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6,766 results for “project”
FUELGAE Project Infographics
<div>Project infographics is developed to support Dissemnation and Communication activities of the FUELGAE project.</div> <div> </div> <div>Funded by the European Union under Grant Agreement 10122151. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environm...</div> <div> <div> </div> </div>
Compilation of Digital Tools on Food Green House Gas Mitigation (CHOICE Project)
<p>A compilation of digital tools to support behaviour change and action to food mitigation measures. The compilation was created for the CHOICE Horizon Europe project (Grant Agreement -101081617).</p>
Projected fire cycle (yrs) for Canada at a 0.25 degree resolution
<p>These rasters represent the projection of future fire cycles for Canada at a 0.25 degree of resolution. The data was produced in three steps:</p> <ol> <li>Future fire cycles were obtain by projecting annual area burned as in Boulanger et al. (2014) (https://cdnsciencepub.com/doi/full/10.1139/cjfr-2013-0372) at the homogeneous fire regime zone scale. Models used here were improved from those used in Boulanger et al. (2014). Projections were conducted for specific time periods (baseline, 2011-2040, 2041-2070 and 2071-2100) under specific anthropogenic climate forcing scenarios (RCP 4.5 and RCP 8.5). Three Earth System models were used i.e., CanESM2, HadGEM2-ES and MIROC-ESM-CHEM.</li> <li>Values obtained at the homogeneous fire regime zone scale were further "downscaled" at a 250m resolution according to vegetation type (cover x age class) following Bernier et al. (2016) (https://www.mdpi.com/1999-4907/7/8/157) using forest attributes of 2011 as assessed in Beaudoin et al. (2014) (https://cdnsciencepub.com/doi/10.1139/cjfr-2013-0401). </li> <li>Values obtained at a 250m resolution were averaged in 0.25x0.25 degree cells.</li> </ol>
CENTAUR project laboratory testing data
<p>This dataset contains results from testing carried out at a laboratory facility at the University of Sheffield (UK) as part of the <a href="https://www.sheffield.ac.uk/centaur">CENTAUR project</a>. CENTAUR is an EC funded Horizon 2020 Innovation Action. The project has developed a system to reduce flood risk in urban areas by utilising existing available storage capacity in urban drainage networks through the use of a gate installed in an existing manhole. The gate is controlled by Fuzzy Logic, using data from level sensors.</p> <p>The laboratory facility is described in the 'CENTAUR_Lab_facility.pdf '. Further details of the sensors and logging system are provided in 'Data_File_Column_Descriptions.csv'.</p> <p>The file 'Test_Record.csv' describes all tests carried out. This dataset contains 83 csv data files in for days when good data was collected, these are zipped into 'DataFiles.zip'. Each csv file within the .zip contains the test results for one day, the files are named with the date of testing in the format yymmdd. The csv data files do not include column headers, but a full description of the data in each column is provided in 'Data_File_Column_Descriptions.csv'. The csv files contain data from all sensors, but the time period of the data from each sensor (or sensor set) and timesteps are not the same, hence for each sensor / sensor set there is a separate time column. The sampling interval for the level sensors is given in column 26 of 'Test_Record.csv', this will be correct for the test period, but outside the tests the interval was often increased and this may be seen in the data files. The gate / FCD sampling interval is the same as the Fuzzy Logic interval in column 27 of 'Test_Record.csv', although the position is only reported when the gate / FCD is active - i.e. not fully open. At the end of a test the FCD will return to the fully open position (100%), but this final datapoint is not recorded. The flow rate and downstream valve position sampling interval are given in column 12 of 'Test_Record.csv'.</p> <p>Test numbers and fuzzy logic version ids are simplified for the journal paper 'Demonstrating a Fuzzy Logic algorithm for real-time flow control in a full-scale laboratory environment' which is currently under review with the Urban Water Journal. A correlation between the information in the paper and in 'Test_Record.csv' can be found in 'Paper_Test_Numbers.csv'.</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641931.</p>
Raw Data of Pilot Plant Runs for CONSENS Project (Case Study 1)
