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.
4,230
datasets available to search
ShareScore release 0.9.0
Dataset results
4,230 results for “Energie”
2746-node Polish Energy System Data of Transmission and Voltage Constraints Contribution to the Formation of LMP
<p>This is the dataset that is used for the original article: "Contribution of Transmission and Voltage Constraints in the Formation of Locational Marginal Prices"</p> <p> </p> <p>MATPOWER is required. The dataset obtained by MATPOWER ver6.0 tool [1].</p> <p>Run run_matpower_acopf.m in MATLAB to start AC OPF. Offers should be saved in the MATLAB search path. Results of AC OPF are saved in bus, branch and gen files. Column names correspond to MATPOWER case file.</p> <p>Price-bonding factors are saved in lambda_P_PBF and lambda_Q_PBF. Ones in MP, MQ columns correspond to marginal nodes for real and reactive power respectively. Ones in CV, CD columns correspond to controlled voltage magnitude and phase respectively. </p> <p>Acronyms in column names:</p> <ul> <li>C(N) - bidding price of a marginal generator at node N </li> <li>Fmax(N) - maximum allowable real power throught line N, where N - index number of a line in branch.csv with binding constraint</li> <li>LAMP_P - LMP for real power</li> <li>LAM_Q - LMP for reactive power</li> <li>PBF - price-bonding factor</li> <li>TC - transmission constraint</li> <li>VC - voltage constraint</li> <li>V(N) - maximum (minimum) allowed voltages at node N</li> </ul>
Replication data for: "How does Docker affect energy consumption? Evaluating workloads in and out of Docker containers"
<p>Database of raw power measurements and energy summaries for our Docker energy tests.</p> <p>Please cite us if you use this dataset.</p> <p>Schema</p> <pre><code>CREATE TABLE configuration( name TEXT PRIMARY KEY, description TEXT ); CREATE TABLE experiment( name TEXT PRIMARY KEY, description TEXT ); CREATE TABLE run( id PRIMARY KEY, configuration TEXT REFERENCES configuration(name) ON DELETE CASCADE ON UPDATE CASCADE, experiment TEXT REFERENCES experiment(name) ON DELETE CASCADE ON UPDATE CASCADE ); CREATE TABLE measurement( run REFERENCES run(id) ON DELETE CASCADE ON UPDATE CASCADE, timestamp REAL NOT NULL, -- Unix timestamp in milliseoncds power REAL NOT NULL ); CREATE TABLE energy( id PRIMARY KEY REFERENCES run(id), configuration TEXT REFERENCES configuration(name) ON DELETE CASCADE ON UPDATE CASCADE, experiment TEXT REFERENCES experiment(name) ON DELETE CASCADE ON UPDATE CASCADE, energy REAL NOT NULL, started REAL NOT NULL, ended REAL NOT NULL, elapsed_time REAL NOT NULL -- in milliseconds );</code></pre>
Dual energy CT scan of ordinary objects
<p>Dual energy CT scan of ordinary objects: wires, pen, fruits (orange, avocado), pastery, bacon, butter, cheese.</p> <p>The purpose of these scans is to enable experimenting with CT scans using various kernels and iterative reconstructions. For instance, studying metal artifacts at different energies, material identification using dual energy index, examining the relation between reconstruction kernel sharpness, iterative reconstruction strength and noise.</p> <p>The dataset also can be used to set up mock trials, e.g. where readers have to choose the sharpest image, or the one with least disturbing metal artifacts. Similarly, it could serve debug purposes, e.g. testing the workflow, DICOM readers, etc.</p> <p>Zenodo-get ( https://doi.org/10.5281/zenodo.1261812 ) could be used to download the whole record at once.</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 9)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>GBCurvApprx_175_to_5200.zip<br> Single-grain-boundary-contour-point-resolved curvature estimation tracking data for time step 175 to 5200 with 1 time step resolution and all grains</p> <p>CurvatureEvolution.zip,<br> CurvatureEvolutionAverage.zip<br> TopologyTracer analysis capillary driving force evolution with 100 time step resolution based on the<br> GBContour* data --- not the GBCurvApprx* data.</p> <p>CurvatureEvolutionSuccessful.zip<br> TopologyTracer analysis matrix of segment-length-averaged capillary migration speed for the surviving<br> grains at 1 time step temporal resolution based on the GBCurvApprx* data</p> <p>CurvatureEvolutionUnsuccessful.zip<br> TopologyTracer analysis matrix of segment-length-averaged capillary migration speed for the false<br> positive sub-grains, see paper for details, based on the GBCurvApprx* data</p> <p>UnbiasedGrowthMeasures.zip<br> TopologyTracer analysis temporal evolution of long-range characterisation with the xi metric, see paper for details</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 7)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_450_to_5296.