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452 results for “Usability”
Dataset: Relevance and usability evaluation in a data portal for biodiversity research
<p>Supplementary material for a relevance and usability evaluation in a data portal for biodiversity research.</p> <p>Data portal: GFBio (<a href="https://www.gfbio.org">https://www.gfbio.org</a>)</p> <p>Evaluation time:<span> February 2016 (at that time the search index consisted of ~ 2 Mio datasets)</span></p> <p>Eight domain experts rated the Top25 search results of 16 provided search questions on a 7-point-Likert scale from 0 (irrelevant) to 6 (highly relevant). Afterwards, we asked the users to provide and rate up to two own queries.</p> <p><span>The users also rated 28 statements in a subsequent usability evaluation on a 5-point Likert scale from 'completely disagree' to 'highly agree'. For some statements, only binary ratings were given.</span></p>
Securing Your Crypto-API Usage Through Tool Support - A Usability Study
<p>Developing secure software is essential for protecting passwords and other sensitive data. Despite the abundance of cryptographic libraries available to developers, prior work has shown that developers often unknowingly misuse the provided Application Programming Interfaces (APIs), resulting in serious security vulnerabilities. Eclipse CogniCrypt is an IDE plugin that aims at helping developers use cryptographic APIs more easily and securely by providing three main functionalities: (1) it provides a use-case oriented view of cryptographic APIs and guides the developer through their configuration, (2) it generates the code needed to accomplish the chosen use case based on the selected choices, and (3) it continuously analyzes the developer’s code to ensure that no API misuses are introduced later. However, so far the effectiveness of CogniCrypt was never empirically evaluated. In this work, we fill this gap through a controlled experiment with 24 Java developers. We evaluate the tool’s effectiveness in reducing API misuses and saving developer time. The results show that CogniCrypt significantly improves code security and also speeds up development for cryptograph-related tasks. The feedback received during the study suggests that developers particularly appreciate CogniCrypt’s code generation. Its static-analysis is valued for keeping the code up-to-date. Yet, the further integration of generated code into a developer’s project still presents a major challenge. Nonetheless, our results show that CogniCrypt effectively helps application developers produce more secure code.</p>
Data from: Barrier bednets target malaria vectors and expand the range of usable insecticides
<p>Transmission of <i>Plasmodium falciparum </i>malaria parasites occurs when nocturnal <i>Anopheles </i>mosquito vectors feed on human blood. In Africa, where malaria burden is greatest, bednets treated with pyrethroid insecticide were highly effective in preventing mosquito bites and reducing transmission, and essential to achieving unprecedented reductions in malaria until 2015. Since then, progress has stalled and with insecticidal bednets losing efficacy against pyrethroid-resistant <i>Anopheles</i> vectors, methods that restore performance are urgently needed to eliminate any risk of malaria returning to the levels seen prior to their widespread use throughout sub-Saharan Africa. Here we show that the primary malaria vector <i>Anopheles gambiae</i> is targeted and killed by small insecticidal net barriers positioned above a standard bednet, in a spatial region of high mosquito activity but zero contact with sleepers, opening the way for deploying many more insecticides on bednets than currently possible. Tested against wild pyrethroid-resistant <i>Anopheles gambiae </i>in Burkina Faso, pyrethroid bednets with organophosphate barriers achieved significantly higher killing rates than bednets alone. Treated barriers on untreated bednets were equally effective, without significant loss of personal protection. Mathematical modelling of transmission dynamics predicted reductions in clinical malaria incidence with barrier bednets that exceeded those of 'next-generation' nets recommended by WHO against resistant vectors. Mathematical models of mosquito-barrier interactions identified alternative barrier designs to increase performance. Barrier bednets that overcome insecticide resistance are feasible using existing insecticides and production technology, and early implementation of affordable vector control tools is a realistic prospect.</p>
Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool
<p>Vídeo de apresentação do artigo "Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool" para o 34° Simpósio Brasileiro de Engenharia de Software (SBES'20), 21-23 de Outubro de 2020, Natal, RN, Brasil. Autores: Leandro F. da Silva e Edson OliveiraJr.</p>
A comparative usability analysis of eye-tracking and mouse click data taken from digital libraries
