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.
1,646
datasets available to search
ShareScore release 0.9.0
Dataset results
1,646 results for “plot”
Oakland Cemetery: Plot 62
A 3D rendering of a headstone located in Section 1 / Plot 62 at Oakland Cemetery in Atlanta, GA. Source: Objaverse 1.0 / Sketchfab
Interior of Plot 22, Sheffield, UK.
Plot 22 is a multipurpose creative space at 22 Exchange Street, Sheffield, UK. This is the right corner of the first space you go into, with art by Trik 9 (the female figure in the middle) and others. (I'd like to credit the others but I don't know their names -- please comment if you know.) There is a bench extending out from the wall underneath the Trik 9 head, but the reconstruction has not captured that. 3D reconstruction using Meshroom and Meshlab, from photos taken in March 2021. Source: Objaverse 1.0 / Sketchfab
A scan of the freshly planted plot
Quick scan using 80 photos of the garden plot using Visual SfM and an iPhone while watering the garden this morning. Source: Objaverse 1.0 / Sketchfab
Data from: Sampling origins and directions affect the minimum sampling area in forest plots
<p><span>The minimum sampling area (or minimum area), representing the smallest space </span>that reflects the species composition and characteristics of a plant community, is estimated using species-area relationships (SARs) for designing and managing biodiversity conservation. However, the sampling design's effect on the determination of the minimum area has rarely been systematically evaluated. In this study, we used tree census data from three forest dynamic plots of 25–60 ha in different climatic zones in China to calculate the minimum areas of woody plants in the plots and analyze the effects of species richness and topographic heterogeneity on the areas by changing sampling origins and directions. Our findings reveal that the estimated size of the minimum areas varied significantly with sampling origins and directions, with a difference of approximately 1.5–2 times in forest plots. Topographic heterogeneity affected the minimum area through changes in species composition, while species richness had only a weak impact. These results suggest the importance of considering the sampling origin and direction design when utilizing SARs to estimate the minimum area and species diversity in plant communities, which contributes to a better understanding of vegetation characteristics and the minimum area required for censuses in heterogeneous habitats.</p>
Stem data from first three censuses on the University of California Santa Cruz Forest Ecology Research Plot
<p>Here we present stem-based data from the first three censuses of the 16-ha UC Santa Cruz Forest Ecology Research Plot, located in the Mediterranean climate forest of coastal central California, USA. The forest includes both mixed evergreen forest and redwood-dominated forest, and is recovering from significant logging disturbance in the early 20th century. Each woody stem with diameter larger than 1 cm has been mapped, tagged, identified, and measured, with censuses on a ~5-year interval. The first census (FERP1) began in 2007, and included just 6 ha. During FERP2, begun in 2011, the plot was expanded to 16 ha. The FERP3 census was begun in 2017. The community includes 34 woody species, including 4 gymnosperm and 9 angiosperm tree species, 18 species of shrubs, and 3 species of lianas. Across the three censuses, we report identity, size, location, and mortality data from 48,556 stems of 31,206 mapped individuals.</p>
3D vegetation scans of DivResource experiment plots (Bad Lauchstädt, Germany)
<p>Meta data:</p> <ul> <li>Place and time of recording: Germany, Bad Lauchstädt, UFZ research station, DivResource experiment, 11.09.2023</li> <li>Specification of the type of smartphone used: iPhone 13</li> <li>App used: Scaniverse</li> <li>Brief information on the project context: Pilot test to create 3-demensional animations of vegetation plots with smartphone and 3D scanning app</li> </ul>
Data on arthropod abundance in tropical forest restoration plots with high or low plant phylogenetic diversity