<p>In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and <em>o</em>-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. </p> <p>The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.</p> <p>In the following the contents of the files are explained.</p> <p><strong>NIR_data_AQ15_raw.zip: </strong>Contains Bruker binary files (0-Files) of NIR spectrometer at AQ15 (Location is located subsequently to NMR spectrometer)</p> <p><strong>NMR_spectra_raw.zip: </strong>Contains Spinsolve files (Binarys of FID and Spectrum, DX-Files) of NMR spectrometer. The use of DX-files files is not recommended.</p> <p><strong>PCS_data_csv.zip</strong>: Contains csv-files of the process control system (PCS) including data of mass flow controlers (*_Bilanz.csv), filling level (*_FillLe.csv), pressures (*_pres), temperatures (*_Temp), position of valves (*_Valves). Relevant labels are: BP13 = LiHMDS storage tank, BP12 = aniline storage tank, BP12 = <em>o</em>-FNB storage tank, CM003 and CM004 = tubular reactors, T0041 and T005 = Temperature at reactor exits, P009 and P003 = Pressure at reactor inlets, P006 = Pressure at reactor exits.</p> <p><strong>housing_data_NMR.csv</strong>: Contrains data of NMR enclosure of all four days. Each columns from left to right represent timestamps, bypass pressure (bar), bypass temperature (°C), Gasalarm (logical), bypass actual flowrate (g min<sup>-1</sup>), bypass flowrate setpoint (g min<sup>-1</sup>), bypass density (kg m<sup>3</sup>)</p> <p><strong>matlab_variables_explanation.xlsx</strong>: Explanation of variables used in matlab structure "data_validation_run".</p> <p><strong>data_validation_run.mat</strong>: Matlab structure containing most relevant process data including NMR results, NIR results, housing data of NMR, and process control system data.</p>
Rapid structure determination of microcrystalline molecular compounds using electron diffraction (nanoArgovia Project A3EDPI)
<p>The are the data linked to the publication "Rapid structure determination of microcrystalline molecular compounds using electron diffraction", <a href="https://doi.org/10.1002/anie.201811318">10.1002/anie.201811318</a>. Electron Diffraction data collected with an EIGER X 1M detector (DECTRIS Ltd.).</p> <p>Each tar file contains the raw files in HDF5 format, together with the XDS.INP file used for data integration. Images of the respective crystals have '_img_' in their file names. The log files for recording the stage alpha angle are included with the same name and suffix .txt. See publication for details.</p> <p>NB: The meta-data in the HDF5 files have no meaning, please refer to the respective XDS.INP file for respective information.</p> <p>The crystallographic data (CIF-files) have been uploaded to the ICSD (High--throughput Structural Chemistry with Electron Diffraction) and CSD (https://www.ccdc.cam.ac.uk/) respectively:</p> <p>Paracetamol from Grippostad CCDC 1856579<br> electron structure of MBBF4 CCDC 1856580</p> <p>ZSM-5 x227 CSD 1856581</p> <p>ZSM-5 x331 CSD 1856582</p> <p>ZSM-5 x79 CSD 1856583<br> ZSM-5 x811 CSD 1856584</p> <p> </p>
Glycomics measurements of the retrospective study of the Pain-Omics project
<p>This deposit contains the QCed glycomics data for the patients in the retrospective study of the Pain-Omics FP7 project.</p>
Third harmonic generation images of the lacuno-canalicular network in bone femoral diaphysis of mice from the BionM1 project (space flight)
<p>Data set for 11 samples in 3 groups of Control, Space Flight and Synchro (ground control with space flight housing and feeding conditions). Contains THG images in tif format of 2D mosaic of selected samples and 3D stacks in selected anatomical regions of interest. See readme file for more information.</p>
Confocal fluorescence microscopy images of the lacuno-canalicular network in bone femoral diaphysis of mice from the BionM1 project (space flight)
<p>This data set provides complementary measurements to a separate THG data set of the same study: doi: 10.5281/zenodo.1475906</p> <p>Data set for 1 sample of each of the 3 groups: Control, Space Flight and Synchro (ground control with space flight housing and feeding conditions). Contains confocal fluorescence microscopy images in tif format of 2D mosaic of selected samples and 3D stacks in selected anatomical regions of interest. See readme file for more information.</p>
Supplemental catalogs for "The Sloan Digital Sky Survey Reverberation Mapping Project: Sample Characterization"
<p>We have compiled additional properties for the SDSS-RM sample in several ancillary catalogs. Below are the notes on these supplemental catalogs. There are .readme files for each additional catalog. We also include the quality assurance plots for the global spectral fits.</p> <p><strong>QA-0000-56837.ps.gz </strong>The full set of 849 quality assessment plots for the global spectral fitting. Each plot includes a top panel showing the continuum (brown) and Fe II (blue) model components; the red line is the sum of the two. The cyan diamonds are pixels masked as absorption or bad pixels. The gray brackets near the top of the panel indicate the windows used for the continuum+Fe II fit. The bottom panels present the emission line fits for five line complexes.</p> <p><strong>allqso_sdssrm.fits</strong> A FITS table of all 1214 known quasars in the 7 square degree SDSS-RM field. Only 849 of them received a fiber in the SDSS-RM spectroscopy. This table lists the basic target information of these quasars.