Find research datasets worth reusing

Data for the article "Mechanically induced correlated errors on superconducting qubits with relaxation times exceeding 0.4 milliseconds"

Here you will find all the raw data and data processing scripts for the plots presented in the article "Mechanically induced correlated errors on superconducting qubits with relaxation times exceeding 0.4 milliseconds."

A Memristive Neural Decoder for Cryogenic Fault-Tolerant Quantum Error Correction - Syndromes Dataset

Simulated sydromes measurement of quantum surface code error correction. Used for the paper: "<a href="https://doi.org/10.48550/arXiv.2307.09463">A Memristive Neural Decoder for Cryogenic Fault-Tolerant Quantum Error Correction</a>". File names: <code>d-<surface_code_distance>_pfr-<physical_fault_rate>_nb-<number_of_samples></code> Each file is formatted as csv with the following columns: <ul> <li>label: binary label (0: no error, 1: error)</li> <li>syndromes: syndrome measurement sequence (tuples of the form (round, syndromes))</li> <li>quantity: number of samples for this label + syndrome sequence</li> </ul> Only distance 3 is currently available with 10M samples for each physical fault rate. The data generation relies on <a href="https://github.com/quantumlib/Stim" target="_blank" rel="noopener">Stim</a>.

A Memristive Neural Decoder for Cryogenic Fault-Tolerant Quantum Error Correction - Simulation Data

Simulation output data used to generate figures of the paper: "<a href="https://doi.org/10.48550/arXiv.2307.09463">A Memristive Neural Decoder for Cryogenic Fault-Tolerant Quantum Error Correction</a>"

Data for "Optimization of decoder priors for accurate quantum error correction"

Datasets of surface code and repetition code memory experiments executed on Google's Sycamore quantum processor. See README at the root of each zip archive for detailed description of each dataset.

opencc-by-sa-4.0Apr 2018View details →

Dataset: error characteristics of a class 0.2S current transformer for publication

Data for demonstrating typical error characteristics of a current transformer of the class 0.2 S. Data are used in a publication.

Figshare44/100

Error Related Potentials from Gaze-Based Typesetting

The recording protocol relied on a standard gaze-based keyboard paradigm that was implemented by an eye-tracker attached to a PC monitor. The gazing information, in the form of a densely sampled sequence of x-y coordinates corresponding to the eye trace on the screen, was registered simultaneously with the participant’s brainwaves. The purpose of this experiment was to provide data where patterns in the physiological activity, of either brain or eyes, could be associated with the case of a typo (due to either the inaccuracy of the eye-tracker or a human mistake).

opencc-by-4.0Dec 2017View details →

opencc-by-4.0Aug 2024View details →

Research Data/Code for "Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantification"

This repository contains research data and code for supplementing the manuscript  "Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantification"  by L. Gossel, E. Corbean, S. Dübal, P. Brand, M. Fricke, H. Nicolai, C. Hasse, S. Hartl, S. Ulbrich, and D. Bothe.  There is a corresponding preprint available on Arxiv:      https://doi.org/10.48550/arXiv.2404.13092 Users are referred to the manuscript for background information. This repository shall enable reproduction of the reported results and does not stand alone.  Please read important information in the README in the top-level directory.  Funded by the Hessian Ministry of Higher Education, Research, Science and the Arts - cluster project Clean Circles.

opencc-by-4.0Aug 2024View details →

Data for "Quantum error correction below the surface code threshold"

Datasets of the surface code and repetition code memory experiments executed on Google's quantum processor. See README at the root of each zip archive for detailed description of each dataset.

opencc-by-4.0Oct 2024View details →

Software, Dataset, and Techreport: Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

This upload contains a techreport titled "Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration" together with the software (with documentation) and dataset generating the results. The software is also available on GitHub at https://github.com/croci/mpfem-paper-experiments-2024/ . The GitHub version may be updated in the future. This upload corresponds to commit number 8506dd368b84655201c8c72b1307239b9b4e43fd . See README.md file for installation instructions. The manuscript is also available on the arXiv: https://arxiv.org/abs/2410.12614.

