Find research datasets worth reusing

Ice-Flow Perturbation Analysis: A method to estimate ice-sheet bed topography and conditions from surface datasets (data)

This dataset accompanies the paper 'Ice-Flow Perturbation Analysis: A method to estimate ice-sheet bed topography and conditions from surface datasets' in Journal of Glaciology, and can be used alongside the provided code to reproduce the figures,

Experimental data and R scripts for simulations and analysis

Zip file including the experimental data and R scripts for simulations and analysis used in the following article: "Colonisation debt: when invasion history impacts current range expansion by Morel-Journel, T., Haond M., Dunan L., Mailleret L. and Vercken E.

opencc-zeroJun 2023View details →

Data for: Meta analysis reveals impacts of disturbance on reptile and amphibian body condition

Ecosystem disturbance is increasing in extent, severity, and frequency across the globe. To date, research has largely focused on the impacts of disturbance on animal population size, extinction risk, and species richness. However, individual responses, such as changes in body condition, can act as more sensitive metrics and may provide early warning signs of reduced fitness and population declines. We conducted the first global systematic review and meta-analysis investigating the impacts of ecosystem disturbance on reptile and amphibian body condition. We collated 384 effect sizes representing 137 species from 133 studies. We tested how disturbance type, species traits, biome, and taxon moderate the impacts of disturbance on body condition. We found an overall negative effect of disturbance on herpetofauna body condition (Hedges' g = -0.37, 95%CI: -0.57, -0.18). Disturbance type was an influential predictor of body condition response and all disturbance types had a negative mean effect. Drought, invasive species, and agriculture had the largest effects. The impact of disturbance varied in strength and direction across biomes, with the largest negative effects found within Mediterranean and temperate biomes. In contrast, taxon, body size, habitat specialisation, and conservation status were not influential predictors of disturbance effects. Our findings reveal the widespread effects of disturbance on herpetofauna body condition and highlight the potential role of individual-level response metrics in enhancing wildlife monitoring. The use of individual response metrics alongside population and community metrics would deepen our understanding of disturbance impacts by revealing both early impacts and chronic effects within affected populations. This could enable early and more informed conservation management.

Data and data analysis for "Human Preferences for the Visual Appearance of Desks: Examining the Role of Wooden Materials and Desk Designs"

Data and data analysis for the article "Human Preferences for the Visual Appearance of Desks: Examining the Role of Wooden Materials and Desk Designs".

Data of "A micromechanical Mean-Field Homogenization surrogate for the stochastic multiscale analysis of composite materials failure"

Id title = "A micromechanical Mean-Field Homogenization surrogate for the stochastic multiscale analysis of composite materials failure" journal = International Journal for Numerical Methods in Engineering year = 2023 volume = 124 pages = 5200-5262 doi = 10.1002/nme.7344 authors = "Calleja, Juan Manuel and Wu Ling, and Nguyen, Van-Dung and Noels, Ludovic" If you use these data or model, we would be grateful if you could cite this above paper Software Requires GMSH and Python 3 with packages numpy, matplotlib, sklearn (scikit-learn), os, pickle, scipy, pandas, cvs, math, seaborn. Each folder contains readme that will help the user to navigate through the data. To run the model you need the open source code <a href="http://gitlab.onelab.info/cm3/cm3Libraries">https://gitlab.onelab.info/cm3/cm3Libraries </a>but you need to request access to cm3MFH as well Directories <ol> <li>Main: Contains fast and easy access to the plots presented in the paper. The readme contained in this plot specifies the plots that are run with each code.</li> <li>1_SVE_Generator:Contains the files needed for the generation of the SVE, the statistical properties of the microstructure, and PLY samples for the full-field simulations, as well as the used samples</li> <li>2_Full_Field: contains the extracted data from the FF composite realizations, as well as the used random SVE geometries.</li> <li>3_Identification: Contains the identification code to find the effective parameters for each SVE realization as well as the obtained identification results.</li> <li>4_Generator: Contains the generated set of parameters for the 25 and 45 micrometer squared SVEs as well as the codes for the new data generation, the file with the generated data and the plots related with the MF-ROM random parameters and their cross-relations shown in Sections 2.5.2, 3.2.3 and 4.</li> <li>5_Tests: Contains all the information concerning the tests used for the verification of the MF-ROM and the ply and experimental compression results.</li> <li>MFH_vs_FF: Allows to easily test the inverse identification process through the use of random SVEs and verify the performance of the identified MFH parameters against its full-field counterpart.</li> </ol> Plot of figures Figure 9 : Run "python plot_Gc.py" which can be found in folder Main/Full_Field_Energy Figure 10: Run "python3 PDF_HIST_Gc.py", which can be found in folder Main/Histograms Figure 23: Run "python3 plot.py" which can be found in folder Main/MFH_FF_Comparison Figure 24: Run "python3 plot.py" which can be found in folder Main/MFH_FF_Comparison Figure 27: Run "python3 Correlation_Graphs_25.py contained in folder Main/Distributions_25_Micrometer_SVE Figure 29: Run "python3 PDF_HIST.py" which can be found in folder Main/Histograms Figure 30: To obtain the data used in this figure, run "python3 DistanceCorrelation_25.py" which can be found in folder /4_Generator Figure 31: To obtain the data used in this figure, run "python3 DistanceCorrelation_45.py" which can be found in folder /4_Generator Figure 32: Run "python3 Correlation_Graphs_25.py" which can be found in folder Main/Distributions_25_Micrometer_SVE Figure 33: Run "python3 Correlation_Graphs_25.py" which can be found in folder Main/Distributions_25_Micrometer_SVE Figure 34: Run "python3 Correlation_Graphs_25.py" which can be found in folder Main/Distributions_25_Micrometer_SVE Figure 36: Run "python3 plot_New.py" which can be found in folder Main/PlyTests Figure 46: Run "python3 plot_Test.py" which can be found in folder Main/CompressionExperiment Figure B3: Run "python3 MicroStrAna.py" which can be found in folder Main/MicroStructStatistics Figure B4: Run "python3 MicroStrAna.py" which can be found in folder Main/MicroStructStatistics Figure D5: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D6: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D7: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D8: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D9: Run "python3 PDF_HIST_B.py" which can be found n folder Main/Histograms Figure D10: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D11: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D12: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D13: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure D14: Run "python3 PDF_HIST_B.py" which can be found in folder Main/Histograms Figure E15: Run "python3 Correlation_Graphs_45.py" which can be found in folder Main/Distributions_45_Micrometer_SVE Figure E16: Run "python3 Correlation_Graphs_45.py" which can be found in folder Main/Distributions_45_Micrometer_SVE Figure E17: Run "python3 Correlation_Graphs_45.py" which can be found in folder Main/Distributions_45_Micrometer_SVE Figure F18: Run "python3 plot_Convergence_25.py" which can be found in folder Main/Convergence Figure F19: Run "python3 plot_Convergence_45.py" which can be found in folder Main/Convergence

