Find research datasets worth reusing

opencc-by-sa-4.0Sep 2024View details →

Data for manuscript: "Understanding lower limb haemodynamics: sensitivity analysis of a 0D model"

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Data for "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model"

Data to accompany: O’Neill, J.F., Edwards, T.L., Martin, D.F., Shafer, C., Cornford, S.L., Seroussi, H.L., Nowicki, S., Adhikari, M., Gregoire, L.J.. (2024). "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model in the Cryosphere". The Cryosphere. DOI: 10.5194/egusphere-2024-441 (preprint) Zipped directories called ismip6_expname_8km containing NetCDFs of output data from each experiment, on an 8 km EPSG3031 polar stereographic common grid for ISMIP6. Variable names are the same as those used for ISMIP6 i.e: land ice mass (lim), land ice mass above floatation (limnsw), floating area (iareaf), grounded area (iareag), thickness (lithk), x component of mean velocity (xvelmean), y component of mean velocity (yvelmean), basal mass flux (libmassbffl), acabf (surface mass balance), sftflf (floating ice mask), sftgrf (grounded ice mask), sftgif (ice mask), dlithkdt (ice thickness imbalance), base (elevation at base of ice sheet) and orog (surface elevation of ice sheet). These latter two are only included for the experiments plotted in Figure 11 in "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model in the Cryosphere".   Also included are csv data for summary variables, masked regionally, and by sectors detailed in the main paper. Please contact J ONeill with any questions or requests.

Processed data used for JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations"

This is the processed dataset used in the JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations" by Xiao Ge. Please contact the author (gexiao@tamu.edu) for all the original/processed outputs of R-CESM, and use the following original papers as citations. The dataset used in this research includes: 1. Loop Current Dynamics 2009-2011: LC_*.nc is the processed (reorganized) data for each in-situ station, * represents their station ID <ul> <li>https://digital.library.unt.edu/ark:/67531/metadc955416/</li> <li>https://www.sciencedirect.com/science/article/pii/S0377026516301348?via%3Dihub</li> <li>https://search.dataone.org/view/%7BBD2513E6-3B34-4B7C-BCB9-3C4ED5E8D0FB%7D</li> </ul> 2. Regional Community Earth System Model, R-CESM: <a href="https://zenodo.org/api/records/13932074/draft/files/h.nc/content" target="_blank" rel="noopener noreferrer">h.nc</a> is the bathymetry data of R-CESM; cmpr_*.nc files are provided as examples of the original R-CESM outputs; pvsf_prho_*.nc are the processed (subsampled at the target region and interpolated on potential density layers, derived stream function, potential vorticity, and relative vorticity) R-CESM outputs used in this research; and <a href="https://zenodo.org/uploads/13932074" target="_blank" rel="noopener noreferrer">LC_pv_40hlp_2013.nc</a> is the example of organized processed R-CESM (pvsf_prho_*.nc files) containing potential vorticity and relative vorticity for figures plotting <ul> <li>https://journals.ametsoc.org/view/journals/bams/102/9/BAMS-D-20-0024.1.xml?tab_body=fulltext-display</li> </ul>

opencc-by-4.0Sep 2024View details →

Development and Comparison of Model-Based and Data-Driven Approaches for the Prediction of the Mechanical Properties of Lattice Structures

This dataset comes from the following paper: Chiara Pasini, Oscar Ramponi, Stefano Pandini, Luciana Sartore, Giulia Scalet, Development and Comparison of Model-Based and Data-Driven Approaches for the Prediction of the Mechanical Properties of Lattice Structures, J. of Materi Eng and Perform, 2024. <a href="https://doi.org/10.1007/s11665-024-10199-x">https://doi.org/10.1007/s11665-024-10199-x</a> It contains: <ul> <li>"Notes.pdf" describing all the files uploaded</li> <li>. m of the neural network</li> <li>. inp of the Abaqus finite element simulations</li> </ul>

The raw data for the research "Comparing Neural Network Models Based on Macro Perspective Economic and Environmental Indicators with ARIMA Model in predicting Construction Cost Index in UK"

The raw data for the research "Comparing Neural Network Models Based on Macro Perspective Economic and Environmental Indicators with ARIMA Model in predicting Construction Cost Index in UK". Data collector: Runda Zheng

openapache2.0Oct 2024View details →

Data and code for FishMIP global marine ecosystem model ensemble projections summarised by countries and territories and other selected marine spatial regions.