opencc-by-4.0Aug 2021View details →

Artifacts supplementing the EuroUSEC '22 paper "Assessing Real-World Applicability of Redesigned Developer Documentation for Certificate Validation Errors"

This upload supplements the conference EuroUSEC 2022 submission by providing the full questionnaire, anonymized dataset and all performed analyses presented in the paper specified below. <ul> <li>Title: Assessing Real-World Applicability of Redesigned Developer Documentation for Certificate Validation Errors</li> <li>Authors: Martin Ukrop, Michaela Balážová, Pavol Žáčik, Eric Vincent Valčík, Vashek Matyas</li> <li>Paper details: https://crocs.fi.muni.cz/public/papers/eurousec2022</li> <li>Paper abstract: We face certificate validation errors commonly, yet the related tools and documentation had been shown to have very poor usability. Previous research suggests that just improving the error messages and corresponding documentation can have significantly positive effects. Our work aims at increasing the usability of certificate validation by 1) redesigning the API error messages and the corresponding documentation, and 2) validating the real-world applicability of the redesign by investigating the opinions of 180 IT professionals. We focus on the perceived obstacles, desired ideal form and overall satisfaction. The redesigned documentation exhibits a reliable significant decrease in perceived incompleteness, with a small amount of perceived bloat and tangle. The redesigned documentation, now published on a dedicated website, is preferred by 89% of our study participants.</li> </ul> The artifacts accompanying this paper contain three major parts: <ul> <li>The questionnaire used in the main study (described in Sections 3.1 and 3.2 of the paper and mostly present in Appendices A and B of the paper).</li> <li>The anonymized dataset (multiple formats) of all valid questionnaire answers and qualitative coding performed. Analyses of this dataset are the core of the paper and are present in subsection 3.4 and all parts of Sections 4 and 5.</li> <li>The set of analyses files (IBM SPSS scripts and outputs) producing all statistical results presented in the paper are included.</li> </ul> More details about the artifacts can be found in the README file in the artifacts archive.

opencc-zeroAug 2021View details →

Raw and aggregated data for the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors"

This dataset contains all the raw data and aggregated data subject of the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors". The study is based on the bibliographic and citation data contained in 729 articles published in 147 journals in 27 subject areas. The articles contained a total amount of 34,140 bibliographic references and 55,100 mentions and quotations overall. The dataset is composed of a series of files: <ul> <li>the files "subject_area_<discipline-name>.csv" contain the raw data of the articles published in the journals of all the disciplines considered in the study;</li> <li>the file "article_data_summary.csv" contains the aggregated data created considering the raw data in the previous files, which have been used to creating all the tables and figures in the article;</li> <li>the file "starred_metadata_set.csv" contains information about the most used subset of bibliographic metadata;</li> <li>the file "journals_selection.csv" contains information about all the journals selected for the study.</li> </ul>

opencc-zeroJun 2016View details →

ERROR: wikipathways-20160610-gmt-Bos_thaurus.gmt

Whoops! Typo in species name. Please see https://zenodo.org/record/7718870 for all (correct) released versions

opencc-by-4.0Jun 2023View details →

Data for "Noise-induced servo errors in optical clocks utilizing Rabi interrogation"

Numerical simulation data used for figures in "Noise-induced servo errors in optical clocks utilizing Rabi interrogation" (Metrologia, DOI 10.1088/1681-7575/acdfd4). For some figures, also the analytical results are given. For description of data, see header rows. For details, see the corresponding figure captions in the article.

opencc-by-4.0Jul 2023View details →

Model outputs for the study "Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis"