<p>This dataset is the result of a study, in which we analyzed parallels and differences between clicks as well as eye movements on two different digital library homepages. For this analysis we used diverse tracking tools for mouse clicks and eye tracking data that where further studied with respect to specific areas of interest (AOI). </p> <p>The dataset contains two screenshots indicating the areas of interest (AOIs; entitled “AreasOfInterest_Kartenportal.jpg and AreasOfInterest_Webportal.jpg), which separate the homepages into analyzable parts. It also contains eight screenshots of the homepages containing the total amount of collected clicks (each name starting with “clicks”) and two screenshots with the eye tracking heat maps (starting with “Heatmap”). The screenshots have directly been extracted from the click and eye tracking tools and matched with the before mentioned AOIs in order to gain the total count of clicks and views as well as the view duration the concerned area.</p> <p>All data are synthesized in a document containing three sheets with different tables: a first one with the initial data compilation for all AOIs of the two analyzed homepages (entitled “Data”), a second one with a more visual compiled data analysis for both homepages and all AOIs (entitled “Data2) and last one with the duration of the view as well as the duration of the fixation and the compiled click data (entitled « Eye tracking study data »).</p>
A Survey on Usability Evaluation in Digital Health and Potential Efficiency Issues
<p><strong>A Survey on Usability Evaluation in Digital Health and Potential Efficiency Issues</strong> is a research study published at HEALTHINF24 that aimed to collect and analyse data from 144 usability experts on their experiences with usability evaluation of digital health applications.</p> <ol> <li>This file, "<strong>Usability Survey Paper Appendix A (Questionnaire)</strong>", contains the comprehensive set of questions and materials used in the usability survey discussed in the main paper. It serves as an essential resource for readers and researchers aiming to gain in-depth insights into the survey's questionnaire design, structure, and content. This appendix offers a detailed overview of the questionnaire, including the questions' wording, order, and categorizations, enabling an in-depth understanding of the survey's methodology and findings. <ul> <li>The survey had three different parts with a total of 19 questions including <ul> <li>1) the introductory and screening part,</li> <li>2) the demographic part,</li> <li>and 3) the main part asking usability-related questions (see survey questionnaires).</li> </ul> </li> <li>The questionnaire used in the study included both fixed-alternative questions (such as true/false, multiple choice, checkbox, and rating scale) and open-ended free-text responses. It incorporates an initial set of response options for the fixed-alternative questions, which were primarily derived from the relevant literature and grey literature. Almost every question included open-text fields to accommodate a broader range of responses, allowing participants to share answers not listed in the fixed alternative questions.</li> <li>The introductory and screening part includes survey information and screening them based on a non-leading mandatory screening question to determine whether volunteers meet the eligibility criteria. </li> <li>The demographic part consists of eight questions designed to know participants better regarding their demographics and previous experiences in assessing and ensuring the usability of digital health applications (see Part II of survey questionnaire). The questions asked participants about their gender, age, job position or title, and their experiences regarding evaluating the usability of applications in the digital health sector. They were also asked about the types of digital health systems/services/technologies they had evaluated for usability.</li> <li>The main part contains ten usability evaluation related questions, with one attention check question placed in the middle of the survey. This section focuses on usability evaluation tools, methods, and approaches to understand how usability experts assess and ensure the usability of digital healthcare software. Participants were also asked about the usability characteristics that are covered during the usability evaluation in digital healthcare. Furthermore, another sub-part of this section explores the benefits of using tools during usability evaluation, as well as the overall perceived benefits and challenges encountered during conducting usability evaluation of digital health apps.</li> </ul> </li> <li><strong>Appendix B</strong>, titled "<strong>Usability Survey Paper Appendix B (Detailed Results in Tabular Form)</strong>," provides an exhaustive compilation of the results obtained from the usability survey detailed in the main paper. The file contains organized, tabulated data offering insights into participants' responses, practices, and experiences. Each table is carefully structured to ensure clarity, making the data accessible and interpretable for subsequent analysis, review, and comparison.