Find research datasets worth reusing

Data for ''A note on systematic biases in the ocean due to the air-sea flux calculation in coupled models''

Data used to in a JAMES publication.   Plotting routines can be found at: https://github.com/RafaelAbel/Coarse_Graining Manuscript DOI: tba

opencc-by-4.0Jan 2019View details →

Data: Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy

We provide the generalised fractional anisotropy connectometry database used in our study titled: Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy.

opencc-by-4.0Jan 2019View details →

Data set associated with the paper "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework"

New data set associated with the revision of the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework:  I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component" The title of the paper has been changed to "Implementation of the Vector Vorticity Dynamical Core on Cubed Sphere for Use in the Quasi-3-D Multiscale Modeling Framework" New simulated data set of the advection test is in the folder ADVEC_NEW; New simulated data set of the barotropic instability test is in the folder BARO_NEW; New simulated data set of the baroclinic instability test is in the folder BCL_NEW

opencc-by-4.0Jul 2018View details →

Data, code, models for "Weakly Supervised Semantic Segmentation for Joint Key Local Structure Localization and Classification of Aurora Image"

Data, code and models for https://ieeexplore.ieee.org/document/8410588/

opencc-by-4.0Jan 2019View details →

Supporting publication for 'Guidelines for reporting 2018 prevalence sample-based data in accordance with SSD2 data model'

These two Excel documents help you to map terms from the matrix catalogue ZOO_CAT_MATRIX used in the aggregated prevalence data model to FoodEx2 codes and offer you examples on how prevalence data can be reported using SSD2

opencc-by-4.0Mar 2019View details →

Model sets and data used in the preprint "Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasite"

Model sets and data used in the preprint "Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasite", reviewed and recommended by Peer Community In Ecology (https://dx.doi.org/10.24072/pci.ecology.100013). See preprint and supplementary materials.

opencc-by-4.0May 2019View details →

Fully synthetic longitudinal real-world data from hearing aid wearers for public health policy modeling

Real-world data from hearing aids and Bluetooth connected smartphones. The associated data report can be found here: <a href="https://doi.org/10.3389/fnins.2019.00850">https://doi.org/10.3389/fnins.2019.00850</a>

opencc-by-4.0May 2019View details →

Viet Nam Technology Catalogue - Technology data input for power system modelling in Viet Nam

Today, innovations and technology improvements within renewable energy are taking place at a very rapid pace. Long-term energy planning is very dependent on cost and performance of future energy producing technologies. This technology catalogue provides  estimates of costs and performance for a wide range of power producing technologies, thereby building one of the key inputs to good energy planning in Vietnam. Due to the multi-stakeholder involvement in the data collection process, the technology catalogue contains data that have been scrutinised and discussed by a broad range of relevant stakeholders including the Ministry of Industry and Trade – MOIT, Vietnam Electricity – EVN, independent power producers, local and international consultants, organizations, associations and universities. This is essential because a main objective is to produce a technology catalogue which is well anchored amongst all stakeholders. The technology catalogue will assist the long-term energy modelling in Vietnam and support government institutions, private energy companies, think tanks and others with a common and broadly recognized set of data for electricity producing technologies in Vietnam in the future.

opencc-by-4.0Feb 2019View details →

Data used in manuscript Spatial modelling of local-scale biogenic and anthropogenic carbon dioxide emissions in Helsinki