R code to extract and create data tables and summary plots of FishMIP mean ensemble projections provided are for percentage change in "exploitable fish biomass", which is a proxy for the biomass available to fisheries, consisting of marine animals spanning the size range 10 g to 100 kg: this is typically dominated by fish, but is also inclusive of other animals such as crustaceans and cephalopods. This release contains scripts and summary data for producing figures in Part A of the following report: Blanchard, J.L., Novaglio, C., eds. (2024). Climate change risks to marine ecosystems and fisheries: Future projections from the Fisheries and Marine Ecosystems Model Intercomparison Project. FAO Fisheries and Aquaculture Technical Paper No. 707. Rome, FAO. Please refer to the above report to cite and for more information. The summary data are here: https://github.com/Fish-MIP/FAO_Report/blob/main/data/table_stats_formatted_admin_full.csv Where the column 'spatial_scale' refers to the type of aggregation: FAO_area = High Sea areas grouped by FAO Major Fishing Areas countries = Exclusive Economic Zones countries_admin = Exclusive Economic Zones results aggregated into Administrative Countries Please note that these results can also be visualised and downloaded from our shiny app: https://rstudio.global-ecosystem-model.cloud.edu.au/shiny/FAO_report_shiny/

Occupant Simulation Data based on Honda Accord 2024 Simplified Passenger Model and Full-factorial Sampling with 243 samples and VIRTHUMAN 5, 50, 95 Percentiles

Database with 729 Honda Accord 2014 passenger occupant simulations featuring VIRTHUMAN.

Data for: Antarctic wide subglacial hydrology modeling

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Data set: Modeling of Electron-Transfer Kinetics in Magnesium Electrolytes: Influence of the Solvent on the Battery Performance

Dataset of the continuum simulations generated and used within the paper "Modeling of Electron-Transfer Kinetics in Magnesium Electrolytes: Influence of the Solvent on the Battery Performance", published in ChemSusChem (2021, 14 (21), 4820-4835, DOI: 10.1002/cssc.202101498). The performance of rechargeable magnesium batteries is strongly dependent on the choice of electrolyte. The desolvation of multivalent cations usually goes along with high energy barriers, which can have a crucial impact on the plating reaction. This can lead to significantly higher overpotentials for magnesium deposition compared to magnesium dissolution. In this work we combine experimental measurements with DFT calculations and continuum modeling to analyze magnesium deposition in various solvents. Jointly, these methods provide a better understanding of the electrode reactions and especially the magnesium deposition mechanism. Thereby, a kinetic model for electrochemical reactions at metal electrodes is developed, which explicitly couples desolvation to electron transfer and, furthermore, qualitatively takes into account effects of the electrochemical double layer. The influence of different solvents on the battery performance is studied for the state-of-the-art magnesium tetrakis(hexafluoroisopropyloxy)borate electrolyte salt. It becomes apparent that not necessarily a whole solvent molecule must be stripped from the solvated magnesium cation before the first reduction step can take place. For magnesium reduction it seems to be sufficient to have one coordination site available, so that the magnesium cation is able to get closer to the electrode surface. Thereby, the initial desolvation of the magnesium cation determines the deposition reaction for mono-, tri- and tetraglyme, whereas the influence of the desolvation on the plating reaction is minor for diglyme and tetrahydrofuran. Overall, we can give a clear recommendation for diglyme to be applied as solvent in magnesium electrolytes.

Data set: Modeling of Ion Agglomeration in Magnesium Electrolytes and its Impacts on Battery Performance

Dataset of the continuum simulations generated and used within the paper "Modeling of Ion Agglomeration in Magnesium Electrolytes and its Impacts on Battery Performance", published in ChemSusChem (2020, 13 (14), 3599-3604, DOI: 10.1002/cssc.202001034). The choice of electrolyte has a crucial influence on the performance of rechargeable magnesium batteries. In multivalent electrolytes an agglomeration of ions to pairs or bigger clusters may affect the transport in the electrolyte and the reaction at the electrodes. In this work the formation of clusters is included in a general model for magnesium batteries. In this model, the effect of cluster formation on transport, thermodynamics and kinetics is consistently taken into account. The model is used to analyze the effect of ion clustering in magnesium tetrakis(hexafluoroisopropyloxy)borate in dimethoxyethane as electrolyte. It becomes apparent that ion agglomeration is able to explain experimentally observed phenomena at high salt concentrations.