Data and R code for: "Global meta-analysis shows reduced quality of food crops under inadequate animal pollination"

R code, data, and metadata for the study "Global meta-analysis shows reduced quality of food crops under inadequate animal pollination"

Raw Taxi Data for the d+Au direct photon analysis

Raw Taxi Data for the d+Au direct photon analysis. This files are primarily intended for building software images.

opencc-by-4.0Dec 2022View details →

Data for "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed"

This folder holds the data for the paper "Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed" (in submission) More information regarding this paper and the data is given in the GitHub repository (https://github.com/sgielis/WT1_TCR) The raw folder contains all MiXCR files for the two studied WT1 epitopes and two VZV epitopes. The VZV epitopes were not taken into account in this paper, but were used to build VZV-specific TCRex models for another paper [in submission]. Since all TCRs for the 4 epitopes were sequences together, this data was used for quality control purposes as explained in the paper. Following 4 folders are present: <ul> <li>run1: TCR data from the first run for WT1-126, WT1-37 and IE62</li> <li>run1_orf18: TCR data from the first run for ORF18</li> <li>run2: WT1-37 data filtered on high and low threshold gating.</li> <li>run 3: extra TCR data for WT1-126, WT1-37 aligned with MiXCR</li> </ul>

First-order phase transitions in Yang-Mills theories and the density of state method---data and analysis code release

Data release for paper: Lucini, B., Mason, D., Piai, M., Rinaldi, E., & Vadacchino, D. (2023). First-order phase transitions in Yang-Mills theories and the density of state method. arXiv preprint arXiv:2305.07463. This data release comprises of: Importance sampling results: Input and output files for PureGauge file of HiRep (https://github.com/claudiopica/HiRep) and csv files contains analysis of results. LLR results: Input files for LLR_HB for a modified version of HiRep for the heat bath LLR algorthim with umbrella sampling (https://github.com/dave452/Hirep-LLR-SU) and some csv files containing analysis of output. Analysis code within the LLRAnalysis.zip, it contains the code and the conda environment.

Unlocking the Potential of Health Data: A Distributed Analysis Approach based on Personal Health Train Infrastructure

While there is a great availability of medical datasets, they are usually focused on a specific research question. This is useful for making experiments transparent and reproducible, however, these datasets can be more efficiently used in other kinds of analyses, where it not for data privacy issues. The Personal Health Train (PHT) provides a distributed analysis infrastructure that follows the FAIR principles and gives control to the data owners (providers) about how their data are used by scientists or other users (consumers).

opencc-zeroJul 2023View details →

Data from: A phylogenetic analysis of Marcetia (Melastomataceae, Marcetieae) and three new sprawling species from Bahia, Brazil

Binary images of leaves and anther connectives of Marcetia alba, M. barbadensis, M. minima, and M. serratifolia. These images were used to generate outlines for the shape analyses in Momocs.

