Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
412
datasets available to search
ShareScore release 0.9.0
Dataset results
412 results for “Verification”
Reproduction Package for Submission `A Literature Review on Verification and Abstraction of Neural Networks'
<div> <div>This artifact contains the aggregated data for the article "A Literature Review on Verification and Abstraction of Neural Networks".</div> <br> <div>The artifact contains the following data files:</div> <br> <div>|-- phase-1_search-space.csv</div> <div>|-- phase-2-3_process-title-abstract.csv</div> <div>|-- review_sheet.csv</div> <br> <h3>Search space for literature review</h3> <div>The file <code>phase-1_search-space.csv</code> contains the metadata of the papers published in our considered conferences during the observed years.</div> <br> <h3>Filtering process</h3> <div>In the file <code>phase-2-3_process-title-abstract.csv</code>, we include the files that contain our expected keywords.</div> <div>Depending on whether we decided to include the paper in our survey after reading the title and the abstract, we marked each of the papers with `accept` or `decline`.</div> <br> <h3>Review sheet</h3> <div>The file <code>review_sheet.csv</code> contains metadata describing our reviews for each of the publications.</div> <div>It holds information on our final review of each paper, including the group we assigned it to and the reasons for its exclusion.</div> <br> <h3>Generating numbers</h3> <div>The following commands can be executed to reproduce the numbers used in our literature review.</div> <br> <div><code># Change directory to the directory containing the CSV files of this artifact.</code></div> <br> <div><code># Number of papers in our search space.</code></div> <div><code>cat phase-1_search-space.csv | tail -n +2 | wc -l</code></div> <br> <div><code># Number of papers after keyword search.</code></div> <div><code>cat phase-2-3_process-title-abstract.csv | tail -n +2 | wc -l</code></div> <br> <div><code># Number of papers that are excluded based on abstracts and titles.</code></div> <div><code>cut -f9 phase-2-3_process-title-abstract.csv | tail -n +2 | sort | uniq -c</code></div> <br> <div><code># Number of papers in different classes.</code></div> <div><code>cut -f7 review_sheet.csv | tail -n +2 | sort | uniq -c</code></div> <div> </div> </div>
Verus: A Practical Foundation for Systems Verification -- Artifact -- Set 2 Screen Capture
<p>A screen capture of the experiment in Set 2 of the artifact for the SOSP24 conditionally accepted paper "Verus: A Practical Foundation for Systems Verification": the experiment was performed on an Amazon AWS c5.4xlarge machine running Windows.</p>
FIGURE 3 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 3. Dendrograms constructed based on SSR markers using a) NJ method and b) Bayesian inference. The numbers in the Bayesian dendrogram are posterior probabilities. Roman numerals mark separate clusters.
FIGURE 5 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 5. Dendrograms constructed based on SNP markers using a) NJ method and b) Bayesian inference. The numbers in the Bayesian dendrogram are posterior probabilities. Roman numerals mark separate clusters.
FIGURE 2 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 2. Dendrograms constructed based on variation in ScBx5 gene fragment using a) NJ method and b) Bayesian inference. The numbers in the NJ dendrogram are bootstrap support and posterior probabilities in Bayesian dendrogram. Roman numerals mark separate clusters.
FIGURE 1 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 1. Dendrograms constructed based on variation in ScBx1 gene fragment using a) NJ method and b) Bayesian inference. The numbers in the NJ dendrogram mean bootstrap support and posterior probabilities in Bayesian dendrogram. Roman numerals mark separate clusters.
FIGURE 4 in Verification of taxonomic relationships within the genus Secale (Poaceae: Pooideae: Triticeae) based on multiple molecular methods
FIGURE 4. Dendrograms constructed based on SSAP markers using a) NJ method and b) Bayesian inference. The numbers in the Bayesian dendrogram are posterior probabilities. Roman numerals mark separate clusters.
Dataset and code for A Multidimensional Error Verification Method for Weather Forecast Based on the Spatial Distribution Structural Similarity of Meteorological Elements
<p>The dataset includes rainfall observations and mesoscale numerical prediction data for 16 July 2019, 13 June 2020 and 2024 rainy season.<br>The code is the algorithm procedure of this paper. Among them, meiyutest.py is the rainfall scoring procedure for the Meiyu period, and 2019case is the forecast scoring and plotting procedure for two individual cases.</p>
Forecasting Capability Verification of the Pangu-Weather and ECMWF Models for the 2022 Summer Weather in Jiangsu Province, China
Open the record for dataset details and reuse information.
