trust questionnaires only after the NoNUI condition. The NASA TLX and UTAUT were only administered once after both sessions were concluded.</p> <h3>Data organization</h3> <p>The data consists of an Excel file with six sheets:</p> <p>1. SUS: Results from Standard Usability Scale (Brooke et al. 1996)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, Voice, Gesture)</li> <li>Column 4-13: SUS items</li> <li>Column 14: SUS score between 1-100</li> </ul> <p>2. UMUX: Results from Usability Metric for User Experience (Finstad 2010)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI, , Voice, Gesture)</li> <li>Column 4-7: UMUX items</li> <li>Column 8: UMUX score between 1-100</li> </ul> <p>3. Trust: Results from Trust perception scale - HRI (Schaefer 2016)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI)</li> <li>Column 4-17: Questionnaire items</li> <li>Column 8: Trust score between 1-100</li> </ul> <p>4. Trust: Results from Trust in industrial human robot collaboration (Charalambous, et.al. 2016)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3: User interface type (NoNUI)</li> <li>Column 4-13: Questionnaire items</li> <li>Column 8: Trust score between 1-100</li> </ul> <p>5. NASA TLX: Results from Task Load Index (Hart 1986)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3-20: Questionnaire items</li> <li>Column 21: TLX score between 1-100</li> </ul> <p>6. UTAUT: Results from Unified Theory of Acceptance and Use of Technology (Venkatesh et al. 2003)</p> <ul> <li>Column 1: Test site</li> <li>Column 2: participant ID</li> <li>Column 3-33: Questionnaire items</li> <li>Column 34-41: Subcategory scores from 1-100</li> </ul> <h3>References:</h3> <p>J. Brooke et al., “Sus-a quick and dirty usability scale,” Usability evaluation in industry, vol. 189, no. 194, pp. 4–7, 1996</p> <p>G. Charalambous, S. Fletcher, and P. Webb, “The development of a scale to evaluate trust in industrial human-robot collaboration,” International Journal of Social Robotics, vol. 8, pp. 193–209, 2016.</p> <p>S. G. Hart, “Nasa task load index (tlx),” 1986.</p> <p>K. Finstad, “The usability metric for user experience,” Interacting with computers, vol. 22, no. 5, pp. 323–327, 2010</p> <p>K. E. Schaefer, Measuring Trust in Human Robot Interactions: Development of the “Trust Perception Scale-HRI”. Boston, MA: Springer US, 2016, pp. 191–218.</p> <p>V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS quarterly, pp. 425–478, 2003.</p>
User Experience Evaluation of BRI Smart Billing Mobile Application Using System Usability Scale and Heuristic Evaluation
<p>This research aims to evaluate user perceptions of the design and functionality of the BRI Smart Billing Mobile app. Through a questionnaire distributed to active BRI Smart Billing users, this study will identify factors that influence user satisfaction with the visual appearance, layout of elements, and ease of use of features available on the dashboard. The results of this research are expected to provide input to the application developers regarding efforts to improve the quality of digital application services and provide recommendations for improving the design of the BRI Smart Billing Mobile dashboard to be more user-friendly and meet user needs.</p>
Supplement to Creating Mobile Self-Triage Applications: Requirements and Usability Perspectives
<p>This is a supplement to our paper "Creating Mobile Self-Triage Applications: Requirements and Usability Perspectives", presented at the <strong>Second International Workshop on Requirements Engineering for Well-Being, Aging, and Health</strong> (REWBAH 2021, https://sites.google.com/view/rewbah2021) and published by IEEE CS.</p> <p>This zip file contains the email template used to invite participants, the consent letter, the pre-test interview, the protocol for the evaluator, the participant tasks, a questionnaire, and a description of three scenarios.</p> <p>Note that the Symptoms Pal application discussed in the paper was named <em>Symptom Checker Mobile</em> (SCM) at the time we performed the usability study.</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.