</li> <li>The <strong>quantitative dataset </strong>(filename: <strong>Usability Survey Paper Dataset.xlsx</strong>) includes the responses of usability experts to questionnaires about their demographics, experience with usability testing, and the frequency of use of different usability evaluation methods. This dataset also includes quantitative data on the ranking of the importance of different aspects of usability evaluation, such as ease of use, efficiency, and satisfaction. The qualitative dataset also includes the responses of usability experts to open-ended field of survey questions.</li> </ol>
Replication package - Potential Effectiveness and Efficiency Issues in Usability Evaluation within Digital Health: A Systematic Literature Review
<p>1. File: <strong>Maqbool_SLR_2023_JSS_Inclusion_610.xlsm.</strong></p> <p>There are two sheets in file. A. <strong>Final_Selected_papers</strong>, (sheet) aims to provide a comprehensive list of articles (n=610) selected for our SLR, whose process and data items specified and detailed in the article. </p> <p>B. <strong>Rejected_After_Full_Review</strong>, (sheet) aims to provide a comprehensive list of articles (n=153) rejected for our SLR based on inclusion or exclusion criteria after full article review process, whose process and data items specified and detailed in the article. </p> <p>2. File: <strong>Maqbool_SLR_2023_JSS_Data_Extraction_Form.pdf</strong></p> <p>This file aims to provide a comprehensive data extraction form, whose process and data items specified and detailed in the article. The form was used to elicit data relevant to answer the postulated research questions. This form served as the foundation for the additional information presented in the final paper.</p> <p>3. File: <strong>Bilal_SLR_JSS_Primary_Studies_References.pdf</strong></p> <p>This file contains the primary selected studies (n=610) for the systematic literature review. The systematic review aims to explore and analyse research literature related to usability evaluation methods and their effectiveness and efficiency in the context of digital health applications. This file will help to identity reference of the primary selected study that is cited in the paper using a prefix (S, e.g. S137). This file can be used for peer review, ensuring the reliability and correctness of findings.</p> <p>4. File: <strong>SLR_Analysis_updated_2023.nvp</strong></p> <p>The data extracted from each article was recorded in a worksheet (Excel) and then coded in NVivo 12/14 to categorise (classify) and compare extracted facets. Each data item's category and related paper id are coded in the given Excel file. Papers were not included in the NVivo project due to copyright concerns. Relevant papers can be tracked using the provided spreadsheet file (see Paper ID cell).<br>The file(s) are cleaned as much as reasonable and other raw data is removed. This file does not include the matrix tables or codes, which were produced and analysed run-time during the analysis phase. Although the given package allows for re-generation.</p> <p>-------- UPDATE: --------</p> <p>5. File: <strong>SLR_Analysis_updated_2023_for_MAC.nvpx</strong></p> <p>This is an extra copy of NVivo project, created for the MAC user.</p> <p> </p> <p>This replication package is produced and published here. Research conducted by Karlstad University researchers. We publish data sets to improve coverage and accessibility. For more info or concerns, contact us.</p> <p> </p> <p>Linked paper published at: Maqbool, Bilal, and Sebastian Herold. "Potential effectiveness and efficiency issues in usability evaluation within digital health: A systematic literature review." <em>Journal of Systems and Software</em> (2023): 111881.</p> <p>DOI: <a href="https://doi.org/10.1016/j.jss.2023.111881">https://doi.org/10.1016/j.jss.2023.111881</a><br> </p> <p>This work was funded, in parts, by Region Värmland through the DHINO project, Sweden (Grant: RUN/220266) and Vinnova through the DigitalWell Arena (DWA) project, Sweden (Grant: 2018-03025).</p>
US4USec: A User Story Model for Usable Security
<p>Excel sheet containing information used for the construction of the US4USec: A User Story Model for Usable Security </p>
Data for: Evaluation of Methods for Eliciting and Specifying Usability Requirements using User Stories: A Controlled Experiment
<p>Este projeto contém os materiais utilizados na pesquisa intitulada Evaluation of Methods for Eliciting and Specifying Usability Requirements using User Stories: A Controlled Experiment: TCLE, Formulário de Caracterização, Cenário, Oráculo, User Stories, Protótipo, Storyboards, Avaliação de ferramentas em escala de Likert e Dados coletados do formulário.</p>