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 450 to 5296 with 1 time step resolution</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 5)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_171_to_259.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 171 to 259 with 1 time step resolution</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 3)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_50_to_99.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 50 to 99 with 1 time step resolution</p> <p> </p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 2)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_1_to_49.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 1 to 49 with 1 time step resolution</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 4)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_100_to_170.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 100 to 170 with 1 time step resolution</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX3D)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>0Synthesis.zip --- Microstructure synthesis<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds and MicrostructureDiagnostics.uds meta data for the grains<br> -parameters.xml parameterization of microstructure synthesis<br> -Scripts and additional input referred to by parameters.xml</p> <p>1Coarsening.zip --- Simulation<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds meta data for the grains<br> -VoxelizedParameters.xml parameterization of coarsening simulation<br> -NrGrains&EnergyStatistics.dat descriptive stats simulation (Time step, Real time, number of grains, ---, grid size)<br> -Network.zip implicit 3d x,y,z unsigned int ID container detailing the microstructure</p> <p>Texture_Faces_1_to_1261.zip<br> Grain boundary network geometry and grain meta data tracking data</p> <p>Network.zip<br> Rendering images for evolution of the grain boundary network and volume properties</p> <p>2DataAnalysis --- Data analyses<br> -All other archive Matlab analysis scripts and TopologyTracer results<br> </p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 1)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>0Synthesis.zip --- Microstructure synthesis<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds and MicrostructureDiagnostics.uds meta data for the grains<br> -parameters.xml parameterization of microstructure synthesis<br> -Scripts and additional input referred to by parameters.xml</p> <p>1Coarsening.zip --- Simulation<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds meta data for the grains<br> -VoxelizedParameters.xml parameterization of coarsening simulation<br> -NrGrains&EnergyStatistics.dat descriptive stats simulation (Time step, Real time, number of grains, ---, grid size)<br> -Network.zip implicit 3d x,y,z unsigned int ID container detailing the microstructure</p> <p>1CoarseningTrackCurvature.zip<br> -Files of the re-run to the simulation along which capillary data were tracked on the fly in each time step</p> <p>GBContourPoints_100_to_5296.zip<br> -Grain boundary face network for time steps 100 to 5296 at 100 time step resolution</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 8)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>GBCurvApprx_1_to_174.zip<br> Single-grain-boundary-contour-point-resolved curvature estimation tracking data for time step 1 to 174 with 1 time step resolution and all grains</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 10)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>NetworkEvolutionPNG.zip<br> Rendered images of the evolving microstructure at very high resolution and reduced size FullHD</p> <p>PRX2DNetwork.gif and PRX2DNetwork.gifx<br> Video of the evolving microstructure and corresponding gif-x video generation file</p> <p>TrackingParallelRXEVO_Resolution_1.zip<br> TopologyTracer analysis of recrystallized volume fraction over time</p> <p>TrackingParallelSEE1002000.zip<br> TopologyTracer analysis of single-grain-resolved stored elastic energy driving forces segment length averaged</p> <p>TrackingParallelTrackingBK_Resolution_1.zip,<br> TrackingParallelTrackingBK_Resolution_100.zip<br> TopologyTracer analysis tracking backwards (BK) in time the evolution of the successful grains with different temporal resolution</p> <p>TrackingParallelTrackingFW_FID100.zip<br> TopologyTracer analysis tracking forward (FW) in time the metadata for all grains at time step 100</p> <p>TrackingParallelTrackingFW_Resolution_1.zip,<br> TrackingParallelTrackingFW_Resolution_20.zip,<br> TrackingParallelTrackingFW_Resolution_100.zip<br> TopologyTracer analysis tracking forward (FW) in time the evolution of all grains with different temporal resolution</p> <p>MPIEDevBranchPRX2D.zip<br> TopologyTracer analysis rendering of images and analysis scripts</p> <p>MPIEDevBranchPRX2DCapTrack.zip,<br> MPIEDevBranchPRX2DMajorRevPCA.zip,<br> MPIEDevBranchTrackSuccessful02.zip<br> TopologyTracer analysis of capillary tracking data in correlation with size and topology evolution and PCA</p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 6)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_260_to_449.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 260 to 449 with 1 time step resolution</p>