Paranal Airglow Line And Continuum Emission (PALACE) model: data and code of v1.0

This data and code release is related to the article "PALACE v1.0: Paranal Airglow Line And Continuum Emission model", which has been published in Geoscientific Model Development, Vol. 18, 2025 (https://doi.org/10.5194/gmd-18-4353-2025). The release consists of three .zip files: PMD.zip: 436 ASCII files with data that were used to build and evaluate the model. More details in PMD/pmd_README.txt. PALACE.zip: Python/Cython code for the calculation of the model. More details in PALACE/README.txt. test.zip: Test output of the code for the default parameters (.dat file in alternative ASCII format).

The ECOLOPES Voxel Model: Multi-domain data integration for ontology-aided generative computational design of ecological building envelopes

The research portrayed in this article is part of the research project ‘ECOlogical building enveLOPES: a game-changing design approach for regenerative ecosystems’ funded by Horizon 2020 Future and Emerging Technologies. The overall research project focuses on developing a multi-domain data-driven computational design framework for the design of ecological building enclosures that addresses humans, plants, animals and microbiota. This article focuses on the development of a key component of the computational workflow in which initial designs are computationally initiated generated and analyzed, namely the ECOLOPES Voxel Model that contains and correlates multi-domain spatialised data for the design process, and its interactions with other components of the ontology-aided generative computational design process for ecological building envelopes. This repository contains all relevant data produced in this paper. Extended technical description is available in the Appendix A to the published paper, containing listing and description of individual voxel data layers. Data were exported from the RDB server (PostgreSQL) in text-based, future-proof format (csv).

Data products for "3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico"

Data products for '3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico' by A. Perez-Silva, D. Li, A.-A. Gabriel and Y. Kaneko

opencc-by-4.0Jan 2021View details →

Data and code for 'Influence of cross-correlation on the modelled uncertainty in stress–strain behavior of soft clays'

This dataset contains data and code used in the research work for the manuscript "Influence of cross-correlation on the modelled uncertainty in stress–strain behavior of soft clays". The study considered two case studies, Haarajoki clay and Suurpelto clay. Two settlement calculation methods were used: compression index method and Janbu (tangential stiffness) method. In addition, clay database FI-CLAY/14/856 was extended and used to study cross-correlations between compressibility paramaters at different clay sites. Version 2 of FI-CLAY/14/856 is provided, including some other updates and corrections also. The Monte Carlo simulation with Gaussian copula was implemented with Python in Jupyter Notebook environment. In addition to data and code, supplementary figures are also provided. The contents of the dataset-folder are briefly described below: <ul> <li>1_Data_Oedometer_test <ul> <li>Oedometer test data for Haarajoki clay and Suurpelto clay: <ul> <li>Data tables that include the clay specimen identifications, index properties, and oedometer test results (.xlsx)</li> <li>Oedometer raw data files that include all the available stress-strain measurements of both constant-rate-of-strain and incrementally loaded odometer tests (.xlsx)</li> </ul> </li> <li>Extended clay database FI-CLAY/14/856 (version 2) (.xlsx)</li> </ul> </li> <li>2_Code_Jupyter_Notebooks <ul> <li>Python code used to run the Monte Carlo simulations and to create the results figures (.ipynb)</li> <li>Readme-file (.txt)</li> </ul> </li> <li>3_Figures_Online_Supplement <ul> <li>Scatterplots with histograms that show the simulated compressibility parameters in each case (.pdf)</li> </ul> </li> </ul>   More information on database FI-CLAY/14/856 can be found from the original article (https://www.tandfonline.com/doi/full/10.1080/17499518.2020.1864410) and 304dB datbase compilation by TC304 (http://140.112.12.21/issmge/tc304.htm).

Data set: Huai et al. (2021). JAMC. Quantifying rainfall in Greenland: a combined observational and modelling approach

Abstract Paper. This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients. The dataset contains: Automatic weather station data: AWS-daily.zip: per station daily values of snowfall and rain fall derived from raw precipitation data and for 7 methods to divide between rain and snowfall AWS-factork.zip: per station the factor with which the data is corrected for undercatch AWS-script.zip: the scripts used for the analyses Staffed weather stations: Meteo-daily.zip: per station daily values of snowfall and rain fall derived from the precipitation data and for 7 methods to divide between rain and snowfall Meteo-factork.zip: per station the factor with which the data is corrected for undercatch Meteo-script.zip: the scripts used for the analyses

openother-openJun 2021View details →

Code and data associated with Christiansen et al. 2021 "Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing"

All code and data input and output files (except reference genome and raw sequencing data) needed to reproduce the results of Christiansen et al. 2021 as released on <a href="https://github.com/notothen/radpilot">https://github.com/notothen/radpilot</a> alongside journal publication. See published paper: Christiansen, H., Heindler, F.M., Hellemans, B. et al. Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing. BMC Genomics 22, 625 (2021). <a href="https://doi.org/10.1186/s12864-021-07917-3">https://doi.org/10.1186/s12864-021-07917-3</a>

Research data supporting "Multiscale Molecular Modelling of ATP-Fueled Supramolecular Polymerisation and Depolymerisation"

Raw research data supporting the publication Perego C. et al., ChemSystemsChem 2021, DOI: <a href="https://doi.org/10.1002/syst.202000038">https://doi.org/10.1002/syst.202000038</a>

Supplemental data of publication "Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement".

