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.
15,519
datasets available to search
ShareScore release 0.9.0
Dataset results
15,519 results for “r”
RZooRoH: an R package to characterize individual genomic autozygosity and identify homozygous-by-descent segments
<p>these are two files used to test the RZooRoH package in the manuscript:<br> RZooRoH: an R package to characterize genomic autozygosity and identify homozygous-by-descent segments<br> A.R. Bertrand, N.K. Kadri, L. Flori, M. Gautier and T. Druet</p> <p>Each row represents a SNP. The files contain first 5 information columns followed by the genotyes (1 row per individual):<br> 1 Chromosome number<br> 2 Marker name<br> 3 Position in bp<br> 4 Allele 1<br> 5 Allele 2</p> <p>Genotypes are coded as 0, 1 and 2 for AA, AB and BB and 9 for missing.</p> <p>The file geno_sim15_5col.txt contains the simulated genotypes: 25000 markers and 500 individuals.<br> The file filtered_soay_5col.txt contains the sheep genotype data: 47365 markers and 110 individuals.</p> <p>The origin of the files is described in the paper.<br> The simulated data set is from Druet and Gautier (2017) whereas the sheep data comes from Kijas et al. (2012).</p>
Data and R code used in the preprint "Parasite intensity is driven by temperature in a wild bird" (doi 10.1101/323311)
<p>Data (as text files) and R code used in the preprint entitled "Parasite intensity is driven by temperature in a wild bird", recommended by <em>Peer Community In Ecology </em>(doi 10.1101/323311). See preprint and supplementary material; some explanations are also included in the R code. </p>
Data and R code associated to the publication: "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity"
<p>This R code and dataset accompany Hanna et al's 2019 publication in Conservation Biology titled "Effects of land use, cover and protection on stream and riparian ecosystem services and biodiversity". Read the "Metadata" tab of the data file and code annotations for more information. </p>
R code and simulation output for Efford, M. G. & Boulanger, J. 2019. Fast evaluation of study designs for spatially explicit capture-recapture. Methods in Ecology and Evolution
<p>R code and simulation output for Efford, M. G. & Boulanger,<br> J. 2019. Fast evaluation of study designs for spatially explicit<br> capture-recapture. Methods in Ecology and Evolution In press.</p> <p>R code draws on previously published R packages 'secr' and 'secrdesign' available from CRAN:</p> <p><a href="https://CRAN.R-project.org/package=secr">https://CRAN.R-project.org/package=secr</a></p> <p><a href="https://CRAN.R-project.org/package=secrdesign">https://CRAN.R-project.org/package=secrdesign</a></p>
Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Rentzsch, R et al.
<p>Supplementary File S2 for the publication 'Predicting Bacterial Virulence Factors - Evaluation of Machine Learning and Negative Data Strategies' by Robert Rentzsch, Carlus Deneke, Andreas Nitsche, and Bernhard Y. Renard</p>
Data and R code used in Delory et al (2019) When history matters: the overlooked role of priority effects in grassland overyielding
<p>This repository contains the raw data and R code used for the following paper: Delory et al (2019) When history matters: the overlooked role of priority effects in grassland overyielding.</p>
Bridge Inspecting with Unmanned Aerial Vehicles R&D
<p>Corresponding data set for Tran-SET Project No. 17STLSU11. Abstract of the final report is stated below for reference:</p> <p>"The project achieves through research including literature, on site interviews, and experimentation: 1) a recommendation for a UAV-based system to practically assist in routine bridge inspection work in the State of Louisiana, 2) the identification and description of advantages, disadvantages, and limitations in the use of UAVs for routing bridge inspection work in Louisiana, and 3) provided recommendations for future work. The Yuneec H520 aircraft and its E90 camera are recommended, as is the need for a boat to be included as part of the system. The recommended system has advantages in reaching portions of the bridge that are difficult to reach by human inspectors and includes sufficient image resolution to assist the bridge inspection process. A disadvantage though, is that of the overburden of regulations both from the FAA and for getting permission to