<p>Consideration of plant phylogenetic diversity in ecological restoration carries substantial potential, as communities with a greater diversity of lineages with older evolutionary histories can increase the diversity of niches and thus are likely to recover larger species networks than communities clustered in specific clades with reduced variation in functional traits. In this study, we experimentally assessed how arthropod communities were affected by the phylogenetic diversity of a set of tropical tree species. We established 12 experimental restoration plots with either high or low plant phylogenetic diversity, while maintaining constant the number of plant species. After one and three years, arthropods with different feeding habits (herbivores, predators, pollinators, and detritivores) were collected and identified as morphospecies or operational taxonomic units using metabarcoding techniques. We provide insights on the influence of plant phylogenetic diversity on arthropod abundance and species diversity, particularly among predator, pollinator, and detritivore common and dominant species, which increased with plant phylogenetic diversity. The trend, however, was the opposite for the diversity of herbivore common and dominant species, which decreased as plant phylogenetic diversity increased. These findings highlight the importance of considering plant species richness when designing restoration strategies, but also their evolutionary histories, as the same number of plant species can produce different outcomes for higher trophic levels, as a function of their phylogenetic relationships. </p>
Data on soil variables (with plot IDs) and grassland species traits used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. Journal of Vegetation Science, 35, e13259. Available from: https://doi.org/10.1111/jvs.13259
<p>File <a href="../api/records/10983049/draft/files/Plot_IDs_990ua.txt/content" target="_blank" rel="noopener noreferrer">Plot_IDs_990ua.txt</a> contains the IDs of the 1-m2 plots used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. The plot data are stored in the sPlot database (PPBio South Brazilian Grassland Database).</p> <p>File <a href="../api/records/10983049/draft/files/E_990ua_21SoilVar.txt/content" target="_blank" rel="noopener noreferrer">E_990ua_21SoilVar.txt</a> contains data on soil variables evaluated in the 250 m transects, but here expanded to the 990 1-m2 plots (each transect was sampled using 10 1-m2 pots).</p> <p>File <a href="../api/records/10983049/draft/files/B_769spp_4t.txt/content" target="_blank" rel="noopener noreferrer">B_769spp_4t.txt</a> is the species trait database collected in the framework of several research projects in the Quantitative Ecology Lab (EcoQua) and Grassland Vegetation Studies Lab (LevCamp) of Universidade Federal do Rio Grande do Sul (UFRGS). Data gaps were filled by compiled from the TRY database and data imputation.</p> <p> </p> <p> </p>
Inference products and plotting code for "Some Times in Standard Cosmology"
<p>This zip file contains the Monte Carlo Markov chains (MCMC), the plotting codes, and the figures for the paper "Some Times in Standard Cosmology" by Lukas Tobias Hergt and Douglas Scott (<a href="https://arxiv.org/abs/2411.07703">arXiv:2411.07703</a>):</p> <ul> <li>The folder <code>MCMC__LCDM__PR3_lowlTT_PR4_LoLLiPoP-lowlEE_HiLLiPoP-TTTEEE_lensing</code> contains the MCMC run generated with Cobaya. For details about theoretical model, input parameters, and likelihoods refer to the <code>.yaml</code> files therein or to information in the corresponding paper.</li> <li>The <code>some_times_in_standard_cosmology.py</code> file was used for the post-processing of the MCMC chains; specifically, to compute the physical times, which are not standard derived parameters.</li> <li>The <code>some_times_in_standard_cosmology.ipynb</code> file contains the plotting code and the <code>some_times_in_standard_cosmology_sympy.ipynb</code> file contains derivations of the 2-fluid solutions. We additinally provide the <code>some_times_in_standard_cosmology.html</code> and <code>some_times_in_standard_cosmology_sympy.html</code> files to allow for easy read access via a browser.</li> <li>The PDF files <code>some_times_in_standard_cosmology.pdf</code> and <code>some_times_in_standard_cosmology_2d.pdf</code> are the two figures published in the paper.</li> <li>The <code>.tex</code> files contain the data used for the tables in the paper.</li> </ul>
Input files, plotting scripts, and figures for "Smoldering combustion in cellulose and hemicellulose mixtures: Examining the roles of density, fuel composition, oxygen concentration, and moisture content"
<p>This bundle of files contains all the <a href="http://reaxfire.com/trac/gpyro">Gpyro</a> input files, data, plotting scripts, and figures for "Smoldering combustion in cellulose and hemicellulose mixtures: Examining the roles of density, fuel composition, oxygen concentration, and moisture content". The README.txt file contains additional details about the contents.</p>
Updated SpMM and SpGEMM Plots
<p>Updated SpMM and SpGEMM plots IPDPS submission "RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs."</p>
Fig. 1. Map with studies plots, 1–18 in Terrestrial Molluscs Of The Tsyr-Pripyat Area In Volyn (Northern Ukraine): The First Findings Of The Threatened Snail Vertigo Moulinsiana In Mainland Ukraine
Fig. 1. Map with studies plots, 1–18 — see "Material and methods".