Input Files and Processed Results for FreeMHD: validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows
<p><strong>Input Files (StartingFiles.zip) and Processed Results (FreeMHDPaperAllFigures.zip) used to make paper figures. </strong></p> <p> </p> <p>FreeMHD: validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows</p> <p><em>The extreme heat fluxes in the divertor region of tokamaks may require an alternative to solid plasma-facing components, for the extraction of heat and the protection of the surrounding walls. Flowing liquid metals are proposed as an alternative, but raise additional challenges that require investigation and numerical simulations. Free surface designs are desirable for plasma-facing components (PFCs), but steady flow profiles and surface stability must be ensured to limit undesirable interactions with the plasma. Previous studies have mainly used steady-state, 2D, or simplified models for internal flows and have not been able to adequately model free-surface liquid metal (LM) experiments. Therefore, FreeMHD has been recently developed as an open-source magnetohydrodynamics (MHD) solver for free-surface electrically conductive flows subject to a strong external magnetic field. The FreeMHD solver computes incompressible free-surface flows with multi-region coupling for the investigation of MHD phenomena involving fluid and solid domains. The model utilizes the finite-volume OpenFOAM framework under the low magnetic Reynolds number approximation. FreeMHD is validated using analytical solutions for the velocity profiles of closed channel flows with various Hartmann numbers and wall conductance ratios. Next, experimental measurements are then used to verify FreeMHD, through a series of cases involving dam breaking, 3D magnetic fields, and free-surface LM flows. These results demonstrate that FreeMHD is a reliable tool for the design of LM systems under free surface conditions at the reactor scale. Furthermore, it is flexible, computationally inexpensive, and can be used to solve fully 3D transient MHD flows.</em></p>
PAN20 Authorship Analysis: Authorship Verification
<p><strong>Task</strong></p> <p>Authorship verification is the task of deciding whether two texts have been written by the same author based on comparing the texts' writing styles.</p> <p>In the coming three years at PAN 2020 to PAN 2022, we develop a new experimental setup that addresses three key questions in authorship verification that have not been studied at scale to date:</p> <ul> <li> <p>Year 1 (PAN 2020): Closed-set verficiation.<br> Given a large training dataset comprising of known authors who have written about a given set of topics, the test dataset contains verification cases from a subset of the authors and topics found in the training data.</p> </li> <li> <p>Year 2 (PAN 2021): Open-set verification.<br> Given the training dataset of Year 1, the test dataset contains verification cases from previously unseen authors and topics.</p> </li> <li> <p>Year 3 (PAN 2022): <em>Suprise task</em>.<br> The task of the last year of this evaluation cycle (to be announced at a later time) will be designed with an eye on realism and practical application.</p> </li> </ul> <p>This evaluation cycle on authorship verification provides for a renewed challenge of increasing difficulty within a large-scale evaluation. We invite you to plan ahead and participate in all three of these tasks.</p> <p>More information at: <a href="https://pan.webis.de/clef20/pan20-web/author-identification.html">PAN @ CLEF 2020 - Authorship Verification</a></p> <p> </p> <p><strong>Citing the Dataset</strong></p> <p>If you use this dataset for your research, please be sure to cite the following paper:<br> <br> Sebastian Bischoff, Niklas Deckers, Marcel Schliebs, Ben Thies, Matthias Hagen, Efstathios Stamatatos, Benno Stein, and Martin Potthast. The Importance of Suppressing Domain Style in Authorship Analysis. CoRR, abs/2005.14714, May 2020.</p> <p>Bibtex:</p> <pre><code>@Article{stein:2020k, author = {Sebastian Bischoff and Niklas Deckers and Marcel Schliebs and Ben Thies and Matthias Hagen and Efstathios Stamatatos and Benno Stein and Martin Potthast}, journal = {CoRR}, month = may, title = {{The Importance of Suppressing Domain Style in Authorship Analysis}}, url = {https://arxiv.org/abs/2005.14714}, volume = {abs/2005.14714}, year = 2020 }</code></pre> <p> </p>
An Empirical Evaluation of the Effectiveness of Smart Contract Verification Tools - Supplemental Material
<p>An Empirical Evaluation of the Effectiveness of Smart Contract Verification Tools - Supplemental Material</p>
Data for 1D/2D verification of AWP-ODC-Iwan implementation
<p>Input data files and output synthetics for 1D and 2D benchmarks for Noah, Noah2D, and AWP-ODC-Iwan.</p>
Benchmark dataset for verification and validation of elPaSo Core module
<p>This dataset contain the set of vibroacoustic benchmark problems for verification and validation of the FEM research code "elPaSo Core".</p>
APOGEE-TESS Verification
<p>This dataset contains stars from NASA's TESS mission and APOGEE to test TESS's calibration comparatively to the Kepler scale. Link to publication: </p> <p>Arxiv:</p> <p><a href="https://arxiv.org/abs/2307.13853">https://arxiv.org/abs/2307.13853</a></p> <p>RNAAS:</p> <p><a href="https://iopscience.iop.org/article/10.3847/2515-5172/ace7af">https://iopscience.iop.org/article/10.3847/2515-5172/ace7af</a></p>
Continuous verification - platooning case
<pre>This repository provides raw data used in the paper "Continuous Verification with Acknowledged MAPE-K Pattern and Time Logic-based Slicing: A platooning System of Systems Case Study". Related tools include the PRISM model checker (<a href="https://github.com/prismmodelchecker/prism.git">https://github.com/prismmodelchecker/prism.git</a>) and the platooning simulator (<a href="https://github.com/KAIST-SE-Lab/StarPlateS">https://github.com/KAIST-SE-Lab/StarPlateS</a>). The Original folder is the data obtained from the existing simulator. The CVplatooning folder is data obtained by improving the existing simulator. Finally, the slicing folder provides the existing model verification results and model slicing verification results.</pre>
Experimental Results for the AAAI 2023 Paper "On Total-Order HTN Plan Verification with Method Preconditions -- An Extension of the CYK Parsing Algorithm"
<p>This is the collection of the experimental results reported in the paper "On Total-Order HTN Plan Verification with Method Preconditions -- An Extension of the CYK Parsing Algorithm". For a detailed explanation, please read the README.md file.</p>
Myocardialbridge Bypass Graft Surgery Efficacy Verification
ClinicalTrials.gov study NCT06857838. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Non-invasive BCI and Application Verification for Depressed People
ClinicalTrials.gov study NCT06417437. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study on the Verification of Kidney CT Non-inferiority Using Low Concentration Contrast Agent
ClinicalTrials.gov study NCT05831943. IPD Sharing: NO. Countries: 1. Publications: 11.
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.