A formative usability study of workflow management systems in label-free digital pathology - Data and Code
<p>This repository holds the necessary data and code as well as a descriptive Readme file that was used for our publication "A formative usability study of workflow management systems in label-free digital pathology" by Markus Jelonek et al. (2022), submitted to F1000Research.</p> <p> </p> <p>Abstract:</p> <p>We present a formative usability study that investigates the usability of different<br> workflow management systems in the field of biomedical data analysis. Specifically, we study a task in the field of so-called label-free digital pathology and investigate one graphical user interface based workflow and one script-based workflow to solve the task. Our main intention is to gain first insights into the systematic study of usability in the context of biomedical image analysis, and formulate experiences and guidelines for future usability studies dealing with workflow management systems. Embedded in a specific setup dealing with label-free digital pathology, the core question behind our contribution is how usability studies for scientific workflow management can be conducted, and how they can be used systematically to improve such tools. Further, we address specific questions about the resource utilisation and management of usability studies, including the recruitment of participants as well as the design of specific workflows to be investigated.</p>
A formative usability study of workflow management systems in label-free digital pathology - Questionnaires
<p>This repository holds the necessary questionnaires, participant data, interview questions and data, as well as a descriptive Readme file that was used for our publication "A formative usability study of workflow management systems in label-free digital pathology" by Markus Jelonek et al. (2022), submitted to F1000Research.</p> <p> </p> <p>Abstract:</p> <p>We present a formative usability study that investigates the usability of different<br> workflow management systems in the field of biomedical data analysis. Specifically, we study a task in the field of so-called label-free digital pathology and investigate one graphical user interface based workflow and one script-based workflow to solve the task. Our main intention is to gain first insights into the systematic study of usability in the context of biomedical image analysis, and formulate experiences and guidelines for future usability studies dealing with workflow management systems. Embedded in a specific setup dealing with label-free digital pathology, the core question behind our contribution is how usability studies for scientific workflow management can be conducted, and how they can be used systematically to improve such tools. Further, we address specific questions about the resource utilisation and management of usability studies, including the recruitment of participants as well as the design of specific workflows to be investigated.</p>
Data results of usability evaluation of a geo-temporal crowding visualization platform
<p>Data results of usability evaluation of a geo-temporal crowding visualization platform.</p> <p>NASA-TLX was used for assessing the cognitive load of performing one task with the platform.</p> <p>SUS and UEQ were used for asessing the usability of performing three tasks with the platform.</p>
Usability data (Drapebot Robot Cell/Dallara)
<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 Dallara, each participant was introduced to the robot work cell and received verbal instructions on how to perform the collaborative draping task. Each participant performed the task ten times. The ten tasks were performed with the same cut piece. Once the draping along the mould was complete, the participant would return the cut piece to the pick-up table before signaling the robot to continue by raising their hand (gesture condition). After 10 task repetitions, the participants filled out the questionnaire battery.</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 (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 (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 (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 (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>
Usable observations over Europe: Evaluation of compositing windows for landsat and sentinel-2 time series