</p> <p><strong>QSObased_Expanded_SDSSRM_107.fits</strong> The narrow MgII/FeII absorber catalog for SDSS-RM quasars, following the methodology outlined in Zhu & Ménard (2013). Each entry corresponds to one quasar. The search for narrow absorbers includes systems that have absorber redshift close to the quasar systemic redshift (|dz|<0.04). MgII absorbers blueshifted from the quasar by dz>0.04 and also redward of CIV by dz>0.02 are of high purity. MgII absorbers with |dz|<0.04 or those at wavelength blueward of CIV, or those with FeII detection but no MgII detections (likely due to bad pixels), while included in this catalog, should be treated with caution, and may contain a small fraction of false positives (mainly CIV absorbers).</p> <p>For convenience, we also provide a version of the absorber catalog organized by absorbers (<strong>Expanded_SDSSRM_107.fits</strong>), i.e., each entry corresponds to one absorber system.</p> <p><strong>rmqso32_aegis_multi_lambda.fits</strong> Multi-wavelength data compiled from Nandra et al. (2015) or 32 SDSS-RM quasars in the AEGIS field.</p> <p><strong>spitzer_seip_rm_match_1.5arcsec.fits</strong> Spitzer IRAC and MIPS data from the Spitzer Enhanced Imaging Products (SEIP) source list for 176 SDSS-RM quasars, with a matching radius of 1.5 arcseconds. This file also compiles infrared fluxes (if available) from 2MASS (Skrutskie et al. 2006).</p> <p><strong>spec_2014_BALrobust.csv</strong> List of 95 BALQSOs (including mini-BALQSOs) identified from the first-year coadded spectroscopy. This file includes BAL flags on CIV, AlIII, MgII, and FeII/FeIII. It also includes notes on individual objects.</p> <p><strong>PS1_MD07_LC_sdssrm.fits</strong> PS1 Medium Deep light curves for the SDSS-RM quasars used to compute PS1_NMAG_OK and PS1_RMS_MAG in the main catalog. Note this is the unofficial release of the PS1 MD07 data, which was approved by the PS1 collaboration. These photometric light curves may differ slightly from the final official release of the PS1 Medium Deep field data. </p>
Projected fresh water use from the European energy sector on NUTS2 level by 2050 following EU Energy Reference Scenario 2016
<p>The dataset contains projections of fresh water withdrawal and consumption from the European energy sector on NUTS2 level by 2050 following EU Energy Reference Scenario 2016.</p> <p>The energy sector in this scope includes energy production (production of coal, oil and gas) and energy transformation in oil refineries and power plants (nuclear, solid fuels, oil, gas, biomass and geothermal).</p> <p>The information in provided on NUTS 2 level following the NUTS2 2013 definition.</p> <p>The dataset is explained in more detail in the report <a href="https://ec.europa.eu/jrc/en/publication/projected-fresh-water-use-european-energy-sector">Projected fresh water use from the European energy sector</a>.</p>
Smart Home Sensor and HVAC Control Dataset from the SHAL Demonsrtator of the Aegis Project
<p>The example dataset was produced within the Smart Home and Assisted Living demonstrator of the AEGIS project. IT contains measurements of indoor temperature and HVAC control actions (ON/OFF status and setpoint values), which were be used to extract comfort profiles.</p>
Participatory activities good practices in the field of cultural heritage (REACH project)
<p>The REACH repository of good practices comprises over a hundred and twenty records of European and extra European participatory activities in the field of cultural heritage, with an emphasis on small-scale, localised examples, but including also larger collaborative projects and global or distributed online initiatives. Located in over twenty different countries, the activities showcased here cover a wide variety of topics and themes, from urban, rural and institutional heritage to indigenous and minority heritage; from preservation, and management to use and re-use of cultural heritage. This easy-to-use collection of good practices offers professionals, practitioners, researchers and citizens useful information about activities which could be transferred, adapted or replicated in new contexts.</p>
Ranking data for the eo-Delphi project
<p>The eo-Delphi project (https://osf.io/8f3aj/) created consensus for a core set of outcomes for future studies evaluating the effects of oral corticosteroid therapy in chronic obstructive pulmonary disease (COPD) patients stratified by eosinophil levels. The dataset presented here reports individual ranking scores for proposed outcomes.</p>
EFSA Project on the use of NAMs to explore the immunotoxicity of PFAS (Annexes B, C, D1, E, G, I, K, M, O)
<p>In vitro raw data, RIN values and RNA concentrations, DNA quality assessment, RNAseq outputs and analysis of EFSA Project on the use of NAMs to explore the immunotoxicity of PFAS (OC/EFSA/SCER/2021/13). </p>
Vortex Catalog from Jovian Vortex Hunter Zooniverse citizen science project
