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57 results for “empirical study data”
Data for "On the Practice of Semantic Versioning for Ansible Galaxy Roles: An Empirical Study and a Change Classification Model"
<p>This dataset accompanies a replication package provided for a study on Semantic Versioning for Ansible Galaxy roles.</p> <p>The replication package is available at https://github.com/ROpdebee/ansible_semver_ext_replication</p>
An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data)
<p>Dataset with the container image metadata used for our IEEE/ACM CCGRID 2023 paper "An Empirical Study of Container Image Configurations and Their Impact on Start Times".</p> <p>Abstract of the paper: A core selling point of application containers is their fast start times compared to other virtualization approaches like virtual machines. Predictable and fast container start times are crucial for improving and guaranteeing the performance of containerized cloud, serverless, and edge applications. While previous work has investigated container starts, there remains a lack of understanding of how start times may vary across container configurations. We address this shortcoming by presenting and analyzing a dataset of approximately 200,000 open-source Docker Hub images featuring different image configurations (e.g., image size and exposed ports). Leveraging this dataset, we investigate the start times of containers in two environments and identify the most influential features. Our experiments show that container start times can vary between hundreds of milliseconds and tens of seconds in the same environment. Moreover, we conclude that no single dominant configuration feature determines a container's start time and that hardware and software parameters must be considered together for an accurate assessment.</p> <p>Dataset description: Our images dataset contains 200,986 entries with 21 features associated to each container image. In the following, we describe the meaning of each feature. Further information is available in <a href="https://github.com/opencontainers/image-spec">OCI Image Specification</a> and the <a href="https://docs.docker.com/engine/reference/run/">Docker Run Documentation</a>. Besides the 20 features grouped in the five categories below, each dataset entry has a image_id, which is used to uniquely identify the dataset entry.</p> <p>Features</p> <p>Metadata features (prefix: meta)</p> <ul> <li><strong>meta_repo_digest</strong> : The repo digest is a SHA-256 hash which is used to uniquely identify and pull the image from Docker Hub</li> <li><strong>meta_architecture</strong> : The CPU architecture which the binaries in the image are built to run on</li> <li><strong>meta_os</strong> : The name of the operating system which the image is built to run on</li> <li><strong>meta_docker_version</strong> : The Docker version used to built this image</li> </ul> <p>I/O stream features (prefix: io)</p> <ul> <li><strong>io_attach_stdin</strong> : boolean setting to determine whether the console should be attached to the process stdin stream</li> <li><strong>io_attach_stdout</strong> : boolean setting to determine whether the console should be attached to the process stdout stream</li> <li><strong>io_attach_stderr</strong> : boolean setting to determine whether the console should be attached to the process stderr stream</li> <li><strong>io_tty</strong> : boolean setting to determine whether the console should pretend to be a TTY when attached</li> <li><strong>io_open_std_in</strong> : boolean setting to determine whether the process stdin stream should be kept open even if console not attached</li> <li><strong>io_std_in_once</strong> : boolean setting to determine whether the process retrieved input from the stdin stream at least once</li> </ul> <p>Start command features (prefix: cmd)</p> <ul> <li><strong>cmd_args</strong> : Length of list of arguments to use as the command to execute when the container starts</li> <li><strong>cmd_envvars</strong> : Environment variables set per default when the container starts</li> <li><strong>cmd_additional_args</strong> : Length of list for additional arguments to the containers entrypoint</li> </ul> <p>File system features (prefix: fs)</p> <ul> <li><strong>fs_volumes</strong> : Number of volumes to create/use by default</li> <li><strong>fs_size</strong> : Size of this image in bytes</li> <li><strong>fs_virtual_size</strong> : Virtual size of this image in bytes (equals size)</li> <li><strong>fs_graph_driver_name</strong> : Name of the image's graph driver</li> <li><strong>fs_root_fs_type</strong> : Name of the file system type used in the image</li> <li><strong>fs_layers</strong> : Number of root file system layers</li> </ul> <p>Networking features (prefix: net)</p> <ul> <li><strong>net_ports</strong> : Number of ports to expose per default</li> </ul> <p> </p> <p>Dataset acquisition: The dataset has been acquired from Docker Hub using a web crawler. We used substring matches with the <a href="https://hub.docker.com/explore">Docker Hub Explore function</a>. As search strings, we used all letter combination with sizes 1 to 3, meaning that our first search string was 'a' and our last was 'zzz'. We included both results from the 'recently updated' and the 'most