This data set includes data used to develop and evaluate carbon dioxide emission modelling component in the Surface Urban Energy and Water balance Scheme (SUEWS). The data files are: <ol> <li>CO2_Model_Parameter_Fitting.zip contains m-files (Matlab) used to calculate parameters for photosynthesis modelling <ul> <li>F_pho_data.mat includes meteorological and EC data used to fit photosynthesis model parameters in Kumpula</li> <li>FitKumpulaData.m calculates the model parameters in Kumpula</li> <li>FitViikkiData.m calculates the model parameters in Viikki</li> <li>Other m-files needed by the above two codes</li> </ul> </li> <li>Data.zip contains measured data used to develop and evaluate SUEWS <ul> <li>KumpulaData2012.txt and TorniData2012.txt include eddy covariance data measured at the two sites in Helsinki</li> <li>SMEARIII_meteorology_2016MM_30.m meteorological data used to fit model parameters in Viikki street trees (see 00 ReadMe_SMEARIII_Meteorology.TXT for details)</li> <li>Viikki_SWC_2016.txt measured soil moisture from Viikki in 2016</li> <li>Kumpula_2016_HH_RLAI6_Output.out is SPP output used to fit model parameters in Viikki street trees</li> </ul> </li> <li>SUEWS_EC_Site_Model_runs: SUEWS input and output files for Kumpula and Torni model runs</li> <li>SpatialRun_input.zip: SUEWS input files for the spatial model run</li> <li>spatmatHel_final.mat: SUEWS output files for spatial model run in mat-format</li> </ol>

opencc-by-4.0May 2019View details →

SET-NAV: WP5: Invert modelling output for the building sector final energy demand and cost data

This data set contains the Invert modelling results for final energy demand for space heating, cooling and hot water in buildings; hourly data for district heating and electricity (for different technologies) for 3-4 building types; annual data for the other energy carriers. It also contains all annual cost (Annuity of investments, O&M, fuel cost ) of electricity generation and / or heat generation and considered efficiency measures. This data is also available and visualised in our dedicated SET-NAV open data platform: The SET-NAV Scenario Explorer: https://data.ene.iiasa.ac.at/set-nav/#/workspaces

Numerical model code, input files and output data for publication "Rapid mixing and exchange of deep-ocean waters in an abyssal boundary current"

Contains numerical model data (code, input files, selected output, matlab diagnostic routines) to supplement publication ``Rapid mixing and exchange of deep-ocean waters in an abyssal boundary current'', by Naveiro Garabato and co-authors. All numerical model data, including any errors, is the responsibility of Sonya Legg. This data set will allow reproduction of simulations, and reproduction of diagnostics shown in plots in the above-referenced paper.

opencc-by-4.0Jun 2019View details →

Multivariate mixed model application to mass cytometry data (processed data)

This bachelor thesis demonstrates the results of mass cytometry data re-analysis using multivariate regression. I reanalyse a dataset by Palgen et al. (2019) using two models: a Poisson log-normal mixed model and a logistic linear mixed model from the R package ‘cytoeffect’ (Seiler et al., 2019). By exposing multivariate patterns and the associated uncertainty profiles in the data, the aim of this analysis is to replicate biological conclusions and uncover new biological findings.

New Zealand native forest plant cover data for Popovic et al. MEE (2019), Untangling direct species associations from indirect mediator species effects with graphical models.

Forest cover measurements were collected at 1246 native forest sites that form part of a network of permanent 20 x 20 m plots spread throughout New Zealand. A total of 1831 plant species were present in these plots, with the most common being herbs, graminoids, ferns, shrubs and trees. Plant cover (in ordinal categories) was assessed for each species in several tiers at different heights. The cover data we analysed (NZ_native_forest_cover.csv) were the maximum cover recorded over all the tiers at the 964 sites identified as native forests, containing 1311 species with at least one presence. NZ_native_forest_species.csv contains species data including species name, exotic/native, and plant type (tree, shrub, etc.), corresponding to the plant species in the columns of NZ_native_forest_cover.csv. We acknowledge the use of data drawn from the Natural Forest plot data collected between January 2002 and March 2007 by the LUCAS programme for the Ministry for the Environment, New Zealand.

opencc-by-4.0Jun 2019View details →

Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"

