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.
1,930
datasets available to search
ShareScore release 0.7.1
Dataset results
1,930 results for “matrix”
Social Accounting Matrix for Lithuania, 2017 (with the shift to bioplastics in packing industry)
<p>The dataset is based on doi: 10.5281/zenodo.5077893 but includes bioplastics as the main input for the production of plastic sacks and bags.</p>
Social Accounting Matrix for Lithuania, 2017
<p>The dataset provides Lithuanian Social Accounting Matrix compilded using official data from Eurostat:</p> <p>•Supply table (naio_10_cp15)</p> <p>•Use table (naio_10_cp16)</p> <p>•Statistics on non-financial transactions (nasq_10_nf_tr)</p> <p>The matrix is balanced minimizing relative deviations from original values. It uses Eurostat's naming conventions. In addition, elements ACT1, ACT2, ACT3, ACT4, ACT5, CMD1, CMD2, CMD3, CMD4, CMD5, FC1, FC2 are introduced to enable disaggregations and descriptions of industrial transformations.</p>
Dataset: Time-dependent source apportionment of submicron organic aerosol for a rural site in an alpine valley using a rolling positive matrix factorisation (PMF) window
<p>Uploaded igor pxp files are the data to generate all figures of the results from our publication in Atmospheric Chemistry and Physics with the name of <em>"Time dependent source apportionment of submicron organic aerosol for a rural site in an alpine valley using a rolling PMF window"</em> by Chen et al. (2021).</p> <p>This study deployed a novel and advanced source apportionment technique on a dataset measured in Magadino. Rolling PMF allows retrieving more realistic, time-dependent and detailed information of the organic aerosol sources. This work highlights the strength of the rolling PMF mechanism by comparing it with the results derived from conventional seasonal PMF. Overall, this comprehensive interpretation of chemical speciation monitor (ACSM) data could be a role model for similar analyses.</p>
Anasillomos matrix-based key in SDD-format
<p>Matrix-based, multi-entry key to species of Anasillomos developed with Lucid Builder v4 in XML Structure of Descriptive Data (SDD) format.</p>
D.melanogaster Genelab OSD Normalized RNA Seq Matrix
<p><em>D.melanogaster </em>normalized counts RNA seq data matrix developed from NASA Genelab's open science data repository. Created using R.</p>
M.musculus Genelab OSD Unnormalized RNA seq Matrix
<p><em>M.musculus </em>unnormalized counts RNA seq data matrix from NASA Genelab's open science data repository. Created using R.</p>
Accurate and Efficient Estimation of Local Heritability using Summary Statistics and LD Matrix -- Demo datasets for the HEELS tutorials
<p>We introduced a new estimator for local heritability, "HEELS", which attains comparable statistical efficiency as the REML estimator (such as those produced by GCTA and BOLT-REML) but only requires summary-level statistics – Z-scores from marginal association tests and the empirical LD. Our method has been implemented into an open-source Python-based command line tool. </p> <p>The datasets released here can be downloaded to test the two main functions of our software package: 1) estimating local heritability; 2) computing the low-dimensional representation of the LD matrix. They are meant to accompany the HEELS tutorials we have posted onto the wiki pages of our github repository: https://github.com/huilisabrina/HEELS/wiki.</p> <p> </p>
Matrix reorderings for "Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs"
<p>The paper "Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs" compares various strategies for reordering sparse matrices. The purpose of reordering is to improve performance of sparse matrix operations, for example, by reducing fill-in resulting from sparse Cholesky factorisation or improving data locality in sparse matrix-vector multiplication (SpMV). Many reordering strategies have been proposed in the literature and the current paper provides a thorough comparison of several of the most popular methods.</p> <p>This comparison is based on 490 sparse matrices from the SuiteSparse Matrix Collection (https://sparse.tamu.edu) and 6 matrix reordering algorithms. The dataset provided here supplies the permutations and reordered matrices in Matrix Market file format for 3 matrices and 6 reorderings.</p>
EU27 social accounting matrix for 2020
