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.
147
datasets available to search
ShareScore release 0.9.0
Dataset results
147 results for “Spatial Network”
Quantification of 3D spatial correlations between state variables and distances to the grain boundary network in full-field crystal plasticity spectral method simulations
<p>This repository provides supplementary material to our paper: <a href="https://doi.org/10.1088/1361-651X/ab7f8c">https://doi.org/10.1088/1361-651X/ab7f8c</a></p> <p><strong>DAMASKPhenoPowerLaw75x75x75TestCase.zip</strong><br> An exemplary DAMASK simulation and corresponding output, generated from DAMASK v2.0.3. We used this to debug more productively the implementation of the post-processing tools. Furthermore we employed this simulation in the paper to identify why the graph clustering grain reconstruction method in many cases fuses neighboring grains in similar orientation.</p> <p><strong>DAMASKPhenoPowerLaw256x256x256ProductionRun.zip</strong><br> All input to run the DAMASK simulation that we discussed in the paper.</p> <p><strong>DAMASKPDTSettings256x256x256ProductionRun.zip</strong><br> All damaskpdt settings files to execute the individual post-processing studies of the paper.</p> <p><strong>DAMASKPDTSlurmSubmissionScripts256x256x256ProductionRun.zip</strong><br> All SLURM scripts we used to execute the compilation of damaskpdt and post-processing on TALOS.</p> <p><strong>DAMASKPDTSlurmLogs256x256x256ProductionRun.zip</strong><br> All logs from the SLURM job management system from the individual post-processing runs.</p> <p><strong>DAMASKPDTSourceCode_USedForAnalyticalDistanceToVoronoiCellFacets.zip</strong><br> The source code to the tool we developed during the revision process of our paper to verify the methods<br> via computing analytically exact distances to the facets of the Poisson-Voronoi tessellation from the<br> DAMASK microstructure instantiation.<br> <br> <strong>DAMASKPDTSourceCode_Production.zip</strong><br> The source code we used to post-process all results from the DAMASK simulations.</p> <p><strong>GitHub repository:</strong><br> https://github.com/mkuehbach/damaskpdt</p>
Dataset from: Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network
<p>Original data and code for the study:</p> <p>Wei, J., Xu, F., Cole, E. F., Sheldon, B. C., de Boer, W. F., Wielstra, B., Fu, H., Gong, P., & Si, Y. (2024, Accepted). Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network. Global Change Biology.</p> <p>The dataset mainly contains data showing the climate change-induced heterogeneous shifts in vegetation phenology and the migration integrity change from 2000 to 2020 for 16 Asian herbivorous waterfowl species. These data were derived from the following resources available in the public domain.</p> <p>The Global Lakes and Wetlands Database is available from “https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database”. The global land cover datasets are available from European Space Agency (ESA) Climate Change Initiative (CCI) products, “https://maps.elie.ucl.ac.be/CCI/viewer/download.php”. The Global Multi-resolution Terrain Elevation Data are available from “https://www.usgs.gov/centers/eros/science/terrain-monitoring-and-modeling”. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance product is available from “https://modis.gsfc.nasa.gov/data/dataprod/mod09.php”. The bird distribution maps are available from Birdlife International, “https://www.birdlife.org/”. The bird foraging attribute data are available from EltonTraits 1.0, “https://figshare.com”. The bird occurrence data are available from eBird Basic Dataset (EBD), “https://science.ebird.org/en/use-ebird-data/download-ebird-data-products”. The Hackett backbone phylogenetic trees are available from “https://birdtree.org/”.</p> <p>The code contains the R scripts and MATLAB scripts that we used for this study.</p> <p>For details please see the file “Readme.txt”, and the research paper.</p>
Predicting placenta transcriptional regulatory interactions based on spatial gene expression data and convolutional neural network
<p><strong>Aims:</strong> The dysfunction of placenta development is correlated to the defects of pregnancy and fetal growth. The detailed molecular mechanism of placenta development is not identified in human due to the lack of material in vivo. Image-based reconstructions of GRN are still very underdeveloped.</p> <p><strong>Methods and Results:</strong> In this study, first-trimester chorionic villus and decidua tissues were collected. Next, we present a machine-learning system to infer gene interaction networks of the human placenta from immunofluorescence images of trophoblast specific transcription factors obtained by a high-resolution scanner.</p> <p><strong>Conclusions:</strong> The experimental results show that deep learning models reveal regulatory roles that have not yet been fully recognized. The spatial expression data reveal new regulatory relationships that traditional experiments have failed to recognize, and has allowed the development of gene regulation networks based on the spatial distribution of gene expression. We demonstrate the effectiveness of this approach in building networks using high-resolution images of the human placenta. Our analysis is of certain significance for further exploration of the development of the placenta and the occurrence of pregnancy-related diseases in the future. The datasets and analysis provide a useful source for the researchers in the field of the maternal-fetal interface and the establishment of pregnancy.</p>
Spanning Scales: The Airborne Spatial and Temporal Sampling Design of the National Ecological Observatory Network
<p>Supporting information, datasets, and R and JavaScript code for the the National Ecological Observatory Network’s Airborne Observation Platform (AOP) sampling design and publication, <em>"Spanning Scales: The Airborne Spatial and Temporal Sampling Design of the National Ecological Observatory Network"</em></p>
Nest choice in arboreal ants is an emergent consequence of network creation under spatial constraints