# README These files contain r data objects and R files that represent the key details of the paper, "Evaluating health facility access using Bayesian spatial models and location analysis methods". The following datasources are available for simulation of some of the ideas in the paper. - dat_grid_sim: simulated data of the grid and grid cells - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data - dat_ohca_sim: simulated OHCA event data - dat_aed_sim: simulated AED location data - dat_bldg_sim: simulated building location data - dat_municipality_sim: simulated municipality information - table_1: Table 1 information containing key demographic data These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R In terms of the paper itself, the functions and code used in the manuscript are located in: * 01_tidy.Rmd - analysis code used to tidy up the data * 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs * 02_model.Rmd - analysis code used to fit the model in INLA * 03_manuscript.Rmd - Full code and text used to create the paper * 04_supp_materials.Rmd - full code and text used to create the supplementary materials The following files are a part of an R package "swatial" that was developed along with the paper. These files are: * DESCRIPTION * NAMESPACE * LICENSE * LICENSE.md * decay.R * spherical-distance.R * test-figure-data-matches.R * test-table-data-matches.R * testthat.R * tidy-inla.R * tidy-posterior-coefs.R * tidy-predictions.R * utils-pipe.R * All files that end in .Rd are documentation files for the functions. ## Regarding data sources Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: "swiss_census_popn_2010_2015.xlsx". These data are put into analysis ready format in the file “01_tidy.Rmd” Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&bgLayer=ch.swisstopo.pixelkarte-grau&lang=en&topic=ech&layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&E=2717616.28&N=1096597.25&catalogNodes=687,696&layers_timestamp=,,2016,2016,,&layers_visibility=true,false,false,false,false,false&layers_opacity=1,1,1,1,1,0.75 For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1 Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&tema=33&id2=61&id3=65&c1=01&c2=02&c3=02 ## Future work In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.

Data and models for automatic scansion experiment Dutch Song Database

This release contains the data used in an <a href="https://github.com/WHaverals/scanner">experiment</a> on automatic scansion for historical Dutch song texts. Aside form the data, two models are included in this release as well. One model is essential for running the code that is part of this experiment (model_s); while the other model is an example of an acquired automatic scansion model (best_model). Item descriptions: <ul> <li>meertens-meter-songs.zip → collection of 23,197 historic Dutch songs (xml-format). These files (and the gathered meta-data) stems from a collaboration project between the <a href="http://www.liederenbank.nl/index.php?lan=en">Dutch Song Database</a> and the <a href="https://dbnl.org">Digital Library for Dutch Literature</a>. All files contain meta-data on the number of beats that is present in individual verse lines. Snippet:</li> </ul> <blockquote> <pre><code class="language-xml"><lg> <l id="s1:l1" met="4" type="-+"> Een Meysken op een Rivierken <rhyme label="a" type="m">sadt</rhyme>,</l> <l id="s1:l2" met="2" type="-+"> So schoon zy <rhyme label="b" type="m">was</rhyme>,</l> <l id="s1:l3" met="4" type="-+"> Sy sadt en verbeyde haer soete <rhyme label="c" type="m">Lief</rhyme>,</l> <l id="s1:l4" met="2" type="-+"> Int groene <rhyme label="b" type="m" corresp="#s1:l2">gras</rhyme>.</l> </lg></code></pre>   </blockquote>   <ul> <li>model_s → model used for syllabification and assignment of lexical stress of (historic) Dutch words. The development of this model was part of a <a href="https://github.com/WHaverals/stresser">previous project</a>.</li> </ul>   <ul> <li>stress_xml.zip → collection of 23,197 historic Dutch songs (xml-format). These are the same songs a the meertens-meter-songs, yet now their individual words are syllabified and annotated for lexical stress. The songs in this folder are used as input during the training process. Snippet:</li> </ul> <blockquote> <pre><code class="language-xml"><l id="s1:l1" met="4" type="-+"> <w token="een"> <s word-stress="1" line-stress="0">een</s> </w> <w token="meysken"> <s word-stress="1" line-stress="0">meys</s> <s word-stress="0" line-stress="0">ken</s> </w> <w token="op"> <s word-stress="1" line-stress="0">op</s> </w> <w token="een"> <s word-stress="1" line-stress="0">een</s> </w> <w token="rivierken"> <s word-stress="0" line-stress="0">ri</s> <s word-stress="1" line-stress="0">vier</s> <s word-stress="0" line-stress="0">ken</s> </w> <rhyme label="a" type="m"> <w token="sadt"> <s word-stress="1" line-stress="0">sadt</s> </w> </rhyme> </l></code></pre>   </blockquote> <ul> <li>gold_scan.zip → 198 Dutch song files (xml-format). These files have been annotated by an expert for line stress.</li> </ul>   <ul> <li>eval_splits.zip → contains the splits made from gold_scan. These are the splits used in the automatic scansion experiment: a development set of 98 songs (used during training), and a test set of 99 songs (used for evaluating the best model after training).</li> </ul>   <ul> <li>best_model.zip → contains the files of an acquired model for automatic Dutch song scansion.</li> </ul>