<p>This dataset contains the aggregated results from the <a href="https://www.zooniverse.org/projects/ramanakumars/jovian-vortex-hunter/" target="_blank" rel="noopener">Jovian Vortex Hunter citizen science project</a>, where citizen science volunteers labeled images from the JunoCam instrument and determined locations and sizes of vortices.</p> <p>The CSV file contains results from the first workflow and details the consensus from volunteers on different features in each image (given by the Zooniverse Subject ID). There are five categories to choose from:</p> <ol> <li>Vortex</li> <li>Turbulent (i.e. Folded Filamentary Regions: FFRs)</li> <li>Cloud bands</li> <li>Blurry (i.e., image issues)</li> <li>Featureless (there is no discernable feature in the image)</li> </ol> <p>The CSV file also contains an additional column defining the number of classifications of the subject.</p> <p>The JSON file contains the aggregated catalog of vortices and their properties from the second workflow. The format of the JSON file is as below:</p> <p>Each entry contains a dictionary of vortex properties, as shown below. The entry is determined by aggregating the vortex properties across multiple Zooniverse images which share the vortex, and building a consensus from multiple volunteer responses.</p> <pre><code>{ "subject_ids": [array of Zooniverse subject ID for each vortex], "perijove": the perijove corresponding to the image from this vortex was determined "color": the aggregated color of the vortex determined from volunteer responses, "lon": System III planetographic longitude [degree], "lat": planetographic latitude [degree], "x0", "y0": reference coordinate on the Zooniverse crop image for longitude/latitude, "x", "y": coordinate of the vortex center on the Zooniverse crop image "rx", "ry": radius of the vortex in pixel coordinates on the Zooniverse crop image "angle": angle in degree from horizontal of the orientation of the vortex in the Zooniverse crop image, "sigma": 1sigma error in the scale of the vortex, "angular_width": width of the vortex in degrees on the planet, "angular_height": height of the vortex in degrees on the planet, "physical_width", "physical width": width/height of the vortex in km, "extracts": [ array of dictionaries consisting of individual ellipses that make up the vortex consensus ] "colors": { "brown": consensus on the vortex being brown [0-1], "red": consensus on the vortex being red [0-1], "dark": consensus on the vortex being dark [0-1], "white": consensus on the vortex being white [0-1], "white-brown": consensus on the vortex being white and brown [0-1], "white-red": consensus on the vortex being white and red [0-1], "red-brown": consensus on the vortex being red and brown [0-1], } }</code></pre> <p>Each extract is a dictionary containing the following properties. An extract is a single aggregated ellipse on a single Zooniverse image.</p> <pre><code>{ "subject_id": Zooniverse subject ID, "perijove": the perijove when the JunoCam image was taken, "color": the color of the vortex with the highest vote fraction, "lon": System III longitude of the vortex [degree], "lat": planetographic latitude of the vortex [degree], "x0", "y0": reference coordinate on the Zooniverse crop image for longitude/latitude, "x", "y": coordinate of the vortex center on the Zooniverse crop image "rx", "ry": radius of the vortex in pixel coordinates on the Zooniverse crop image "angle": angle in degree from horizontal of the orientation of the vortex in the Zooniverse crop image, "probability": the 1sigma error in the scale of the vortex, "angular_width": width of the vortex in degrees on the planet, "angular_height": height of the vortex in degrees on the planet, "physical_width", "physical width": width/height of the vortex in km, }</code></pre>
Horizon projects network
<p>Horizon 2020 and Horizon Europe are key EU initiatives fostering collaborative research and innovation across Europe. The data about Horizon programmes can be explored via the CORDIS Data Lab at <a href="https://cordis.europa.eu/datalab/" target="_blank" rel="noopener">https://cordis.europa.eu/datalab/ </a> and can be accessed trough <a href="https://data.europa.eu/data/datasets/cordish2020projects" target="_blank" rel="noopener">https://data.europa.eu/data/datasets/cordish2020projects</a> for Horizon 2020 and <a href="https://data.europa.eu/data/datasets/cordis-eu-research-projects-under-horizon-europe-2021-2027" target="_blank" rel="noopener">https://data.europa.eu/data/datasets/cordis-eu-research-projects-under-horizon-europe-2021-2027</a> <br>for Horizon Europe..</p> <p>The <strong>Horizon projects network</strong> <strong>dataset </strong>is a collection of case studies created with the <strong>Horizon intelligence</strong> software [DOI: 10.5281/zenodo.11276687]. Its purpose is to provide an additional method for analyzing the impact of Horizon projects, specifically in terms of collaborations among European organizations, leveraging network analysis and community detection techniques. The dataset has been enriched with NUTS3 geolocation data and name tags for Italian organizations and is segmented by year, covering the period from 2015 to 2029.