popular' selection. We came up with an initial list of 286,294 image names. We then tested we could pull and start these images once. These tests have been conducted from April to June 2022. We sorted out all images that were either not pullable or startable and retrieved all total of 200,986 valid images. In the following, we describe the error types that we encountered and that let to the removal of the causing image from the dataset:</p> <ul> <li>The image manifest was unknown when we tried to download it meaning that is has been renamed or deleted from the time when our web crawler was running</li> <li>The entrypoint command required a dependency that was missing in the image and therefore the container could not be started</li> <li>The image did not specify an entrypoint command and could therefore not be started</li> <li>The image declared an invalid root file system type</li> <li>The image had a malformed root file system</li> <li>The image configuration was incomplete and therefore not all required data could be obtained</li> </ul> <p>See also our CodeOcean capsule with the processing scripts for our paper: https://doi.org/10.24433/CO.4595026.v2</p>
Data for empirical example in: An effect size for comparing the strength of morphological integration across studies
<p>Understanding how and why phenotypic traits covary is a major interest in evolutionary biology. Biologists have long sought to characterize the extent of morphological integration in organisms, but comparing levels of integration for a set of traits across taxa has been hampered by the lack of a reliable summary measure and testing procedure. Here we propose a standardized effect size for this purpose, calculated from the relative eigenvalue variance, Vrel. First we evaluate several eigenvalue dispersion indices under various conditions, and show that only Vrel remains stable across samples size and the number of variables. We then demonstrate that Vrel accurately characterizes input patterns of covariation, so long as redundant dimensions are excluded from the calculations. However, we also show that the variance of the sampling distribution of Vrel depends on input levels of trait covariation, making Vrel unsuitable for direct comparisons. As a solution, we propose transforming Vrel to a standardized effect size (Z-score) for representing the magnitude of integration for a set of traits. We also propose a two-sample test for comparing the strength of integration between taxa, and show that this test displays appropriate statistical properties. We provide software for implementing the procedure, and an empirical example illustrates its use.</p>
Data from an empirical study on generative artificial intelligence painting
<p>This is an empirical study on generative artificial intelligence painting, including research methods, basic data of 17 subjects and their AI art painting, and quantitative data after their data analysis.</p>
Data for empirical example in: An effect size for comparing the strength of morphological integration across studies
Open the record for dataset details and reuse information.
Data in the analysis of Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective
<p>This data is used in the analysis related to the article Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective. The data contain Crude Oil Prices, Exchange Rates, and Dummy variables coded 1 for the era before the Covid-19 outbreak and 0 for the era of Covid-19.</p> <p> </p>
Data for: Evolution Reinforces Cooperation with the Emergence of Self-Recognition Mechanisms: an empirical study of the Moran process for the iterated Prisoner's dilemma using reinforcement learning
<p>This contains data used for a paper titled: Evolution Reinforces Cooperation with the Emergence of Self-Recognition Mechanisms: an empirical study of the Moran process for the iterated Prisoner's dilemma using reinforcement learning.</p> <p>Numerous data sets are included, the main being `main.csv` which includes the fixation counts for a number of Moran processes between pairs of players from the Axelrod library.</p> <p>The source code and explanation of the data is here: https://github.com/Axelrod-Python/axelrod-moran. </p> <p> </p>
Raw Coding Data for "Insights for Improving Diagram Editing Gained from an Empirical Study"
<p>This MaxQDA Exchange file contains the raw coding data for "Insights for Improving Diagram Editing Gained from an Empirical Study"</p>
Data of the Paper "How to Communicate when Submitting Patches: an Empirical Study of the Linux Kernel"
<p>This repository includes the data of the paper "How to Communicate when Submitting Patches: an Empirical Study of the Linux Kernel".</p> <p>It contains three parts:</p> <ol> <li>Related online documents.</li> <li>Original questionnaire of the survey.</li> <li>Survey results.</li> </ol> <p> </p>
Data Science Tasks used in "AI Support for Data Scientists: An Empirical Study on Workflow and Alternative Code Recommendation"
<p>This entry contains the supplementary files for a scientific article. </p> <p>The dataset contains the necessary files for the two data science tasks used in the experiment study from scientific article "AI Support for Data Scientists: An Empirical Study on Workflow and Alternative Code Recommendation"</p> <p> </p>