<p>Landsat and Sentinel-2 data archives provide ever-increasing amounts of satellite data. However, the availability of usable observations greatly varies spatially and temporally. Pixel-based compositing that generates temporally equidistant cloud-free synthetic images can mitigate temporal variability, by constructing uninterrupted time series using different compositing windows. Here, we evaluated the feasibility of using compositing windows ranging from five days to one year for 1984-2021 Landsat and 2015-2021 Sentinel 2 time series to derive uninterrupted time series across Europe. We considered separate and joint use of both data archives and analyzed the spatio-temporal availability of composites during each calendar year and pixel-specific growing season across a variety of time windows and hypothesizing data interpolation. Our results demonstrated opportunities and limitations in the available data records to support medium- and long-term analyses requiring uninterrupted time series of composites with sub-annual temporal resolution. Spatial disparities across different compositing windows provide guidance on the feasibility of workflows relying on different data densities and on the challenges in wall-to-wall analyses. The feasibility of consistent time series based on composites with sub-monthly aggregation periods was mostly limited to the combined Landsat and Sentinel-2 archives after 2015, yet in some geographies requires interpolation of up to 50% of data.</p>
Improving the Usability of a MAS DSML
<p><strong>Improving the Usability of a MAS DSML</strong></p> <p>Tomás Miranda, Moharram Challenger, Baris Tezel, Omer Faruk Alaca, Vasco Amaral, Miguel Goulão, and Geylani Kardas</p> <p>Paper accepted for publication in the <a href="http://emas2018.dibris.unige.it/">6th International Workshop on Engineering Multi-Agent Systems (EMAS 2018)</a></p> <p> </p> <p><em><strong>Abstract </strong></em></p> <p><strong> Context: </strong>A significant effort has been devoted to the design and implementation of various domain-specific modeling languages (DSMLs) for the software agents domain.</p> <p><strong>Problem: </strong>Language usability is often tackled in an ad-hoc way, with the collection of anecdotal evidence supporting the process. However, usability plays an important role in the productivity, learnability and, ultimately, in the adoption of a MAS DSML by agent developers.</p> <p><strong>Method: </strong>In this paper, we apply the principles of The “Physics” of Notations (PoN) to improve the visual notation of a MAS DSML, called SEA_ML and evaluate the result in terms of usability.</p> <p><strong>Results: </strong>The evolved version of the language, SEA_ML++, was perceived as significantly improved in terms of icons comprehensibility, adequacy and usability, as a direct result of employing the principles of PoN. However, users were not significantly more efficient and effective with SEA_ML++, suggesting these two properties were not chiefly constrained by the identified shortcomings of the SEA_ML concrete syntax.</p> <p><em><strong>Study Participants</strong></em></p> <p><strong>Summary. </strong>This evaluation is comprised of a set of studies, each with its own subset of participants. No participants were involved in more than one study.</p> <ul> <li>Symbol selection study (25 participants)</li> <li>Concrete syntax evaluation experiment (24 + 12 participants)</li> </ul> <p><strong>Participants in the symbol selection study. </strong>The symbol selection experiment had 25 participants, 20 males, 5 females, all trained in Computer Science. Of these, 5 had completed their MSc, 16 their BSc and 4 were undergraduate Computer Science students at UNL. 11 had learned about MAS in the context of a course (although not using any of the particular languages in this experiment). The remaining 14 were not familiar with MAS. 9 participants had learned about the semantic web in the context of a course, 9 had only informal knowledge about it and the remaining 7 were not familiar with the semantic web.</p> <p>More details concerning the development of the SEA_ML++ version of SEA_ML can be found in: <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/SEA_MLPoN.pdf">SEA_MLPoN.pdf</a> .</p> <p><strong>Participants in the concrete syntax evaluation experiment. </strong>This evaluation experiment was run as a pair of replicated studies. The first replica was run in Universidade Nova de Lisboa, in Portugal. The second replica was run in the International Computer Institute, Ege University, Izmir, in Turkey.</p> <ul> <li><strong>UNL evaluation. </strong>At UNL we had 24 participants, including 19 males and 5 females, all trained in Computer Science. Of these, 8 have completed their MSc, 15 their BSc and 1 is an undergraduate Computer Science student. 12 of them had learned about MAS in the context of a course (although not using any of the particular languages in this experiment), and 1 had only informal knowledge about MAS. The remaining 11 were not familiar with MAS. 14 participants had learned about semantic web in the context of a course, 5 had informal knowledge about it, while 4 were not familiar with the semantic web. </li> <li><strong>EGE evaluation. </strong>At Ege University, we had 12 participants, all Computer Science graduate students who had learned about MAS in the context of a course.