<p>The dataset contains the European Union's social accounting matrix for 2020. The FIGARO database’s 2022 edition (Eurostat (2022). ESA supply, use and input-output tables) is used to create product-by-product input-output table for the EU, while Eurostat’s data on non-financial transactions (a dataset called nasa_10_nf_tr , Eurostat (2022). Non-financial transactions - annual data) is used to cover the remaining parts of the social accounting matrix.</p> <p> </p> <p>This research was funded by the grant S-MIP-20-53 from the Research Council of Lithuania.</p>
Social Matrix for Lithuania, 2020 with disaggregated CPA_C22
<p>The dataset contains the Lithuanians social accounting matrix for 2020 with disaggregated CPA_C22. The FIGARO database’s 2022 edition (Eurostat (2022). ESA supply, use and input-output tables) is used to create product-by-product input-output table for the EU, while Eurostat’s data on non-financial transactions (a dataset called nasa_10_nf_tr , Eurostat (2022). Non-financial transactions - annual data) is used to cover the remaining parts of the social accounting matrix.</p> <p>The dataset includes a baseline (Reference) scenario without the simulation of sustainability practices and three scenarios simulating the substitution of plastic bags by paper bags (PaperBags), bioplastic bags (BioPlastics) and the reduction of the use of plastic bags (ConsReduction).</p> <p> </p> <p>This research was funded by the grant S-MIP-20-53 from the Research Council of Lithuania.</p>
Distance matrix to newly build motorways in Slovakia
<p>This dataset includes distances from villages and cities within (mostly) central Slovakia to various motorway exits. Focus is on the R1 motorway. It includes car distances both in kilometers and in seconds. The dataset is intended for analysis on socio-economic development of settlements as a result of motorway expansion.</p> <p>Four distances to four different stages of building the motorways in Slovakia are present:</p> <ol> <li>useky1: link to Trnava built in 2000</li> <li>useky2: segments built between 1990 and 2000</li> <li>useky3: newest built segments of motorway (built after 2003, major parts in 2011)</li> <li>useky4: D1 motorway</li> </ol> <p>interactive map at https://epsilon.sk/mapa-dostupnosti/dialnice.html</p> <p> </p> <p>The dataset was created using OpenStreetMap data with OSRM routing engine.</p>
GBASE_Exitation_Emission_Matrix
<p>This dataset contains the Exitation Emission Matrix data associated with GBASE: Geomicrobiology of Antarctic Subglacial Environments - Subglacial Lake Whillans.</p> <p>For the dataset metadata, please see: https://ipt.biodiversity.aq/resource?r=gbase</p>
Matrix of floral traits of Lilium pomponium
<p>Matrix of floral traits of <em>Lilium pomponium</em>. Height and width of the corolla (the latter measured three times, one for each pair of tepals), the distance between the top of the ovary and the tip of the stigma, the distance between the top of the ovary and the tip of the six stamens, the length of the six anthers and the corolla surface are reported. Corolla surface was calculated as the surface of an oblate spheroid. The year of sampling (Year) and the populations code (Pop) are reported. Data of populations are reported in relevé locality data table.</p>
A Post-separation Social Accounting Matrix for the Sudan
<p>A detailed Social Accounting Matrix for the Sudan. Data includes 57 commodity, 64 activity, 14 production factor and 10 households accounts. Currency: Sudanese Pound (SDG)</p>
All vs all matrix of tanimoto scores for GNPS AllPositive dataset
<p>All vs all matrix of tanimoto scores of the "AllPositive" dataset, created from GNPS positive ionmode mass spectra (95320 spectra after filtering). To simplify this matrix, all spectra are grouped by the first 14 characters of their respective inchikeys, which leaves 12,846 inchikeys.</p> <p>In version 2 a lookup table, the metadata file, is provided that records which row/column of the matrix corresponds to which inchikey.</p>
Files and plotting scripts for "Parallel tridiagonal matrix inversion with a hybrid multigrid--Thomas algorithm method"
<p>This archive contains the files required to reproduce the results and figures presented in <em>Parallel tridiagonal matrix inversion with a hybrid multigrid--Thomas algorithm method</em>, J. T. Parker, P. A. Hill, D. Dickinson and B. D. Dudson.</p> <p>Also available at the repository: https://gitlab.com/JosephThomasParker/files-and-plotting-scripts-for-parallel-tridiagonal-matrix-inversion-with-a-hybrid-multigrid-thomas-algorithm-method/</p> <p>Questions to joseph.parker@ukaea.uk.</p> <p>This version is before submission to journal.</p>