inspect a bridge using a UAV. These regulations my render negligible, any gains in efficiency perceived in the use of UAVs for bridge inspection. Also, the UAV is described by the project as an assistance tool for the manual bridge inspection process and cannot replace the needed work of bridge inspectors, as it has limitations. For example, the UAV cannot perform inspections beneath the bridge deck since it may lose its GPS navigation reference. Likewise, it cannot see beneath the surface to tell of concrete components have subsurface cracks or timbers might be hollow. These tests are still the domain of manual bridge inspection. The project provided recommendations with respect to changes in how inspections should be done using the UAV, i.e. in the pre-inspection phase, needed field studies using the UAV, needed economics alternative-tradeoffs studies, and recommendations for augmenting the aircraft and its instruments. The Second phase, i.e. the Implementation Phase, will utilize the information and educational fruits of the technical research phase for tutorials, seminars and to facilitate feedback surveys with engineering firms, the LADOTD, engineering societies, and students."</p>
Dataset for Wenz et al. Phys. Rev. B 99, 201409(R) (2019), "Quantum dot state initialization by control of tunneling rates"
<p>Collection of the datasets used to generate the figures in the following journal paper:</p> <p>"Quantum dot state initialization by control of tunneling rates"<br> Tobias Wenz, Jevgeny Klochan, Frank Hohls, Thomas Gerster, Vyacheslavs Kashcheyevs, and Hans W. Schumacher<br> PHYSICAL REVIEW B 99, 201409(R) (2019)</p> <p>DOI: 10.1103/PhysRevB.99.201409</p>
Basic Operations in R
<p>In this video we use R for the first time, basic concepts are explained, how to trigger actions, what are functions and variables, where do I get help, and how to do basic calculations.</p>
Data types and Variables in R
<p>This video explains how you store numbers, texts and logical variables in R using scalar and vector variables and also what are matrices and data frames and how we can utilize them in R.</p>
R-Script surface contour: Republic of Moldova project report Free University Berlin
<p>This R-Script supplements (surface contour) the project of the Freie Universität Berlin with the title: <strong>Anwendung geoarchäoogischer Methoden zum Verständnis anthropogener Spuren der Poineşti-Lucaşeuca Kultur in Ivancea-Sub Pădure, Republik Moldau. </strong>The project was carried out by students during the module Projekt I at the Freien Universität Berlin. Fieldwork was conducted 16th - 23rd September 2018in the vicinity of Ivancea (central Moldova), about 30km north of the capital Chisinau. </p>
An exploratory study (with and without time pressure) using mouse dynamics to detect faking-good behavior in the MMPI-2 and PPI-R validity scales
<p>Please find here the dataset generated and analyzed during the study entitled "Can mouse dynamics detect faking-good behavior in personality questionnaires? An exploratory study (with and without time pressure) using the MMPI-2 and PPI-R validity scales". Moreover, here you can find the source code of the experiment to execute the task using MouseTracker software, the code of the statistical analysis and a file containing the instructions to replicate ML model results reported in the original paper.</p>
Post-revision data and R Script for Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.'
<p>Data and analysis file (written in R studio) for the paper Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.' Updated based on reviewer comments and additional analyses requested (master data and analysis filed labelled with 'rev' suffix).</p>
Data and R code used in Baudson et al (2019) Developmental plasticity of Brachypodium distachyon in response to P deficiency: modulation by inoculation with phosphate-solubilizing bacteria
<p>This repository contains the raw data and R code used for the following paper: Baudson et al (2019) Developmental plasticity of <em>Brachypodium distachyon</em> in response to P deficiency: modulation by inoculation with phosphate-solubilizing bacteria</p>
Figure 3 in Shar Mountain National Park (R. North Macedonia) - shelter for caddisfly biodiversity in the country
Figure 3. Male genitalia of Crunoecia bosniaca a) lateral view b) ventral view c) dorsal view.