This resources provides pre-processed input data, model checkpoints and model outputs for experiments on the OpenI dataset in below study.  <blockquote> Jan Trienes, Paul Youssef, Jörg Schlötterer, and Christin Seifert. 2023. <a href="https://arxiv.org/abs/2307.12803">Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis</a>. In Proceedings of the 16th International Natural Language Generation Conference (INLG), Prague, Czech Republic. Association for Computational Linguistics. </blockquote> For more information please refer to the accompanying paper and code repository (<a href="https://github.com/jantrienes/inlg2023-radsum">https://github.com/jantrienes/inlg2023-radsum</a>). The data is structured as follows: <ul> <li><code>data/preprocessed/</code> includes the dataset(s) for each model</li> <li><code>output/</code> includes one folder for each experiment/model run. The first part of each output path indicates the dataset that was used at inference.</li> <li>For a mapping between model IDs and results in the paper, see below table. All models were also trained with the background section as input. These are available in directories with the <code>-bg-</code> qualifier. </li> </ul> <table> <thead> <tr> <th>Model name in paper</th> <th>Output directory</th> </tr> </thead> <tbody> <tr> <td>Results from Table 2</td> </tr> <tr> <td>OracleExt</td> <td>openi-unguided/oracle</td> </tr> <tr> <td>BertExt (Liu and Lapata, 2019)</td> <td>openi-unguided/bertext-default</td> </tr> <tr> <td>BertAbs (Liu and Lapata, 2019)</td> <td>openi-unguided/bertabs-default</td> </tr> <tr> <td>GSum (Dou et al., 2021)</td> <td>openi-bertext-default-clip-k1/gsum-default</td> </tr> <tr> <td>GSum w/ LR-Approx</td> <td>openi-bertext-default-clip-lrapprox/gsum-default</td> </tr> <tr> <td>GSum w/ BERT-Approx</td> <td>openi-bertext-default-clip-bertapprox/gsum-default</td> </tr> <tr> <td>GSum w/ Thresholding</td> <td>openi-bertext-default-clip-threshold/gsum-default</td> </tr> <tr> <td>WGSum (Hu et al., 2021)</td> <td>openi-wgsum/wgsum-default</td> </tr> <tr> <td>WGSum+CL (Hu et al., 2022)</td> <td>openi-wgsum-cl/wgsum-cl-default</td> </tr> <tr> <td>Results from Table 3</td> </tr> <tr> <td>Fixed (k=1)</td> <td>openi-unguided/bertext-default-clip-k1</td> </tr> <tr> <td>LR-Approx</td> <td>openi-unguided/bertext-default-clip-lrapprox</td> </tr> <tr> <td>BERT-Approx</td> <td>openi-unguided/bertext-default-clip-bertapprox</td> </tr> <tr> <td>Thresholding</td> <td>openi-unguided/bertext-default-clip-threshold</td> </tr> <tr> <td>k = |OracleExt|</td> <td>openi-unguided/bertext-default-clip-oracle</td> </tr> <tr> <td>Results from Table 4</td> </tr> <tr> <td>Fixed (Dou et al., 2021)</td> <td>openi-bertext-default-clip-k1/gsum-default</td> </tr> <tr> <td>Oracle Length</td> <td>openi-bertext-default-clip-oracle/gsum-default</td> </tr> <tr> <td>Oracle Length + Content</td> <td>openi-oracle/gsum-default</td> </tr> <tr> <td>Results from Table 5</td> </tr> <tr> <td>BertExt w/ k=[1,5]</td> <td>openi-unguided/bertext-default-clip-k{1,2,3,4,5}</td> </tr> <tr> <td>GSum w/ k=[1,5]</td> <td>openi-bertext-default-clip-k{1,2,3,4,5}/gsum-default</td> </tr> </tbody> </table>