Data from: Behavioral thermoregulation of caterpillars is altered by temperature, but not parasitism: an empirical field study
<p>Laboratory assays show that parasites often have lower heat tolerance than their hosts. But how physiological tolerances and behavioral responses of hosts and parasites combine to affect their ecological interactions in heterogeneous field environments is largely unknown. We addressed this challenge using the model insect system of the braconid wasp parasitoid, <em>Cotesia congregata</em>, and its caterpillar host, <em>Manduca sexta</em>. We used experimental manipulations of microclimate in the field to determine how elevated daytime temperatures altered the behavior, performance, and survival of the host and parasite. Our experimental manipulation increased daily maximum temperatures on host plants, but had negligible effects on overall mean temperature. These increased maximum temperatures resulted in subtle, biologically relevant, changes in physiology and behavior of the host and parasitoid. We found that parasitism by the wasp did not significantly alter caterpillar thermoregulatory behavior, while experimentally increased daily maximum temperatures resulted in both parasitized and unparasitized caterpillars being found more frequently in cooler microhabitats. Overall, we did not observe the complete parasitoid mortality seen at extreme temperatures in laboratory studies, but gained insight into sublethal effects of increased daily maximum temperatures on host and parasitoid behavior and physiology. Climate change will alter both the biotic and abiotic environments that organisms face, and we show here that empirical experiments in the field are important for understanding organismal response to these new environments. </p>
Data for study "Digital tools for innovative higher education teaching - a Scoping Review of Empirical Studies".
<p>The goal of this research is to point out, by a scoping review of the papers published between 2020 and 2023, the digital tools used in the teaching process at the higher education level. The dataset was collected using Web of Science and Scopus databases.</p> <p>The dataset contains the following elements:</p> <ol> <li>paper details (Authors, Publication Year, Article Title, DOI),</li> <li>OECD classification,</li> <li>teaching tool assigned to paper.</li> </ol>
Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories"
<p>Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories", published in Information and Software Technology, Volume 164, December 2023. DOI: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.infsof.2023.107318" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.infsof.2023.107318</span></span></a></p>
Data from: implications of methodologies for integrating empirical kinships into ex situ population management using PMx: a case study of Baer’s Pochard (Aythya baeri) in North America
Open the record for dataset details and reuse information.
Data from: Behavioral thermoregulation of caterpillars is altered by temperature, but not parasitism: an empirical field study
Open the record for dataset details and reuse information.
Data - An Empirical Study of Method Chaining in Java
<p><strong>THERE ARE PROBLEMS WITH THIS DATASET. SEE <a href="https://tomokinakamaru.github.io/msr2020/">HERE</a> FOR MORE INFORMATION.</strong></p> <p>The collected method chains and the results of our manual inspections presented in "An Empirical Study of Method Chaining in Java.", which will be published in MSR 2020. The archive file contains the following materials:</p> <ul> <li><code>data.txt</code>: List of all the collected chains</li> <li><code>metadata.txt</code>: List of files and the number of lines for each file</li> <li><code>rq1_{short,long,extlong}_201{0,8}.md</code>: Sampled chains for RQ1</li> <li><code>rq1_201{0,8}.csv</code>: Result of our manual inspections in RQ1</li> <li><code>rq2.md</code>: Sampled chains for RQ2</li> <li><code>rq2.csv</code>: Result of our manual inspections in RQ2</li> </ul>
A Large-scale Data Set and an Empirical Study of Docker Images Hosted on Docker Hub
<p>The data set schema, fields description, and analysis scripts are in the GitHub artifact repository.</p> <p>https://github.com/linncy/icsme2020-docker-study</p> <p> </p> <p>@inproceedings{LinICSME20,<br>author={Changyuan Lin and Sarah Nadi and Hamzeh Khazaei},<br>title={A Large-scale Data Set and an Empirical Study of Docker Images Hosted on Docker Hub},<br>booktitle={Proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME)},<br>year={2020},<br>url_Paper={https://www.dropbox.com/s/3bktcmdr7rlw1ic/LinICSME20.pdf}<br>}</p>
Data from: Finding clarity in ecological outcomes using empirical integrated social-ecological systems: a case study of agriculture-dependent grassland birds