WASHTREET. Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model

WASHTREET - Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model. This dataset contains raw data and runoff velocities results obtained using seeded and unseeded Particle Image Velocimetry (PIV) techniques in an urban drainage physical model, which is placed in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain). The objective of this work is to obtain an accurate representation of the surface velocity distribution as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>, where a series of high-resolution experiments were performed measuring urban surface wash-off and sediment transport through gully pots and pipes under laboratory-controlled conditions. The experimental facility is a 36 m2 full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. The dataset was used in the work developed in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a>). A detailed description of experimental setup, procedure, postprocessing and results can be consulted in ‘1_TestsDescription.pdf’. 4K resolution and 25 fps raw videos from which frames are extracted for the PIV analysis are provided for each experiment performed in separated zip files (named as ‘2.(test ID)_RawVideos_(configuration).zip’).  Experiments includes three different steady rainfalls of 30, 50 and 80 mm/h of rain intensity and were recorded with and without added fluorescent traces. Data to orthorectify frames from videos are provided in ‘3_SpatialCalibration.zip’. In addition, 60 seconds of steady conditions are extracted for each test and the frames are processed to obtain velocities from a PIV analysis. ‘4_ProcessedFrames_SteadyFlow.zip’ includes the 1500 rectified and processed frames for each experiment to perform the PIV analysis.  Results of runoff velocity distributions are included in ‘5_VelocityResults.zip’. Further details of the rainfall simulator, physical model geometry and more hydraulic and sediment transport results can be consulted in <a href="http://doi.org/10.5281/zenodo.3233918">WASHTREET hydraulic, wash-off and sediment transport experimental data</a>. In addition, data regarding the use of photogrammetry to obtain the elevation map of this physical model is included in <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET Structure from Motion data</a>. The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU) Derived publications: <ul> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. Journal of Hydrology, 575, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. Scientific Data, 7(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., García, J. T., Puertas, J., & Anta, J. (2021). Assessing different imaging velocimetry techniques to measure shallow runoff velocities during rain events using an urban drainage physical model. Hydrology and Earth System Sciences, 25(2), 885-900. <a href="https://doi.org/10.5194/hess-25-885-2021">https://doi.org/10.5194/hess-25-885-2021</a> </li> </ul>

Datasets associated with: Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography

Data associated with the paper 'Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography' by Lembrechts JJ et al., published in Global Ecology and Biogeography. Contains a dataset containing all extracted and measured temperature variables for all 106 measurement plots (climatedata), as well as the climate and species data used in the Species Distribution Models (SDMs).   For details on the content of the table, see the readme-file, for details on methodology, see the original paper.

Supplementary Data for "A framework for the construction of generative models for mesoscale structure in multilayer networks"

Supplementary Data for "A framework for the construction of generative models for mesoscale structure in multilayer networks"

Data for Nguyen Le at al. ""Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices"

Codes and simulation data used in Nguyen Le at al. "“Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices."

Research data supporting "Investigating the accumulation and translocation of titanium dioxide nanoparticles with different surface modifications in static and dynamic human placental transfer models"

Research data supporting the publication: Aengenheister, L. et al., 2019, "Investigating the accumulation and translocation of titanium dioxide nanoparticles with different surface modifications in static and dynamic human placental transfer models",  Eur J Pharm Biopharm. https://doi.org/10.1016/j.ejpb.2019.07.018