Supplemental data of publication "Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement". Authors: Morgan Tranter, Maria Wetzel, Marco De Lucia, Michael Kühn Contact: mtranter@gfz-potsdam.de Submitted to Advances in Geosciences (31.06.2021). Special Issue: European Geosciences Union General Assembly 2021, EGU Division Energy, Resources & Environment (ERE) EGU21 Abstract: https://doi.org/10.5194/egusphere-egu21-9832 Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

Isca model data for Flex-UM manuscript (Maher and Earnshaw 2021)

This archive contains the model output generated for the manuscript Maher and Earnshaw (2021). The single data file, IscaSlabOcean.nc, contains a slab ocean Isca simulation using the Frierson default set-up. The Flex-UM and GA7.0 data for this manuscript are available at <a href="https://doi.org/10.5281/zenodo.5700372">https://doi.org/10.5281/zenodo.5700372</a> The python postprocessing and plotting routines for this manuscript are available at <a href="https://doi.org/10.5281/zenodo.5700633">https://doi.org/10.5281/zenodo.5700633</a>

Data from: Building on 150 years of knowledge: the freshwater isopod Asellus aquaticus as an integrative eco-evolutionary model system

Introduction This is a literature database with reference information of all papers that use the freshwater isopod Asellus aquaticus; published between the years 1867 and 2020. This database is intended as a starting point for scientists interested in conducting research on and with this organism. The database is currently only available as a single CSV file; future versions may be made available through a more frequently updated SQL database. The database includes specific information about the subject area and content of each paper, as well as bibliographic information. This repository is associated with the paper "Building on 150 years of knowledge: the freshwater isopod Asellus aquaticus as an integrative eco-evolutionary model system", published in Frontiers in Ecology and Evolution. Details on Methods from the electronic supplement: We used the we online search tools of Web of Science (WOS; Clarivate analytics) by searching for the term "asellus aquaticus" in six relevant databases (BIOSIS, CABI, FSTA, Medline, WOS Core Collection and Zoological Records). The database was accessed with a University License (Lund University). We manually downloaded the results and combined them to a single CSV file in Excel (Microsoft). All further processing was done in the statistical programming language R, version 4.0.2 (R Core Team 2020). From the 1238 obtained records we discarded three papers that were published after the year 2020 to work with completed years only. We used the subject areas assigned by WOS to provide an overview of the fields of science in which A. aquaticus has been most studied. Each paper had between one and ten subject areas assigned by WOS (2845 assignments to 1235 papers, meaning 2.3 assignments per paper, on average). To represent these multiple assignments in relation to the actual number of papers per year, we calculated "fractional assignments" by adding up all assignments to a field per year, divided by the total number of assignments in that year, and then multiplied by the number of papers.  For example, if there were 12 assignments to "toxicology" in 1993, and 133 assignments in 1993, but only 21 papers published, "toxicology" would get a score of 1.9 papers in 1993 (as calculated by = (12/133)*21). In Figure 1, we represent these "fractional assignments" in the top panel, and the total number of assignments in the lower panel. Caption for figure (1) in publication: FIGURE 1 | Over 150 years of research on and with Asellus aquaticus. The figure summarizes published scientific literature on A. aquaticus. We conducted a quantitative literature survey with the search tools of Web of Science (WOS; Clarivate analytics) by searching for the term "asellus aquaticus" in six databases (i.e., BIOSIS, CABI, FSTA, Medline, WOS Core Collection, and Zoological Records). We found 1235 records, published between 1867 and 2020. (A) The graph shows the number of publications per year within a given subject area, as designated by WOS. (B) The graph shows the total number of publications assigned to a specific subject area. The top 10 fields account for 72.58% of all publications, and are indicated by color coding in A and B (multiple assignments are possible, summing up to 2845 assignments). The inset in B shows a wordcloud with the 100 most used keywords from all A. aquaticus’ publications. Furthermore, we compiled all records with relevant information (e.g., title, keywords, research areas, and abstract) to a single file which is available online. More details can be found in the Supplementary Material.