<p>1. Efforts to monitor and conserve populations and ecosystems in human-dominated landscapes can benefit from an empirical social-ecological systems approach.<br> 2. Here we illustrate how latent variable structural equation modelling of regional time series data can effectively describe interconnected drivers of population fluctuations in dynamic landscapes and can help to reveal previously unknown system drivers.<br> 3. Using a declining farmland-dependent bird species (Ammodramus savannarum) in the eastern United States (1994-2015) as a case study, our analysis reveals how farm management decisions drive population fluctuations (R<sup>2</sup> = 20%), while management is in turn highly influenced by climate (R<sup>2</sup> = 23-51%), but not by regional conservation spending.<br> 4. Synthesis and applications. Structural equation modelling revealed potential social-ecological pathways for halting regional population declines in a grassland bird, the Grasshopper Sparrow. Lower population growth rates followed years of higher hay yields (~4 percentage points per metric ton increase in hay yield) and later harvests (~2 percentage points per 10-day delay in harvest). Thus, one pathway for stabilising regional populations could involve compensating farmers for reducing hay harvests, potentially requiring a six-fold increase in current annual agri-environmental conservation spending.</p>
Data for: Gene tree estimation error with ultraconserved elements: An empirical study on Pseudapis bees
<p>Summarizing individual gene trees to species phylogenies using two-step coalescent methods is now a standard strategy in the field of phylogenomics. However, practical implementations of summary methods suffer from gene tree estimation error, which is caused by various biological and analytical factors. Greatly understudied is the choice of gene tree inference method and downstream effects on species tree estimation for empirical data sets. To better understand the impact of this method choice on gene and species tree accuracy, we compare gene trees estimated through four widely used programs under different model-selection criteria: PhyloBayes, MrBayes, IQ-Tree and RAxML. We study their performance in the phylogenomic framework of > 800 ultraconserved elements from the bee subfamily Nomiinae (Halictidae). Our taxon sampling focuses on the genus <i>Pseudapis</i>, a distinct lineage with diverse morphological features, but contentious morphology-based taxonomic classifications and no molecular phylogenetic guidance. We approximate topological accuracy of gene trees by assessing their ability to recover two uncontroversial, monophyletic groups, and compare branch lengths of individual trees using the stemminess metric (the relative length of internal branches). We further examine different strategies of removing uninformative loci and the collapsing of weakly supported nodes into polytomies. We then summarize gene trees with ASTRAL and compare resulting species phylogenies, including comparisons to concatenation-based estimates. Gene trees obtained with the reversible jump model search in MrBayes were most concordant on average and all Bayesian methods yielded gene trees with better stemminess values. The only gene tree estimation approach whose ASTRAL summary trees consistently produced the most likely correct topology, however, was IQ-Tree with automated model designation (MFP). We discuss these findings and provide practical advice on gene tree estimation for summary methods. Lastly, we establish the first phylogeny-informed classification for <i>Pseudapis</i> s. l. and map the distribution of distinct morphological features of the group.</p>
Data from: Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross-specific and species-specific amplifications
Although whole-genome sequencing is becoming more accessible and feasible for nonmodel organisms, microsatellites have remained the markers of choice for various population and conservation genetic studies. However, the criteria for choosing microsatellites are still controversial due to ascertainment bias that may be introduced into the genetic inference. An empirical study of red deer (Cervus elaphus) populations, in which cross-specific and species-specific microsatellites developed through pyrosequencing of enriched libraries, was performed for this study. Two different strategies were used to select the species-specific panels: randomly vs. highly polymorphic markers. The results suggest that reliable and accurate estimations of genetic diversity can be obtained using random microsatellites distributed throughout the genome. In addition, the results reinforce previous evidence that selecting the most polymorphic markers leads to an ascertainment bias in estimates of genetic diversity, when compared with randomly selected microsatellites. Analyses of population differentiation and clustering seem less influenced by the approach of microsatellite selection, whereas assigning individuals to populations might be affected by a random selection of a small number of microsatellites. Individual multilocus heterozygosity measures produced various discordant results, which in turn had impacts on the heterozygosity-fitness correlation test. Finally, we argue that picking the appropriate microsatellite set should primarily take into account the ecological and evolutionary questions studied. Selecting the most polymorphic markers will generally overestimate genetic diversity parameters, leading to misinterpretations of the real genetic diversity, which is particularly important in managed and threatened populations.
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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.