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.
56
datasets available to search
ShareScore release 0.9.0
Dataset results
56 results for “Benchmark study”
Supplementary information for phylogenetic benchmarking study
<p>This dataset comprises the following files:</p> <p>- A tarball containing all alignments per run, used to infer phylogenies from (gzipped)</p> <p>- A tarball containing all assemblies (where applicable) per run (gzipped)</p> <p>- Several files with final results of the analyses. These can be read directly into SuperPlotsOfData to obtain the plots in our paper. RF = Robinson Foulds distance, KC = Kendall Colijn metric. L_0, L_0.5 and L_1 indicate lambda values of 0, 0.5 and 1 respectively in the calculation of the Kendall Colijn metric. full_data.csv contains all data. full_data_nomlst.csv contains all data, excluding the runs employing MLST alignment. run_differences_absolute.csv contains absolute differences between identical runs.</p>
The International FluidFlower benchmark study dataset
<p>The dataset describes physical, laboratory CO<sub>2</sub> injection experiments in a room-scale physcial reservoir model with geological realistic geometry. The dynamics of relevant subsurface CO2 injection and trapping mechanisms are recorded in time-lapsed image-series. Five repetitions of operationally identical CO2 injection experiments were performed. For each of the five repetitions (termed C1, C2, C3, C4 and C5) one dataset is issued. Each dataset contains 137 high-resolution images with the following intervals: 10 images before CO<sub>2</sub> injection at 20 second intervals; images every 5 min during the first 360 min (6 hours) of the experiment (73 images); images every hour until 48 hours (42 images); images every 6 hours until end of experiment (12 images).</p> <p> </p> <p>The format of image names is yyMMdd_timeHHmmss_image number.TIF (e.g. '211124_time082740_DSC00067.TIF')</p> <p>Note: image series C5 contains 133 images; the 4 missing images from the 5-minute interval between 5-6 hours.</p>
Single-cell RNA-seq count data used in differential expression benchmark study
<p>Count matrices and meta data tables from simulated and real world immune cell single-cell RNA-seq experiments.</p> <p>All files are in Rds format and can be read by R using "readRDS()". </p> <ul> <li>10k_*: These files contain a filtered version of the 10k Human PBMCs, 3' v3.1 data <a href="https://www.10xgenomics.com/resources/datasets/10k-human-pbmcs-3-v3-1-chromium-controller-3-1-high">published</a> by 10x Genomics</li> <li>blueprint_data.Rds: This file contains the bulk RNA-seq data downloaded from <a href="http://dcc.blueprint-epigenome.eu">BLUEPRINT</a></li> <li>blueprint_immune_comparisons.Rds: Results from running three bulk RNA-seq differential expression methods</li> <li>sim_data*: These files contain the count matrices and meta data tables for the simulated data. Every file contains a list of 13 replicates.</li> </ul> <p> </p>
The Women TDF-FTC Benchmark Study
ClinicalTrials.gov study NCT05057858. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data from: On the flexibility of the multipole model refinement. A DFT benchmark study of the tetrakis(μ-acetato)diaquadicopper model system
Open the record for dataset details and reuse information.
Comparative Study of the Restorative effects of Forest and Urban Videos during Covid-19 Lockdown: Intrinsic and Benchmark Value
<p>Article: "Comparative Study of the Restorative effects of Forest and Urban Videos during Covid-19 Lockdown: Intrinsic and Benchmark Value"</p> <p>Video S1: forest environment </p> <p>Video S2: urban environment</p>
Data for "A Phaseless Auxiliary-Field Quantum Monte Carlo Perspective on the UniformElectron Gas at Finite Temperatures: Issues, Observations, and Benchmark Study"
<p>Phaseless AFQMC data (input and output) for "A Phaseless Auxiliary-Field Quantum Monte Carlo Perspective on the UniformElectron Gas at Finite Temperatures: Issues, Observations, and Benchmark Study" </p> <p> </p> <p>data: contains raw qmc data</p> <p>figures: contains analysed data + plotting scripts.</p>
Benchmarking Study of Deep Generative Models for Inverse Polymer Design: Generation Results
Open the record for dataset details and reuse information.
