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19 results for “Empirical Research”
Cognition in Social Engineering Empirical Research: a Systematic Literature Review
<p># Description of contents</p> <p>This repository contains the codebook, dataset and analysis scripts in R used for the following publication: Pavlo Burda, Luca Allodi, Nicola Zannone. "Cognition in Social Engineering Empirical Research: a Systematic Literature Review". ACM Transactions on Computer-Human Interaction (TOCHI).<br> The repository consists of the following files:</p> <p>## dataset_and_codebook.xlsx contains the dataset, the codebook and a detailed description of contents.</p> <p>## scripts/ contains the R scripts used for the analysis</p> <p>## readme.txt contains this readme</p> <p><br> # Dataset and codebook</p> <p>The dataset_and_codebook.xlsx contains the following sheets:</p> <p>## Codebook<br> Contains a detailed description of the dataset (tables, columns, fields, etc.).<br> The codebook describes the concepts and variables that are present in the dataset. This includes explanations on meaning, numerical values, classification schemes and labels.</p> <p>## Hypotheses table <br> Contains the hypotheses for all analyzed papers and is used in the results of the paper. <br> Each row is a hypothesis of an included paper, cells contain one or more values (e.g., value1,value2,...) with or without sub values (e.g., value1,value2(sub-value1, ...)). Any content that is in square brackets [] is ignored in the analysis. Empty cells mean that there is no applicable value for that column.</p> <p>## Papers table<br> Contains the analyzed papers and is used in the results of the paper. It is also used in the overview table (Table 6) in Appendix C.<br> Each row is an included paper, cells contain up to two values (e.g., value1, value2) or the word 'multiple' in case of more than two values. Empty cells mean that there is no applicable value for that column.</p> <p>## Values table <br> Contains the description of cell values of 'Hypotheses' and 'Papers' and sub-values (specific variables in a study) that belong to a value. <br> It has a hierarchical structure from left to right where each field on the right column falls under the first non-empty field on the immediate left-top.</p> <p><br> # Reproducing results with scripts/ (generate figures)<br> To run the R scripts included in the 'scripts' directory it is sufficient to follow the instructions in and run the 'RUN_ALL_SCRIPTS.R' in 'scripts' directory.<br> The scripts use the TSV (Tab Separated Values) format of the dataset, which is the exact copy of the 'Papers' and 'Hypotheses' tables in the 'dataset_and_codebook.xlsx' file.<br> The resulting figures are stored in the 'scripts/results' directory.</p>
Research Artefact: An Empirical Study of React-Library Related Issues via Stack Overflow
<p>This research artifact accompanies the paper titled "An Empirical Study of React-Library Related Issues via Stack Overflow." It is a comprehensive repository that includes the collected dataset containing 447,542 React-related Stack Overflow question posts, as well as 384 representative samples obtained randomly. The primary objective of this artifact is to facilitate the replication of our dataset for researchers and allow them to utilize it for further investigations and research purposes.</p>
Solutions for Reproducibility in Empirical Research: Virtual Machines, Containers, Environment Management Packages, and Cloud Platforms
<p>This image provides a comprehensive overview of various technologies and platforms used to enhance the reproducibility of empirical research. It is divided into several sections:</p> <ol> <li><strong>Virtual Machines (VMs): </strong>the left section of the image illustrates the architecture of VMs with Type 1 and Type 2 hypervisors. <br> - <em>Type 1 Hypervisor </em>runs directly on the hardware, providing high efficiency and performance. Examples include VMware ESXi, <strong>Microsoft Hyper-v</strong>, and Xen Project.<br> - <em>Type 2 Hypervisor</em> runs on an existing operating system, offering flexibility at the cost of some performance. Examples include <strong>Oracle VirtualBox</strong>, VMware Workstation, and Parallels.</li> <li><strong>Containers: </strong>the middle section of the image explains the containerization concept, which shares the host operating system's kernel, making containers more lightweight than VMs. Technologies like <strong>Docker</strong> and <strong>Kubernetes</strong> are shown as popular solutions for container orchestration.</li> <li><strong>Environment Management Packages: </strong>the top right section focuses on tools for managing software dependencies and environments. <strong>renv</strong> (for R) and <strong>Conda</strong> (for Python and other languages) are highlighted as key tools for creating reproducible research environments.