opencc-by-nc-sa-4.0Aug 2023View details →

ifilot/microkinetic-datasets-methanation-fts: Fix error in description

This repository contains three datasets for performing microkinetic simulations. <ul> <li>CO2 methanation over Co(1121) lattice [1]</li> <li>CO2 methanation over a NiMn catalyst [2]</li> <li>Fischer-Tropsch synthesis over a dual-site Co(0001)xCo(1121) lattice [3]</li> </ul> These datasets are based on the following publications 1. W. Chen; R. Pestman; B. Zijlstra; I.A.W. Filot; E.J.M. Hensen, Mechanism of cobalt-catalyzed co hydrogenation: 1. methanation,     ACS Catal., 2017, 7, 8061-8071. 2. W.L. Vrijburg; E. Moioli; W. Chen; M. Zhang; B.J.P. Terlingen; B. Zijlstra; I.A.W. Filot; A.Zuttel; E.A. Pidko; E.J.M. Hensen, Efficient Base-Metal NiMn/TiO2 Catalyst for CO2 Methanation, ACS Catal., 2019, 9, 7823-7839. 3. B. Zijlstra; R. J. P. Broos; W. Chen; G. L. Bezemer; I. A. W. Filot; E. J. M. Hensen, The vital role of step-edge sites for both co activation and chain growth on cobalt fischer-tropsch catalysts revealed through first-principles-based microkinetic modeling including lateral interactions, ACS Catal., 2020, 10, 9376-9400. For more information on the formatting of these files, please consult the <a href="https://wiki.mkmcxx.nl/index.php/Main_Page">MKMCXX wiki</a>.

opencc-by-4.0May 2020View details →

Generalized model-based solutions to false positive error in species detection/non-detection data: DataS5.

Data/code associated with empirical case study (Gray fox relative abundance estimation/prediction) in article "Generalized model-based solutions to false positive error in species detection/non-detection data" [doi pending].

opencc-by-4.0Jun 2020View details →

Dataset: Accuracy of Motor Error Predictions for Different Sensory Signals

Supplementary Data for Accuracy of Motor Error Predictions for Different Sensory Signals article Dataset associated with the following publication: Joch, M., Hegele, M., Maurer, H., Müller, H., & Maurer, L. K. (2018). Accuracy of Motor Error Predictions for Different Sensory Signals. Frontiers in Psychology, 9 (August), 1–13. https://doi.org/10.3389/fpsyg.2018.01376

opencc-by-4.0Jul 2020View details →

Online Supplemental Materials for: "Total Error and Variability Measures for the Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in OnTheMap"

This archive contains supplementary materials for the published manuscript. We report results from the first comprehensive total quality evaluation of five major indicators in the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): total flow-employment, beginning-of-quarter employment, full-quarter employment, average monthly earnings of full-quarter employees, and total quarterly payroll. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics (LODES) workplace reports as displayed in OnTheMap (OTM), including OnTheMap for Emergency Management. We account for errors due to coverage; record-level non-response; edit and imputation of item missing data; and statistical disclosure limitation. The analysis reveals that the five publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs are a transition zone, where cells may be fit for use with caution. Tabulations involving one or two jobs, which are generally suppressed on fitness-for-use criteria in the QWI and synthesized in LODES, have substantial total variability but can still be used to estimate statistics for untabulated  aggregates as long as the job count in the aggregate is more than 10.

opencc-by-4.0Nov 2020View details →

Database for "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China"

This file contains the dataset accompanying the manuscript '2020EA001232-TR' submitted to the ESS journal (https://earthandspacescience-submit.agu.org). Title: "A new perspective for charactering the spatio-temporal patterns of the error in GPM IMERG over mainland China" China Merged Precipitation Analysis data (CMPA, hourly, with the resolution of , as validation data) for China Mainland is available at website http://data.cma.cn. Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrieval data (IMERG, half-hourly, with the resolution of , as the observed data) is available at https://pmm.nasa.gov/data-access/downloads/gpm. The Shuttle Radar Topography Mission data (SRTM, with a 90-m spatial resolution) could be accessed at http://srtm.csi.cgiar.org.