AR6 WG3 Plots and Processing
<p>Repository reproducing plots and processing used in AR6 WG3 made by Zebedee Nicholls, Malte Meinshausen and Jared Lewis.<br> <br> For questions and comments, please contact Zebedee Nicholls (zebedee.nicholls@climate-energy-college.org), Jared Lewis (jared.lewis@climate-resource.com) and Malte Meinshausen (malte.meinshausen@unimelb.edu.au). For full details, please see https://gitlab.com/magicc/ar6-wg3-plots-and-processing.</p>
Data and plotting code for "Energetic electron scattering by kinetic Alfvén waves at strong magnetic field gradients of dipolarization front"
<p>This publication includes the dataset and plotting code for reproducing results and figures of the manuscript "Energetic electron scattering by kinetic Alfvén waves at strong magnetic field gradients of dipolarization front", which was submitted to Physics of Plasma for potential publication. In this paper, we use test particle simulations to study energetic electron pitch angle and momentum scattering driven by kinetic Alfvén waves, at the magnetic field gradients associated with the dipolarization front, current sheet and plasma sheet fields in the magnetotail. </p> <p>The simulation data contains time history of 1000 test particle trajectories, momentum, energy, and KAW wave phases recorded every 0.001 second. Each simulation for different electron energies and pitch angles has a size of over 1 GB, so here we have only included one example of test particle simulation run associated with Figure 3. Only the final results of pitch angle diffusion coefficients are provided associated with Figure 4. A full set of time history results of all test particle simulation runs for Figure 4 will be available upon reasonable request (yshen@epss.ucla.edu). </p> <p>Detailed descriptions:</p> <p> PoP_figure_1.m --- Matlab plotting code for reproducing magnetic field model and geometry for Figure 1.</p> <p> PoP_figure_2.m --- Matlab plotting code for reproducing resonant energy as a function of wave normal angle, electron pitch angle, and field model parameters in Figure 2.</p> <p> PoP_figure_3.m --- Reading test particle simulation data and plotting code for reproducing Figure 3. Please ensure proper directory setting to read test particle data files. </p> <p> PoP_figure_4_5.m --- Reading saved bounce-averaged diffusion coefficient data and plotting Figure 4 and Figure 5.</p> <p> Daa_Energy_alpha_ad3xp15_e1.csv --- Electron diffusion coefficients driven by KAW scattering as a function of energy and pitch angle obtained from test particle simulations. KAW wave amplitude is set to 1 mV/m. Electrons are initiated from a position of x=150 km within the dipolarization front.</p> <p> Tau_Energy_alpha_xp15.csv --- Electron bounce periods as a function of energy and pitch angle based on numerical test particle simulations without KAW input.</p> <p> pKAW_1000p_dify_E100keV_PA5_Daa_E4_pop.zip --- Data files containing 1000 test particle trajectories, momentum and adiabatic invariant. This one single run is for electrons with an energy of 100 keV and a pitch angle of 5 degree, under influence of KAW wave electric field of 4 mV/m. This dataset is used to plot Figure 3. </p> <p> pKAW_1000p_dify_init_Ppara_mue_E100_PA4_Daa_E4_pop.dat --- initial parallel momentum and first adiabatic invariant of 1000 test particles. Read this file for plotting Figure 3. </p> <p> Bxyz.m --- calculate model magnetic field for given positions in x, y, and z</p> <p> FAC.m --- convert local x, y, z coordinates to field-aligned coordinates</p> <p> gradB.m --- calculate the gradient of magnetic field for given positions in x, y, and z</p> <p> E_to_pnorm_hsr.m --- calculate normalized momentum based on relativistic electron energy</p> <p> mysubplot.m --- plotting function to replace subplot routine of Matlab</p> <p> </p> <p> </p>
Tree inventory data of P. menziesii var. menziesii (= viridis) (Schwerin) Franco in Pavari's Plot 412 ninty years after plantation.