</li> <li>Cloud Platforms: the bottom right section features various cloud-based platforms that facilitate reproducible research by providing scalable and shareable computational environments. Platforms include <strong>Google Colab</strong>, <strong>Posit Cloud</strong>, JupyterHub, <strong>Binder</strong>, Nextjournal, OpenShift, and <strong>Code Ocean</strong>.</li> </ol> <p>Together, these solutions provide a robust framework for ensuring that empirical research can be reliably reproduced and validated by others, addressing the challenges of dependency management, environment consistency, and computational resource availability.</p>
Replication package for "Evolution of statistical analysis in empirical software engineering research: Current state and steps forward"
<p>This is the replication package for the analysis done in the paper "Evolution of statistical analysis in empirical software engineering research: Current state and steps forward" (DOI: <a href="https://doi.org/10.1016/j.jss.2019.07.002">https://doi.org/10.1016/j.jss.2019.07.002</a>, preprint: <a href="https://arxiv.org/abs/1706.00933">https://arxiv.org/abs/1706.00933</a>).</p> <p>The package includes CSV files with data on statistical usage extracted from 5 journals in SE (EMSE, IST, JSS, TOSEM, TSE). The data was extracted from papers between 2001 - 2015. The package also contains forms, scripts and figures (generated using the scripts) used in the paper.</p> <p>The extraction tool mentioned in the paper is available in dockerhub via: <a href="https://hub.docker.com/r/robertfeldt/sept">https://hub.docker.com/r/robertfeldt/sept</a></p>
Empirical Research on Requirements Quality: A Systematic Mapping Study - Dataset
<p>We conducted a systematic mapping study on the empirical research into the quality of requirements titled "Empirical Research on Requirements Quality: A SystematicMapping Study" in the Requirements Engineering Journal. This is our replication package.</p> <p>Full Abstract:</p> <p>Research has repeatedly shown that high quality requirements are essential for the success of development projects. While the term “quality” is pervasive in the field of requirements engineering and while the body of research on requirements quality is large, there is no meta study of the field that overviews and compares the concrete quality attributes addressed by the community. To fill this knowledge gap, we conducted a systematic mapping study of the scientific literature. We retrieved 6,905 articles from six academic databases, which we filtered down to our 105 relevant primary studies: explicitly defining, improving, or evaluating quality attributes while including an empirical research component. We found that research on requirements quality focuses on improvement techniques, with very few primary studies addressing evidence-based definitions and evaluations of quality attributes. Among the 12 quality attributes identified, the most prominent in the field are ambiguity, completeness, consistency, and correctness. We identified 111 sub-types of quality attributes such as “template conformance” for consistency or “passive voice” for ambiguity. Ambiguity has the largest share of these sub-types. The artefacts being studied are mostly referred to in the broadest sense as “requirements,” while little research targets quality attributes in specific types of requirements such as use cases or user stories. We present and discuss our detailed analysis along the various quality attributes. Our findings highlightthe need to conduct more grounded research aimed at “definitions,” to use more diverse research methods, and to address a more diverse set of requirements types.</p>
The dataset for the research "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
In recent years, the topic of digitalisation and sustainability of supply chains has become increasingly important. In addition, as the environmental dynamism becomes more complex, it is essential to explore how technologies impacts on sustainability under the supply chain dynamism. Hence, there is a study to explore the relationship between technologies and sustainability under the supply chain dynamism in the energy supply chain. In this study, the author collects quantitative data from two Chinese companies, including China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd. This is a questionnaire survey and it has 24 questions, including 3 general questions, 5 technologies dimension questions, 12 sustainability dimension questions and 4 supply chain dynamism questions. The author collected data from 30 May 2024 to 6 June May 2024, and there are totally 316 answers.