The role of particle, energy and momentum losses in 1D simulations of divertor detachment
<p>Source code, inputs, simulation outputs, analysis scripts and figures used in the paper</p> <p>"The role of particle, energy and momentum losses in 1D simulations of divertor detachment" by B D Dudson, J Allen, T Body, B Chapman, C Lau, L Townley, D Moulton, J Harrison, B Lipschultz.</p> <p>Questions to benjamin.dudson@york.ac.uk .</p> <p>This version is before submission to journal.</p> <p> </p> <p> </p>
Global monthly discharge dataset, derived from dynamical 1-D water-energy routing model (DynWat) at 10 km spatial resolution
<pre>Global 10km spatial resolution discharge dataset at the global scale for all major rivers, lakes and reservoirs. Data are provided at a monthly temporal resolution.</pre>
Dataset for "An alternative to market-oriented energy models: nexus patterns across hierarchical levels"
<p>Dataset used for the publication "Di Felice, Louisa Jane, Maddalena Ripa, and Mario Giampietro. "An alternative to market-oriented energy models: Nexus patterns across hierarchical levels." <em>Energy Policy</em> 126 (2019): 431-443.". The dataset follows the distinction across hierarchical levels as specified in the publication.</p> <p>The same dataset was also used for a case study developed for the MAGIC project, available <a href="http://magic-nexus.eu/case_study/electric-grid-catalonia-illustrations-musiasem">here</a>. </p>
(PRE) Socio-economic and cultural dataset in relation to Persuasive Strategies to boost Energy Efficiency and in the UK, Spain, Greece and Austria
<p>The dataset has been created from obtaining answers from 303 participants of four different countries in the EU (the questionnaire can be studied in <strong>GreenSoul_Questionnaire.pdf</strong>). It is composed by several factors which are explained in different TXT files. All these factors are contained in a "<strong>all_code_final_zenodo.xlsx</strong>" along with their answers by participants. In the following a short descrition of each TXT which explian the dataset is provided.:</p> <p> * <strong>socio-economic_description_not_dependent_of_work</strong><br> - Contains all the information from participants which is irrespective of their current workplace. This file contains typical socio-demographic and cultural attributes from respondents.</p> <p> * <strong>socio-economic_description_dependent_of_work</strong><br> - Contains socio-economic and cultural information from participants which is relevant to the workplace in relation to energy efficient practices in such environment.</p> <p> * <strong>actions-at-work</strong><br> - Are a set of attributes which describe certain practices of employees in relation to energy efficiency.</p> <p> * <strong>persuasive_strategies</strong><br> - Explain the ratings from 1 to 5 that participants attributed to a set of persuasive strategies. These strategies are framed within Phychological Persuasive principles which are also explained in the file.</p> <p> * <strong>all_attributes_together</strong><br> - All the variables together without distinction of the environment where they are applicable.</p> <p>Finally, plots from every construct or attribute are provided in a zip file (<strong>plots_descriptive_analysis_per_city.zip</strong>) which contains the plots uploaded in "PNG" extension</p>
National Energy and Climate Plans - Preliminary analysis on Prosumerism for 9 EU Member States
<p>Preliminary check on the provisions on self-consumption and energy communities in the draft National Energy and Climate Plans (NECPs) of nine EU Member States (BE, DE, ES, FR, HR, IT, NL, PT, UK). The main findings are that only France and Spain put a reasonable emphasis on the importance of self-consumption and energy communities as suggested by RED II. Germany and Italy show some efforts while the NECPs of the other five member states contain only weak or no provisions on prosumerism. Most countries don’t define neither targets nor measures.</p>
Dataset associated with Schyns & Vanham (2019) "The water footprint of wood for energy consumed in the European Union"
<p>Input and output datasets related to the paper Schyns & Vanham (2019) The water footprint of wood for energy consumed in the European Union. <em>Water</em>, 11(2): 206.</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.