<p>This dataset containing the historical series of dendrometric data of a Douglas fir (<em>P. menziesii var. menziesii (= viridis) (Schwerin) Franco)</em> plantation. Implemented in 1932, the plantation is located in place “Rio di Mercurella”, in the Tyrrhenian coastal mountain range in Calabria (Southern Italy). The experimental plot has been identified as Plot 412 and its Google Earth’s coordinates are 39°20'11.55"N e 16° 4'49.40"E. The forest stand is characterized by trees with a relevant role for forest community biodiversity.</p> <p>In 1940, the monitoring of this stand has been started. In this dataset, four of all inventories have been reported. Until 2013, these inventories have been carried out by Istituto Sperimentale di Selvicoltura and Unità di Ricerca per la Selvicoltura in Ambiente Mediterraneo, now incorporated in CREA Research centre of Forestry and Wood which has taken over the last two inventories.</p> <p>90 years after is plantations, in Plot 412 a total analysis has been performed. The following data have been collected: position, number, Diameter at breast height (DBH) of all trees, total height (Ht) of a sample of trees. All data have been elaborated to determine the mean dendrometric parameters as basal area (BA) and Volume (V). Volume of tree was calculated using the local volume table elaborated by Avolio in 1987 and it was integrated with measurements to model trees by Avolio e Bernardini in period 1988-1996.</p> <p>The data collected constitute a fundamental contribution to assess the health and stability of this forest stands. They represent an important historical source and evidence of first experimental test of the introduction of Douglas fir that must also be monitored in the future in Calabria.</p>
Plots of 1962 and 1983 lava flows and scoriae in Miyakejima
<p>Thermomagnetic curves (jst), hysteresis loops (hys), and Arai diagrams with Zijderveld diagrams of Thellier results (thl) by site.</p>
Raw Data of the plots presented in the article entitled "Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis"
<p>This is the collection of raw data for the graphical items presented in the article with given details. </p> <p>This research has received funding from the Swedish Energy Agency (43521-1) and in part by Swedish Research Agency Council (VR, 2018-03462) and the European Union’s Horizon 2020 research and innovation program under the grant agreement No 863222.</p>
Summary data for plots in: Eco-evolutionary extinction and recolonization dynamics reduce genetic load and increase time to extinction in highly inbred populations
<p>Understanding how genetic and ecological effects can interact to shape genetic loads within and across local populations is key to understanding ongoing persistence of systems that should otherwise be susceptible to extinction through mutational meltdown. Classic theory predicts short persistence times for metapopulations comprising small local populations with low connectivity, due to accumulation of deleterious mutations. Yet, some such systems have persisted over evolutionary time, implying the existence of mechanisms that allow metapopulations to avoid mutational meltdown. We first hypothesize a mechanism by which the combination of stochasticity in the numbers and types of mutations arising locally (genetic stochasticity), resulting in local extinction and recolonization through evolving dispersal, facilitates metapopulation persistence. We then test this mechanism using a spatially and genetically explicit individual-based model. We show that genetic stochasticity in highly structured metapopulations can result in local extinctions, which can favour increased dispersal, thus allowing recolonization of empty habitat patches. This causes fluctuations in metapopulation size and transient gene flow, which reduces genetic load and increases metapopulation persistence over evolutionary time. Our suggested mechanism and simulation results provide an explanation for the conundrum presented by the continued persistence of highly structured populations with inbreeding mating systems that occur in diverse taxa.</p>
Plots of interaural cues of listening experiment conditions (exact vs. experiment approximation)
<p>The plots show interaural cohehrence (IC) and interaural level difference (ILD) for a subset of experiment conditions presented in the JASA-EL publication 'Surrounding line sources optimally reproduce diffuse envelopment at off-center listening positions'. The experiment compared on-center with off-center listening (0.5 times radius). Off-center listening was simulated by remapped loudspeaker signals in a 24-channel loudspeaker setup. The nearest available loudspeaker was chosen for a direction shift, and the approximated angles (approx.) lead to negligible deviations in interaural cues compared to the interaural cues of an actually shifted listener (exact). Curves result from IC and ILD computations in 320 gammatone frequency bands, using a KU100 HRTF database.</p>
TLS data of forest plot
<p>TLS data acquired with a Riegl VZ-2000i within a forest plot in the Zirbenwald near Obergurgl, including 23 scanning positions using the one-touch-mode. Ground classification was done based on progressive TIN densification (Axelsson 2000). Projection: UTM 32N (EPSG 32632), fine registration based on the ALS-data from 2017.</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.