<p>Biological transportation networks must balance competing functional priorities. The self-organizing mechanisms used to generate such networks have inspired scalable algorithms to construct and maintain low-cost and efficient human-designed transport networks. The pheromone-based trail networks of ants have been especially valuable in this regard. Here, we use turtle ants as our focal system: In contrast to the ant species usually used as models for self-organized networks, these ants live in a spatially constrained arboreal environment where both nesting options and connecting pathways are limited. Thus, they must solve a distinct set of challenges which resemble those faced by human transport engineers constrained by existing infrastructure. Here, we ask how a turtle ant colony's choice of which nests to include in a network may be influenced by their potential to create connections to other nests. In laboratory experiments with Cephalotes varians and Cephalotes texanus, we show that nest choice is influenced by spatial constraints, but in unexpected ways. Under one spatial configuration, colonies preferentially occupied more connected nest sites; however, under another spatial configuration, this preference disappeared. Comparing the results of these experiments to an agent-based model, we demonstrate that this apparently idiosyncratic relationship between nest connectivity and nest choice can emerge without nest preferences via a combination of self-reinforcing random movement along constrained pathways and density-dependent aggregation at nests. While this mechanism does not consistently lead to the de-novo construction of low-cost, efficient transport networks, it may be an effective way to expand a network, when coupled with processes of pruning and restructuring.</p>
Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient
<p>Species interactions underlie most ecosystem functions and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks were constructed from biodiversity monitoring data and known trophic links to assess how ecosystems have changed over time. The Baltic Sea is subject to many anthropogenic pressures, and low species diversity makes it an ideal candidate for determining how pressures change food webs. In this study, we used benthic monitoring data from 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated fundamental food web metrics evaluating network horizontal and vertical diversity, as well as stability that were compared over space and time. Our results show that the west coast of Sweden (Skagerrak) suffered a reduction in benthic invertebrate biodiversity by 32 % between the 1980's and 2010's, and that the number of links, generality of predators, and vulnerability of prey, have been significantly reduced. The other basins (Bothnian Sea, Baltic Proper and Bornholm Basin) do not show any significant changes in species richness or consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.</p>
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b in Spatial, temporal, molecular, and intraspecific differences of haemoparasite infection and relevant selected physiological parameters of wild birds in Georgia, USA
Fig. 3. Minimum spanning network for Haemoproteus and Plasmodium mitochondrial DNA cytochrome b haplotypes detected in four species of passerines from Georgia (USA). Circles are drawn proportional to the frequency at which haplotypes were observed. Color represents the host species from which haplotypes originated: red for Northern Cardinal (Cardinalis cardinalis), blue for Indigo Bunting (Passerina cyanea), yellow for White-throated Sparrow (Zonotrichia albicollis), and grey for Tufted Titmouse (Baeolophus bicolor). A single mutation separates nodes unless explicitly indicated by number. Letters within each node refer to Table 8 which indicates the haplotype name, sampling location, and other factors associated with hosts.
Data from: Integrating pheromonal and spatial information in the amygdalo-hippocampal network. Villafranca-Faus et al. 2021
<p>The local field potential (LFP) of the dorsal hippocampus (CA1) and cortical amygdala (PMCo) of mice, under head-fix recording and inmersed on a virtual environtmernt.</p> <p><strong>Paper Abstract</strong>: <br> Vomeronasal information is critical in mice for territorial behavior. Consequently, learning the territorial spatial structure should incorporate the vomeronasal signals indicating individual identity into the hippocampal cognitive map. In this work we show in mice that navigating a virtual environment induces synchronic activity, with causality in both directionalities, between the vomeronasal amygdala and the dorsal CA1 of the hippocampus in the theta frequency range. The detection of urine stimuli induces synaptic plasticity in the vomeronasal pathway and the dorsal hippocampus, even in animals with experimentally induced anosmia. In the dorsal hippocampus, this plasticity is associated with the overexpression of pAKT and pGSK3β. An amygdalo-entorhino-hippocampal circuit likely underlies this effect of pheromonal information on hippocampal learning. This circuit likely constitutes the neural substrate of territorial behavior in mice, and it allows the integration of social and spatial information.</p>
Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions"
<p>Data to reproduce the results of the manuscript entitled "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" submitted to Geophysical Research Letters. The companion jupyter notebook can be found in DOI: <a href="https://doi.org/10.5281/zenodo.8387558">10.5281/zenodo.8387558</a></p>
Spatial coding dysfunction and network instability in the aging medial entorhinal cortex
Open the record for dataset details and reuse information.
Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient
Open the record for dataset details and reuse information.
Nest choice in arboreal ants is an emergent consequence of network creation under spatial constraints
Open the record for dataset details and reuse information.
Code from: Spatial resource heterogeneity stabilizes local and regional predator-prey dynamics in ecologically-realistic networks
Open the record for dataset details and reuse information.