</li> </ul> <p> </p> <p><em><strong>Case studies</strong></em></p> <p><strong>Music Trader. </strong>In this case study, participants are requested to develop a system that allows agents to trade their music albums without using any currency. Agents want to trade their music albums for other albums, with this trade being made on an N to N basis (Agent A wants to trade the album A1 for the album B1 from Agent B and vice versa). Agents are not able to trade more than one album for only one album.)</p> <p><strong>Expert Finding. </strong>In this case study, participants are requested to develop a system that allows agents to find information about other agents that they are searching for in order to communicate with them. Agents have some information about the other agent they are looking for (they are family related or were friends at the past), which is crucial in order to find the correct SemanticWeb Service to search the right person. The communication between agents can be made through Social Networks, E-Mail, VoIP or Phone Call. This case study is an adaptation of the case study "Expert Finding" for an evaluation of SEA_ML.</p> <p><em><strong>Exercises</strong></em></p> <p>Each case study presents the participants with 2 different exercises (4 exercises in total). Each exercise has a description that defines all variables of the system to be modeled. For each exercise, an incomplete version of this system is presented. Participants should read the description that is provided to them and compare to the model they have in hands. When the participant thinks the model is according to the description, the exercise is complete, passing to an inquiry about the system they have modeled and afterward to the next exercise. Each exercise should take around 10 minutes to be completed. The total experiment should take around 40 minutes.</p> <p>A short description of each exercise is as follows:</p> <p>1. Music Trader: Exercise 1 — In this exercise, the participants will be modeling the M.A.S viewpoint. An environment and one customer are missing from the original model. A model is presented to the participant for this exercise (either in SEA_ML or in SEA_ML++).</p> <p>2. Music Trader: Exercise 2 — In this exercise, the participants will be modeling the Agent-SWS viewpoint. A SS_RegisterPlan is missing from the original model. A model is presented to the participant for this exercise (either in SEA_ML or in SEA_ML++).</p> <p>3. Expert Finding: Exercise 1 — In this exercise, the participants will be modeling the Agent Internal viewpoint. A goal, a belief and a behavior (and its respective connections) are missing from the original model. A model is presented to the participant for this exercise (either in SEA_ML or in SEA_ML++).</p> <p>4. Expert Finding: Exercise 2—In this exercise, the participants will be modeling the Ontology viewpoint. A fact and a semantic web organization are missing from the original model. A model is presented to the participant for this exercise (either in SEA_ML or in SEA_ML++).</p> <p> </p> <p><em><strong>How does the usage of SEA_ML vs SEA_ML++ affect the effectiveness and efficiency of developers?</strong></em></p> <p><strong>Summary. </strong>We briefly present the data analysis for comparing the effectiveness and efficiency of developers with the case studies, using SEA_ML and SEA_ML++. The data collection was performed in two replicate experiments: one conducted in Universidade Nova de Lisboa, the other in EGE University. The tasks and experimental design were identical and planned so that we are able to aggregate the results. In the end, we outline how the data collected in each of these replications compares with each other.</p> <p><strong>Descriptive statistics. </strong>We start by presenting the descriptive statistics for the correctness and duration of the task. The correction is measured as the percentage of elements correctly identified by participants in our case studies. The duration measures how long it took them to perform the task (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/CorrectnessEfficiencyDescriptives.pdf?versionId=9e46c43e-349f-4ec6-a97c-fa358cee72bf">CorrectnessEfficiencyDescriptives.pdf</a>). </p> <p><strong>Normality tests.</strong> We conducted a Kolmogorov-Smirnov and a Shapiro-Wilk tests to check for normality. Neither the correctness nor the duration have a normal distribution, p < 0.001 (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/CorrectnessEfficiencyNormality.pdf?versionId=f27fe63c-45c0-4e41-869d-f91af58bc97e">CorrectnessEfficiencyNormality.pdf</a>).</p> <p><strong>Hypothesis testing. </strong>Our null hypotheses are that:</p> <ul> <li>Using SEA_ML and SEA_ML++ has no impact in the correctness of the answers provided by our participants.</li> <li>Using SEA_ML and SEA_ML++ has no impact in the duration of the tasks performed by our participants.</li> </ul> <p>We summarize the main descriptive statistics here. We note a slight increase from .8021 to .8368 in the achieved correctness and a slight decrease in the mean time to complete the tasks, from 14m48s to 13m20s (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/CorrectnessEfficiencySummary.pdf?versionId=b1d2d603-74fe-4149-89e2-484efcdd6998">CorrectnessEfficiencySummary.pdf</a>).