</p> <p>The dataset includes 3 case studies, each focused on a specific topic, selected using the EuroSciVoc taxonomy: <em>hydrogen energy</em>, <em>electron microscopy</em>, and <em>pandemics</em>. For each case study, the dataset includes:</p> <ul> <li> <p>A set of CSV files:</p> <ul> <li><code>O.csv</code>: Contains <em>organisation </em>unique identifier and attributes.</li> <li><code>P.csv</code>: Contains <em>project </em>unique identifier and attributes.</li> <li><code>W.csv</code>: Describes the <em>participation </em>of each organization in a project for each specific year. The participation is weighted according to the "total cost" of the project, shared proportionally based on the project's duration within that year.</li> </ul> </li> <li> <p>An additional CSV file, <code>activity_type.csv</code>, which provides a description of the codes used to define the activity types associated with each organization.</p> </li> <li> <p>A set of network files representing the collaboration between organizations in any given year (from 2015 to 2029), in interoperable format <code>.graphML</code>. These yearly graphs include centrality measures (degree, strength, coreness) and community labels. More details on <code>.graphML</code>format are provided in <code>format-info.txt</code> file.</p> </li> </ul> <p>The file <code>sample-networks-hydrogen-energy</code> showcases a visual representation of the networks for the first case study. </p>
Efficient Detection of Test Interference in C Projects (Artifact)
<p>This record provides research artifacts for the article "Efficient Detection of Test Interference in C Projects", accepted and to be presented at <a href="https://conf.researchr.org/home/ase-2024">ASE 2024</a>. Please refer to the README.md in the tgz file for details about the artifact and how it relates to the manuscript describing our study. Please also see our related Zenodo record with the container images used in the study: <a href="https://doi.org/10.5281/zenodo.7935821" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7935821</a>.</p>
Excel template for the aggregate database on descriptive representation of the ActEU project
<p>This is the Excel template used to structure the databases that provide data at the legislature / party level for each of the six countries studied in Tasks 4.1 and 4.2 of the ActEU project.</p>
Projection of temperature-related mortality in 854 European cities under climate change and adaptation scenarios
<p>This repository contains the data and results from the paper <strong>Estimating future heat-related and cold-related mortality under climate change, demographic and adaptation scenarios in 854 European cities</strong> published in <em>Nature Medicine</em> (<a href="https://doi.org/10.1038/s41591-024-03452-2">https://doi.org/10.1038/s41591-024-03452-2</a>).</p> <p>It provides projections of excess death rates and burden for the period 2015-2099 for five age groups in 854 cities across 30 countries, under three Shared Socioeconomic Pathway (SSP) scenarios, and four adaptation scenarios. The results include point estimates for five-year periods and four global warming levels, along with 95% empirical confidence intervals. </p> <p>The fully reproducible analysis code using the data and producing the results included in this repository is provided in <a href="https://github.com/PierreMasselot/EUcityProj" target="_blank" rel="noopener">GitHub</a>. The results can be visualised and explored in a dedicated <a href="https://ehm-lab.shinyapps.io/vistemphip/">Shiny app</a>.</p> <h3>Content</h3> <p>This repository contains three zip files, each with an internal codebook:</p> <ul> <li><em>data.zip</em>: contains the input data necessary to run the analysis. It includes historical and projected daily temperature at the city level, age-group specific projections of population and survival rates at the country level, and exposure-response functions extracted from another Zenodo repository (<a href="https://doi.org/10.5281/zenodo.10288665" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10288665</a>). This file also include a script showing how each dataset was extracted for the purpose of this projection study.</li> <li><em>results_csv.zip</em>: contains the full results from the health impact projections. It includes one file for each combination of geographical level (city, country, region or European wide) and scale of reporting (five year periods or global warming levels). </li> <li><em>results_parquet.zip</em>: contains the same information as the <em>results_csv.zip</em> but in a parquet format. This allows for more efficient storage and data reading.</li> </ul> <p>It is recommended to only download <em>results_csv.zip</em> for a quick exploration of the results, or only <em>results_parquet.zip</em> when the results are to be loaded into a software for deeper analysis.</p> <p> </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.