Spatial Span and Matrix Reasoning data from the UW-Madison Learning and Transfer Lab
<p><strong>Matrices_SpatialSpan.csv</strong> includes one row for every mouse click for every trial for each participant's spatial span performance (for similar spatial span methods see Cochrane, Simmering, & Green, 2019, PLOS One). Participant IDs, trial numbers, the presence [f] or absence [n] of feedback, and task order (spatial span first or spatial span second) are included alongside by-click accuracy. Also included are each participants' average scores on a subset of items from the UCMRT (Pahor et al., 2019, Beh. Res. Meth) and from the matrices developed at Sandia National Laboratories (Matzen et al., 2010, Beh. Res. Meth.).</p> <p><strong>robustCor.R </strong>is R code implementing a test of bivariate correlation. Univariate Yeo-Johnson transformations are applied, then bootstrapped correlations coefficients are calculated. Point estimates, CI, and Bayes Factors are each returned.</p> <p>Data were collected and code was developed as part of A. Cochrane's dissertation work at the University of Wisconsin - Madison under the supervision of C. Shawn Green.</p>
Video footages captured by Matrix Vision camera and Gopro camera
<p>The two videos briefly demonstrate the video quality captured by the matrix vision camera (mb.mp4) and the GoPro camera (GH010787_Trim.mp4).</p> <p>As can be seen, severe motion blurs showed in the video captured by the matrix vision camera.</p>
Matrix multiplication software and results bundle for paper "Tuning and optimization for a variety of many-core architectures without changing a single line of implementation code using the Alpaka library" for P^3MA submission
<p>This is the archive containing the matrix multiplication software and the results of the publication "<em>Tuning and optimization for a variety of many-core architectures without changing a single line of implementation code using the Alpaka library</em>" submitted to the P^3MA workshop 2017.</p> <p><strong>The archive has the following content:</strong></p> <ul> <li>Source code for the (tiled) matrix multiplication in "src": <ul> <li>regular version in "src/matmul": <ul> <li>Remote: https://github.com/theZiz/matmul.git (copy will be removed)</li> <li>Branch: topic-compatible-alpaka-0-1-0</li> <li>Commit: a63ba4810d6bfcca62c68dd57408af15028e78a3</li> </ul> </li> <li>forked version for XL in "src/matmul": <ul> <li>Remote: https://github.com/theZiz/matmul.git (copy will be removed)</li> <li>Branch: topic-xl-workaround</li> <li>Commit: 1fee028eccb8cf7b677e8071233e08aa9f81846a</li> </ul> </li> </ul> </li> <li>The compiled binaries and the results of the tuning and scaling runs are in "runs" in sub folders for each type of run and architectures.</li> </ul>
Data from: Artificial intelligence enabled multi-purpose smart detection in active-matrix digital microfluidics
<p>Active-matrix digital microfluidics (AM-DMF), integrated with hundreds of thousands of active electrodes, can simultaneously realize multiple on-chip bio-chemical reactions at the single-cell level. An intelligent detection system is critical for fully automating manipulations of thousands of digitalized bio-samples and programming the subsequent experiments in real time. In this work, we developed a series of deep learning algorithms based on an AM-DMF system for sample detections. We used the U-net model to quantitatively evaluate different splitting methods on sample droplet generation uniformity. The results revealed that droplets generated using the "one-to-two" strategy exhibits optimal uniformity. We used the YOLOv5 model to monitor the droplet splitting success rates over 18 different AM-DMF chips, and a 97.7% splitting success rate was observed. The results indicated that the model precision was 99.980% and the model recall was 99.976% through manual verification. In addition, we used an improved YOLOv8 model to detect single cells in nanoliter droplets effectively. In comparison with manual verification, the results showed that the model achieved a precision of 99.260% and a recall of 99.193%. By leveraging an artificial intelligence enabled smart detection system, AM-DMF has shown great potential as a ubiquitous platform for true lab-on-a-chip.</p>
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.