Applicability of the inverse dispersion method to measure emissions from animal housings - data set & R scripts
<h2>Data availability</h2> <p>Provided are:<br>- raw data of the instruments<br>- R Scripts to reproduce the findings in the publication<br>- R outputs</p> <h2>Scripts</h2> <p>In total, there are 10 scripts provided, of which most of them are needed to reproduce the data in the publication.</p> <p>Below, a brief explanation of the content of the different scripts.</p> <ul> <li>01_Datatreatment_01_Weatherstation.r ## This script reads in the weather station data and makes it ready for further use.</li> <li>01_Datatreatment_02_Sonics.r ## This script reads in the 3D ultrasonic data and makes it ready for further use.</li> <li>01_Datatreatment_03_GasFinder.r ## This script reads in the GasFinder data and makes it ready for further use.</li> <li>01_Datatreatment_04_MFC_Pressuresensor.r ## This script reads in the mass flow controller (MFC) and pressure sensor data and makes it ready for further use.</li> <li>02_Calculation_01_bLS.r ## This script is made to run the bLSmodelR and tailored to the number cruncher of the University of Applied Sciences BFH. The code should also work on your computer but you have to adopt the number of cores.</li> <li>02_Calculation_02_Concentration.r ## This script treats the unprocessed concentration data. It removes false concentrations, applies an intercalibration, and makes the data ready for further use.</li> <li>02_Calculation_03_Emissions.r ## This script calculates emissions and makes it ready for further use.</li> <li>02_Calculation_04_contourXYZ_Plume.r ## This script calculates the plume contours in the XY and XZ plane. This script is not necessary to reproduce the findings of the publication.</li> <li>03_Apply_filter.r ## This script applies the quality filtering and makes the data ready for further use.</li> <li>04_Plots_Tables.r ## With this script one can recreate all the plots and values in the tables of the publication, the supplement, and the initial submission.</li> </ul> <p>Note, for the geometry, there is no script provided. The coordinates of the different sensors and the source are solely provided as R output.</p> <h3>Naming of instruments</h3> <p>The instruments in the publication have different names than in the scripts. In some scripts the final names are also provided but throughout the evaluation the original device names are used. Only in the script 04_Plots_Tables.r are the final names introduced. Below is an overview of what original name corresponds to the final name of the devices:</p> <h4><strong>GasFinder instruments called 'OP' in the publication</strong></h4> <ul> <li>OP-UW = GF26</li> <li>OP-2.0h = GF17</li> <li>OP-5.3h = GF18</li> <li>OP-6.8h = GF16</li> <li>OP-12h = GF25</li> </ul> <p><strong>3D ultrasonic anemometer instruments called 'UA' in the publication</strong></p> <ul> <li>UA-UW = SonicC</li> <li>UA-2.0h = SonicA</li> <li>UA-5.3h = Sonic2</li> <li>UA-6.8h = SonicB</li> </ul> <p><strong>Source</strong><br>In some of the scripts, the source might be called 'Schopf' which is a local term for 'shed'.</p> <h2>Note</h2> <p>This code was written by Marcel Bühler (minor code chunks were originally written by Christoph Häni) and is intended to reproduce the findings of the linked publication. Please feel free to use and modify it (e.g., use it to run different dispersion models), but attribution is appreciated.</p> <h2>Disclaimer</h2> <p>I do not guarantee that everything works. It might be that not all variables were changed to English for better understanding correctly. Unfortunately, it is not possible to provide all the catalogs of the bLS run, as the total size is several 100s of GB. In case you run the bLS model on your own, the result will have a minimal difference, as no bLS run produces the same result twice. This should, however, not alter the findings.</p> <h2>Contact</h2> <p>In case you have questions, please contact Marcel Bühler (mb@bce.au.dk). In case this does not work, Christoph Häni might also be able to help (christoph.haeni@bfh.ch).</p>
Amphibian Species of the World (ASW) - obsolete: Frost, Darrel R. 2018. Amphibian Species of the World
Data from Frost, Darrel R. 2018. Amphibian Species of the World: an Online Reference. Version 6.0. Electronic Database accessible at <p></p>http://research.amnh.org/herpetology/amphibia/index.html. American Museum of Natural History, New York, USA.<p></p>Frost, Darrel R. 2019. Amphibian Species of the World: an online reference. Version 6 (DATE OF ACCESS). Electronic Database accessible at <p></p>http://research.amnh.org/herpetology/amphibia/index.html. American Museum of Natural History, New York, USA. <p></p>https://eol-jira.bibalex.org/browse/TRAM-811 The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
Oregon-R-modENCODE(#25211) wild-type fruit fly (D.melanogaster) lifespan under standard maintenance conditions
<p><span>Aging is a phenomenon that manifests itself as permanent physiological deterioration, resulting in changes like reduction of immune function and fitness-related forms of behavior. Studies on changes in lifespan in response to various environmental alterations can bring knowledge of the mechanisms driving them. To properly conduct these studies, data on lifespan under the standard husbandry conditions are required.</span></p>
R codes prepared for the manuscript, entitled "The roles of Y chromosomal genes in mouse sex spectrum phenotypes"
<p>R codes for the manuscript, entitled "The roles of Y chromosomal genes in mouse sex spectrum phenotypes" </p>
Data files for siderite + R. palustris experiment
<p>Full dataset for the siderite + R. palustris experiment. Includes:</p> <ul> <li>Solution and pellet ferrozine assay data (Excel file)</li> <li>Raman data of samples and standards (Excel file)</li> <li>XRD data of samples and standards (Excel file)</li> <li>Normalized XAS absorption data for all standards used in Fe K-edge XANES (Excel file)</li> <li>Representative least-squares fits of 1) siderite-like (reduced) and 2) oxidized sample endmembers (Excel file)</li> </ul>
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.