Data and code from: Determinants of species’ centrality in spatially-connected plant-frugivore networks
Open the record for dataset details and reuse information.
Functional, temporal, and spatial complementarity in mammal-fungal spore networks enhances mycorrhizal dispersal following forest harvesting
Open the record for dataset details and reuse information.
Temporal and spatial changes in benthic invertebrate trophic networks along a salinity gradient
<p>Species interactions underlie all ecosystem goods and services and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks are able to be constructed from biodiversity monitoring data and known trophic links to understand how ecosystems have changed over time. The Baltic Sea is subject to high anthropogenic pressures, and its low species diversity makes it an ideal candidate for understanding how pressures change food webs. In this study, we used benthic monitoring data from 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated traditional food web metrics that we compared over space and time. Our results show that the west coast of Sweden (Skagerrak) showed a reduction in benthic invertebrate biodiversity by 40% between the 1980's and 2010's, and that the number of links, linkage diversity, generality of predators, and vulnerability of prey have been significantly reduced. However, connectance has not significantly changed in the Skagerrak. The other basins (Bothnian Sea, Baltic Proper and Bornholm Basin) do not show any consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.</p>
Spatial Tournament Data for Complex Networks Non Deterministic Size - MSc Dissertation
<p>A data set that contains the results of various spatial tournaments, for the iterated prisoner's dilemma. Three different types of complex networks have been used as topology for the spatial tournaments. Small world, random and complete networks.</p>
Unraveling the cavity-nesting network at large spatial scales: The biogeographic role of woodpeckers as ecosystem engineers
<p><strong>Aim</strong>: Cavities are usually a limiting resource for several forest-dwelling vertebrates, with effects that propagate through ecological networks. Although diverse assemblages of primary excavators (e.g., woodpeckers) are assumed to increase cavities, other forest resources can also limit populations of primary excavators and cavity users, thus undermining the ecological role of excavators over different scales. We aim to test the biogeographical-scale relationships between primary excavators and cavity users by distinguishing the contribution of forest characteristics.</p> <p><strong>Location</strong>: Southern South America</p> <p><strong>Methods</strong>: We used species distribution models, which combine bioclimatic and remote sensing derived variables, to map the richness of vertebrates composing the cavity network of temperate and Mediterranean forests of South America. Based on a resampling procedure for ensuring spatial independence, we fitted structural equation models to estimate causal relationships between forest characteristics and cavity-user vertebrates.</p> <p><strong>Results</strong>: Secondary cavity users (obligated, habitat generalists and forest specialists) were positively and strongly influenced by the richness of primary excavators, while mammal richness was more influenced by tree richness. The richness of trees and <em>Nothofagus</em> tree species influenced positively the richness of primary excavators and secondary cavity users. Canopy height and net primary productivity affected positively secondary cavity users.</p> <p><strong>Main conclusions</strong>: Our results confirm the role of primary excavators as ecosystem engineers but highlight the importance of considering large spatial scales when analyzing cavity-nesting networks. Biogeographical patterns of tree diversity and forest structure can be important drivers of cavity-nesting networks that remain hidden when studies are conducted over fine spatial scales. </p>
Mesosphere/lower thermosphere 3-dimensional spatially resolved winds observed by Chinese multistatic meteor radar network using the newly developed VVP method
<p>This dataset supports the article "Mesosphere/lower thermosphere 3-dimensional spatially resolved winds observed by Chinese multistatic meteor radar network using the newly developed VVP method" . The data are provided in MatLab format.</p>
Application of inverse theory for high spatial resolution reconstructions of thermospheric vector wind fields from Doppler shifts measured by a ground-based network of all-sky Fabry-Perot interferometers
<p>Several types of all-sky viewing Fabry-Perot Interferometers (FPI) have been developed since the 1990s for ground-based remote sensing of thermospheric winds. The Scanning Doppler Imager (SDI) is one such instrument, which provides temporally simultaneous line-of-sight observations from hundreds of independent look directions per instrument exposure. A geographically distributed network of such instruments increases spatial coverage and, at many locations, also provides overlapping observations along multiple independent lines-of-sight. Together, these characteristics significantly increase the density and fidelity that is possible for reconstructed thermospheric vector wind fields, compared to a traditional narrow-field FPI, but at the cost of complexity and difficulty.<br><br></p> <p>Presently, we describe an application of inverse theory to reconstruct three-component vector thermospheric neutral wind fields using data from multiple SDI instruments. The salient features of the method used here are the ability to reconstruct three-component winds on a dense grid that is sampled regularly in latitude, longitude, and time, without assuming any a-priori underlying structure of the winds. This requires solving an inverse problem that does not in general yield a unique solution unless additional constraints are enforced. We describe this step, also known also as regularization, along with the strategy used to maximize the spatial resolution of the derived wind fields by automatically determining the minimum level of regularization that can produce stable inversions. We present example results obtained from applying this technique to one night of data from a network of SDIs in Alaska, and discuss the implications of these results for current understanding of thermospheric dynamics.</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.