Geo-gender-based analysis of human health data

Data supporting analysis in "Geo-gender-based analysis of human health: the presence of cut flower farms can attenuate pesticide exposure in communities, yet women remain most vulnerable"

opencc-zeroJul 2023View details →

Data for: Developmental plasticity in anurans: meta-analysis reveals effects of larval environments on size at metamorphosis and timing of metamorphosis

Many anuran amphibians (frogs and toads) rely on aquatic habitats during their larval stage. The quality of this environment can significantly impact the overall lifetime fitness and dynamics of the population. Over 450 studies have been published on the impact of the environment on anuran developmental plasticity, yet we lack a synthesis of these effects across different environments. We conducted a meta-analysis and used a comparative approach to understand whether developmental plasticity in response to different larval environments produces predictable changes in metamorphic phenotypes. We analyzed data from 124 studies spanning 80 anuran species and six larval environments and showed that interspecific variation in mass at metamorphosis and the duration of the larval period is partly explained by the type of environment experienced during the larval period. Phylogenetic relationships among species were not associated with variation in mass at metamorphosis plasticity or duration of the larval period plasticity. Larval environments tended to reduce mass at metamorphosis relative to control conditions, with the degree of change depending on the identity and severity of environmental change. Higher temperatures and lower water levels shortened the duration of the larval period, whereas less food and higher densities increased the duration of the larval period. Our results provide a foundation for future studies on developmental plasticity, especially in response to global changes. This study provides motivation for additional work that links developmental plasticity with fitness consequences within and across life stages, as well as how the outcomes described here are altered in compounding environments.

opencc-zeroJul 2023View details →

Data from: Transcriptome analysis reveals the mechanism underlying rapid changes in the early phase brain of bi-directional sex change in Trimma okinawae

Teleost fish exhibit remarkable sexual plasticity and display divergent developmental systems including hermaphroditism. One of the more fascinating model systems of sexual plasticity is socially controlled sex change, which is often observed in coral reef fish. The Okinawa rubble goby, Trimma okinawae, is a bi-directional sex change fish that can rapidly change its sex in both directions depending on social circumstances. Although behavioral and neuro-endocrinal sex change occurs within an hour and is believed to trigger gonadal changes, the underlying mechanisms remain poorly understood. In this study, we conducted a de novo transcriptome analysis of the T. okinawae brain and identified genes that were differentially expressed between the sexes and genes that were immediately controlled by social stimulation causing a sex change. We found that a larger number of genes are regulated during the male-to-female transition compared with a change from female to male. Several genes showed concordant expression shifts regardless of the sex change direction. Furthermore, some were associated with histone modification in nerve cells and regulated in the same direction. Overall, we identified genes that regulate the rapid behavioral and neuroendocrinal control of sex change and provide insight into the mechanism of sexual plasticity in teleost fish.

Computer Code and Data - Determination of server location in emergency care systems: an index proposal using Data Envelopment Analysis and the Hypercube Queuing Model

Computer code and data related to the research project "Determination of server location in emergency care systems: an index proposal using Data Envelopment Analysis and the Hypercube Queuing Model".

Experimental data and analysis of performances of dual-type temperature probes

Experimental data, VBA software, and data analysis resulted from an investigation of the performances of prototypes of dual-type temperature probes, that were used for testing the new concept of dual-type thermometers. Dual-type thermometers enable in-situ determination of thermocouple drift. The basic idea behind the concept is that thermocouple drift can be continuously monitored in situ by placing an additional and different temperature sensor in close proximity. The essential requirement for this additional sensor is that it experiences a drift that is lower than the drift of the monitored thermocouple. A drift of a thermocouple can be determined by an algorithm that monitors, and over time compares, the differences in its temperature readings and the readings of an additional (reference) sensor.

Enhancing stock price data analysis through variants of principal component analysis

The dataset used in the research titled "Enhancing stock price data analysis through variants of principal component analysis". It includes the daily closing prices of top 100 stocks in S&P500 from 29th March 2020 to 28th March 2023.

Performance Analysis of LoRa in Indoor Settings: A Data Descriptor

This work is a description of the experiment conducted to understand the reception of LoRa in closed environments, such as a building. The experiment was carried out on 04/05/2023, in the NW1 building of University of Bremen. The data’s primary goal is to provide researchers with the understanding of factors such as distance, obstacles, interference with other wireless devices that dictates LoRa’s performance.

opencc-by-4.0Oct 2022View details →

An infoveillance analysis of public interest, national data and wastewater monitoring in Wales, UK

Infoveillance, wastewater and national data.R - The R script used for the analyses and figures present in the manuscript.   R functions: flattenCorrMatrix.R -A function for correlation analysis cormtest.R - A function for correlation analysis   Data files: Medical data.csv - Data extracted from the UK government portal for COVID-19 cases, deaths and vaccinations South Wales qPCR data.csv - qPCR data for different South Wales sites on each date, with ‘signal’ denoting the signal of SARS-CoV-2 detection in wastewater samples Wales GT data.csv - Google Trends relative search volume data extracted directly from Google Trends for the region of Wales

Data analysis for "Wellbeing, loneliness, health-related quality of life and perception of technology of older adults in Slovenian senior homes"

We present datasets data analysis conducted in R for the article"Wellbeing, loneliness, health-related quality of life and perception of technology of older adults in Slovenian senior homes".