The dataset of "Evaluation of Digital Supply Chain Technology's Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
<p>This dataset involves the data from the questionnaire, which come from the project "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain". It comprises three dimensions questions, technology, sustainability and supply chain dynamism. The datas come from two Chinese energy firms, <span>China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd.</span></p>
Empirical research in software architecture - perceptions of the community (supplementary material)
<p>This repository contains supplementary material for the manuscript "Empirical research in software architecture - perceptions of the community" published in the Journal of Systems and Software (<a href="https://doi.org/10.1016/j.jss.2023.111684">https://doi.org/10.1016/j.jss.2023.111684</a>):</p> <ul> <li>ICSA_papers.xlsx: This file contains the papers published at ICSA 2017-2021.</li> <li>invited_PC_members.xlsx: This file contains all names of PC members of ECSA, ICSA, QoSA, CBSE and WICSA for all instances of these conferences. This information was collected in June 2017 from the publicly available websites of these conferences as well as the publicly available online profiles of PC members.</li> <li>protocol.pdf: This files contains a summary of the survey protocol.</li> <li>responses.xls: This file contains all the responses of the survey from all respondents for all questions.</li> </ul>
Data from: Relational values of nature in empirical research: A systematic review
<p>In the past five years, scholarly and policy attention to relational values, a concept that articulates plural values of nature, has grown steadily. To date, there are no published syntheses of empirical research that explicitly address relational values. We perform a systematic literature review of n = 72 empirical studies of relational values to summarize the state of current research and to identify opportunities for future research and conceptual development. In our analysis, we categorize what authors identify as relational values and summarize study characteristics (e.g., study location, methods approach.) Authors collectively report n = 312 unique relational values. Categories of <em>identity, social cohesion, livelihoods, connection to place/human-nature connection</em>, and <em>religion</em> are most common. Scholarship that explicitly addresses relational values has increased since 2017 and exhibits substantial diversity: in how relational values are conceptualized (or not); in disciplinary associations; in geographical location; and in data collection methods. We find that most empirical research on relational values does not justify how its results reflect characteristics that establish the relational values concept as unique from other environmental values concepts. As a result, diverse interpretations of the relational values concept pose the risk of the relational values concept being so broad and inclusive that it becomes meaningless, or at least meaning-light.</p>
Data from: Relational values of nature in empirical research: A systematic review
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Dataset of Empirical MOOC Research 2016 - 2017
<p>Dataset of Empirical MOOC Research 2016 - 2018 </p>
CARPE Database of Empirical Research on Assessment for the Leaving Certificate in Ireland (May 2024)
<p>This is the download site for the <strong>CARPE Database of Empirical Research on Leaving Certificate Assessment in Ireland (May 2024). </strong>We hope that this database will act as a guide and resource for any future research regarding the Leaving Certificate and the assessment methods used therein. If you do use this database as a reference or tool, please cite it as:</p> <p>Lehane, P., O'Connor, G. & O'Leary, M. (2024). <em>CARPE Database of Empirical Research on Leaving Certificate Assessment in Ireland </em>[Database]. Dublin City University. </p> <p>We realise that there are current and future studies that should be included in this database now and in the years to come. We intend on updating this database on an annual basis with missing or new studies. If you wish to suggest an empirical study that could be added to this database, please fill in the relevant details on this <a href="https://forms.gle/ggi53t1psYXJXqi77">Google Form</a>. </p>
Research data for "A machine-learned interatomic potential for silica and its relation to empirical models"
<p>This dataset supports the paper "A machine-learned interatomic potential for silica and its relation to empirical models". The paper is online here:</p> <p>The following files are provided:</p> <ul> <li>xyz-file containing all structures in the training database including forces and energies</li> <li>GAP file containing the corresponding parameters, which can be used for example for Lammps MD simulations</li> <li>Amorphous structure files for silica created by different interatomic potentials.</li> </ul>
Dataset for How open is innovation research?–An empirical analysis of data sharing among innovation scholars
<p>This dataset comprises responses from 241 innovation researchers on their personal data sharing behavior as well as their perceptions of and attitudes towards open research data. This dataset is the supplementary material to Barczak et al. (2021) (<a href="https://doi.org/10.1080/13662716.2021.1967727" target="_blank" rel="noopener">https://doi.org/10.1080/13662716.2021.1967727</a>).</p>
Clinical Empirical Research of ARDS
ClinicalTrials.gov study NCT05922826. IPD Sharing: NO. Countries: 1. Publications: 1.
The Model Building and Empirical Research of Eye Health Interventions for Children
ClinicalTrials.gov study NCT02903628. IPD Sharing: UNDECIDED. Countries: 0. Publications: 5.
Construction and Empirical Research of the Applicable Baduanjin Protocol for Patients With Colorectal Cancer Enterostomy
ClinicalTrials.gov study NCT07172087. IPD Sharing: NO. Countries: 1. Publications: 0.
Research on the impact of the digital economy on narrowing the gap between urban and rural areas—An empirical analysis based on provincial panel data
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Replication Package for the Paper:Empirical Research on Secure Development in Agile Methods: A Systematic Literature Review
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.