</p> <p>We can visually compare the distributions of correctness and duration, depending on the particular version of the language. Concerning correctness, as we can observe, the mode is 1.00 for both languages, although the distribution seems to be more skewed towards the highest rank. The values below 1.00 are considered extreme values, for SEA_ML++, meaning they are relatively scarce. It was relatively infrequent not to obtain maximum correctness with SEA_ML++ (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/CorrectnessBoxplot.pdf?versionId=2c15f46f-c02d-4a0a-8005-09734fe2f2af">CorrectnessBoxplot.pdf</a>).</p> <p>Concerning duration, the distributions are even more similar (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/EfficiencyBoxplot.pdf?versionId=f875ffcc-b6dc-4116-9d3e-839b3f1b8b09">EfficiencyBoxplot.pdf</a>). </p> <p>In order to assess whether there is any statistically significant difference between correctness using SEA_ML vs SEA_ML++ and between duration, again using SEA_ML vs SEA_ML++, we conducted a Welch T test, which is robust to deviations from normality, unequal sample sizes and does not assume equal variances of the compared variables (see <a href="https://zenodo.org/api/files/b8f7c0ab-6121-479c-b356-440ff1cde8e1/WelchTTestCorrectnessEfficiency.pdf?versionId=3caff774-4f6f-4395-81dc-37cd7b6f3be1">WelchTTestCorrectnessEfficiency.pdf</a>).</p> <p>The <em>correctness does not differ significantly</em>, according to Welch’s t-test, t(141.968) = .417, p=.519 from the SEA_ML (M = .80, SD = .32) to the SEA_ML++ (M = .84, SD = .32) concrete syntax. These results suggest that there was <em>no difference between the two concrete syntaxes, in terms of complexity</em>.</p> <p>The <em>duration does not differ significantly</em>, according to Welch’s t-test, t(122.030) = 1.180, p = .280 from the SEA_ML (M = 14 : 48, SD = 09 : 32) to SEA_ML++ (M = 13 : 20, SD = 06 : 12) concrete syntax. These results suggest that there was <em>no difference between the two concrete syntaxes, in terms of duration</em>.</p> <p><strong>Conclusions</strong></p> <p>The slight differences are not statistically significant. We found no evidence supporting the hypothesis that using SEA_ML++ instead of SEA_ML leads to more correct models. Likewise, we also did not find evidence supporting the hypothesis that using SEA_ML++ instead of SEA_ML will make practitioners reduce the duration of this task.</p> <p><strong>Acknowledgments</strong></p> <p>The authors would like to thank the followings:</p> <ul> <li>the Scientific and Technological Research Council of Turkey (TUBITAK) under grant 115E591</li> <li>Portuguese grants NOVA LINCS Research Laboratory (Grant: FCT/MCTES PEst UID/ CEC/04516/2013) and DSML4MA Project (Grant: FCT/MCTES TUBITAK/0008/2014)</li> </ul>
Automated Usability Evaluation of Augmented Reality Applications
<p>Research data for my master thesis on the topic: "Automated Usability Evaluation of Augmented<br> Reality Applications"</p>
Dataset for article: Gait Speed Assessment in the 10-meter Walk Test for Older Adults Using a Computer Vision-based System: A Cross-sectional Study on Validity, Reliability, and Usability
<p>This dataset provides the Validity, Reliability, and Usability for an assessment of gait speed detection system in the 10-meter Walk Test for Older Adults.</p> <p>The dataset is formatted for easy import into microsoft excel software consist of:<br>Supplementary1.xlsx - Validity <br>Supplementary2.xlsx - Reliability<br>Supplementary3.xlsx - Usability test</p>
Supplementary material for a usability evaluation of a semantic search for biological datasets
<p>We conducted a usability evaluation for a semantic dataset search with 20 biodiversity scholars in June and July 2022 in Germany.</p> <p>Following the TREC guidelines (https://www-nlpir.nist.gov/projects/t9i/spec.html), we setup eight user tasks and surveys with questionnaires to guide users through the evaluation. The zip file provides questionnaires, survey templates and the original results.</p> <p>A Jupyter notebook for data analysis is provided in our GitHub repository: <a href="https://github.com/fusion-jena/semantic-search-usability-analysis">https://github.com/fusion-jena/semantic-search-usability-analysis</a></p>
Usability results of the ENCORE database interface through the SUS questionnaire
<p>This repository contains the results derived from the analysis of the SUS questionnaire answers in regard to the ENCORE project's database management system interface.</p>
Experimental material of the article "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"
<p>Questionnaires, problems description and solution, and raw data of the paper "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"</p>
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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.