Dataset from: A pragmatic benchmarking study of an evidence-based personalized approach in 1938 adolescents with high-risk idiopathic scoliosis
<p>Dataset from a still non published study titled "A pragmatic benchmarking study of an evidence-based personalized approach in 1938 adolescents with high-risk idiopathic scoliosis"</p>
Dataset of "Poster - BugOss: Regression Bug Benchmark for Empirical Study of Regression Fuzzing Techniques"
<p>Dataset of "Poster - BugOss: Regression Bug Benchmark for Empirical Study of Regression Fuzzing Techniques"</p>
Benchmarking data for studying order-related performance effects
<p>This dataset includes over 2.2M performance measurements collected on the CloudLab testbed. Performance tests from CPU and memory benchmarks were run in fixed and random orders allowing comprehensive comparisons. The analysis and the outcomes are summarized in the paper "Avoiding the Ordering Trap in Systems Performance Measurement", which will become available online in the near future and will be presented at USENIX ATC'23.</p> <p>--------------</p> <p>Contributors:</p> <ul> <li> <p>Dmitry Duplyakin (University of Utah)</p> </li> <li> <p>Nikhil Ramesh (University of Utah) </p> </li> <li> <p>Carina Imburgia (University of Washington) </p> </li> <li> <p>Hamza Fathallah Al Sheikh (University of Utah) </p> </li> <li> <p>Semil Jain (University of Utah) </p> </li> <li> <p>Prikshit Tekta (University of Utah) </p> </li> <li> <p>Aleksander Maricq (University of Utah) </p> </li> <li> <p>Gary Wong (University of Utah) </p> </li> <li> <p>Robert Ricci (University of Utah) </p> </li> </ul>
GNN-powered Approach to Decompose Monoliths to Microservices: A Case Study on Third Party Benchmark
<p>This table shows the original classes in the ftgo-microservice application and the decomposition predicted by the approach using an autoencoder with K-means (AE-K). The common classes are highlighted in green.</p>
GNN-powered Approach to Decompose Monoliths to Microservices: A Case Study on Third Party Benchmark
<p>This table shows the original classes in the ftgo-microservice application and the decomposition predicted by the approach using an autoencoder with C-means (AE-C). The common classes are highlighted in green.</p>
GNN-powered Approach to Decompose Monoliths to Microservices: A Case Study on Third Party Benchmark
<p>The results describe the similarity between the ftgo-microservice application and the decomposition predicted by three AI models.</p>
Study to Assess the Effect of Ofatumumab in Treatment Naïve, Very Early RRMS Patients Benchmarked Against Healthy Controls.
ClinicalTrials.gov study NCT05084638. IPD Sharing: YES. Countries: 2. Publications: 0.
Unveiling Developers' Feelings: A Benchmarking Study on Emotion and Sentiment Analysis of Software Commit Messages
Open the record for dataset details and reuse information.
Supplementary Information: On the Role of Dielectric Screening in Calculating Excited States of Solvated Azobenzene: A Benchmark Study Comparing Quantum Embedding and Polarizable Continuum Model for Representing the Solvent
<p>Link to Gitlab repo: https://gitlab.com/jezsmartinez/azobencene_ep/-/tree/main</p>
Figure 6 from: Albratty M, Thangavel N, Chandrasekaran B, Meraya AM, Alhazmi HA, Muthumanickam S, Boomi P, Bhagavan NB, Saleh SF (2024) Benchmarking docking, density functional theory and molecular dynamics studies to assess the aldose reductase inhibitory potential of Trigonella foenum-graecum compounds for managing diabetes-associated complications. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e118949
Figure 6 Molecular dynamics of Tigogenin and Gitogenin bound to aldose reductase: (a) RMSD, (b) RMSF, (c) Hydrogen bond profile; green-Tigogenin, red-Gitogenin, black-apoprotein.
Supplementary material 1 from: Albratty M, Thangavel N, Chandrasekaran B, Meraya AM, Alhazmi HA, Muthumanickam S, Boomi P, Bhagavan NB, Saleh SF (2024) Benchmarking docking, density functional theory and molecular dynamics studies to assess the aldose reductase inhibitory potential of Trigonella foenum-graecum compounds for managing diabetes-associated complications. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e118949
List of molecular weight matched decoys retrieved from DEKOIS 2.0
Figure 5 from: Albratty M, Thangavel N, Chandrasekaran B, Meraya AM, Alhazmi HA, Muthumanickam S, Boomi P, Bhagavan NB, Saleh SF (2024) Benchmarking docking, density functional theory and molecular dynamics studies to assess the aldose reductase inhibitory potential of Trigonella foenum-graecum compounds for managing diabetes-associated complications. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e118949
Figure 5 HOMO and LUMO distribution plots: (a) HOMO (b) LUMO of Tigogenin (c) HOMO (d) LUMO of Gitogenin.
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.