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.
495
datasets available to search
ShareScore release 0.9.0
Dataset results
495 results for “spatial scale”
supplementary dataset for "Review of quantitative applications of the concept of the water planetary boundary at different spatial scales"
<p>This supporting information includes 6 spread sheets:</p> <p>Table S1 288_database search The studies collected through an adjusted search strategy from ISI Web of Science v.5.35.<br> Table S2 114_1st filter The studies passed the 1st filter and their category (Category I ).<br> Table S3 52_2nd filter The studies passed the 2ed filter and their category (Category II ).<br> Table S4 26_additional screening The studies collected through manual searching from the citations of 288 studies, as well as the range included in previous literature reviews.<br> Table S5 28_final The studies passed the three filters and three additional reports.<br> Table S6 488_data records The 488 data records collected from the 28 studies.<br> </p>
A New Speech, Spatial, and Qualities of Hearing Scale Short-Form for Deaf Children
ClinicalTrials.gov study NCT04106063. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Glioblastoma disrupts cortical network activity at multiple spatial and temporal scales
GEO Series GSE263832. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
Data from: Social spider webs harbor largely consistent bacterial communities across broad spatial scales
Open the record for dataset details and reuse information.
Data from: Grizzly bear response to fine spatial and temporal scale spring snow cover in Western Alberta
Open the record for dataset details and reuse information.
Data from: Sensory deficiencies affect resources selection and associational effects at two spatial scales
Open the record for dataset details and reuse information.
Sounding rocket payload systems for in-situ measurements of ionosphere-thermosphere structure at small spatial scales Project
<p> The methodology developed under this grant is primarily an effort to develop new sub-payload technologies and an inexpensive method of testing them. The three technical goals are: (1) to improve and test the existing spring sub-payload ejection system and rocket propelled ejection system, (2) to test the performance of ampule-deployed radar chaff (rather than TMA) to track high altitude winds, and (3) to develop and test sensor and telemetry packages to monitor the attitude stability and position of deployed sub-payloads.&nbsp; The proposed effort will also demonstrate very low cost, low altitude rockets as an inexpensive flight test of payloads prior to expensive sounding rocket deployments. The payloads tested on 5 to 7 low-cost rockets will be (1) foil chaff designed for radar tracking of mesospheric winds, (2) plasma instruments composed of GPS monitors, magnetometers, and accelerometers, and (3) android phones for the investigation of off-the-shell instrumentation and telemetry.&nbsp; Finally, a campaign of 2 to 4 sounding rocket deployments on &lsquo;as-available&rsquo; flights from Poker Flats will be used to test spring ejection without spin up, spring ejection with spin up for sub-payload attitude control, and rocket ejection</p>
Fig. 2 in Phylogenetic and functional diversity of African muroid rodents at different spatial scales
Fig. 2 Mean value of indices (NRI and NTI) of phylogenetic (blue) and functional (red) community structure resulting from averaging SES values obtained in all local communities belonging to the same assemblage (bioregion; SAH Saharan, SUD Sudanian, CON Congolian, SOM Somalian, ETH Ethiopian, ZAM Zambezian, SOU Southern African).
FIG. 5 in Phenotypic Variation in Brook Trout Salvelinus fontinalis (Mitchill) at Broad Spatial Scales Makes Morphology an Insufficient Basis for Taxonomic Reclassification of the Species
FIG. 5. Representative examples of diverse morphology, particularly in mouth shape and position, observed within a single stream-dwelling Brook Trout population. Fish on the first row display more inferior mouth positions, whereas fish on the last row show more isognathous and prognathic jaws with a terminal/superior mouth position. All fish were captured from Crabtree Creek in the Savage River Watershed of western Maryland (39827047.2500 N, 79812036.0800W). Fish total length is noted in the upper right corner of each photograph. A full description of collection and photography protocols is provided in Kazyak et al. (2015).
FIG. 3 in Phenotypic Variation in Brook Trout Salvelinus fontinalis (Mitchill) at Broad Spatial Scales Makes Morphology an Insufficient Basis for Taxonomic Reclassification of the Species
FIG. 3. Comparison of pored lateral-line scale counts for specimens collected from (A) 38 streams in the Great Smoky Mountains National Park (GSMNP) by Weathers et al. (2019) and (B) three streams surveyed by Stauffer (2020) and three populations described by Stauffer and King (2014) in Long Island, NY. Individual-level data collected by Weathers et al. (2019) are displayed with violin plots, with the width of the violin plot for each stream demonstrating the density of the distribution for a given value and the minimum and maximum values indicated by the tails of the distribution. Due to discrepancies between published and raw data, values from Stauffer (2020) and Stauffer and King (2014) are shown using two methods. Data from the publication appear as the mode(s) (circle) and range (lines), and the raw, individual-level data appear as violin plots. Streams appear on the x-axis by ascending average trait value, and streams included in both Weathers et al. (2019) and Stauffer (2020) are plotted with the same color (Cosby Creek [CS]: yellow; Greenbrier Creek [GB]: green; Indian Camp Creek [ICC]: blue). Data from populations in NY are shown in red and all other sites from GSMNP, TN in gray.
SMMGCL: A novel multi-scale graph contrastive learning framework for integrating spatial multi-omics data
Open the record for dataset details and reuse information.
Figure 4 in Dissecting copepod diversity at different spatial scales in southern European groundwater
Figure 4. (A) Mean species richness of the local units in karstic and porous aquifers in each region (standard error bars shown); (B) total species richness of karstic and porous aquifers in each region; (C) mean species richness of local units in the four habitat types in each region (standard error bars shown); (D) total species richness of the four habitat types in each region.
Fine-scale tree spatial patterns are shaped by dispersal limitation which correlates to functional traits in a natural temperate forest - Raw SPPA data
<p>Raw data allowing the reproduction of the spatial point pattern analysis detailed in Beyns, R. et al. (2021) Fine-scale tree spatial patterns are shaped by dispersal limitation which correlates to functional traits in a natural temperate forest. <em>Journal of Vegetation Science</em>.</p>
National-Scale Spatial Flood Modeling with an Optimized Deep Learning Approach (case study: Sweden)
<p>National-Scale Spatial Flood Modeling with an Optimized Deep Learning Approach (case study: Sweden)</p>
Data from: Specialization patterns in symbiotic associations: a community perspective over spatial scales.
<p><strong>Nostoc_rbcLX_alignment: </strong>Alignment of Nostoc rbcLX sequences in FASTA format. </p> <p><strong>Name_equivalences: </strong>Excel cointaining mycociont species names, abbreviations, alignment code for each sample used in the aligment, forest and Nostoc phylogroup.</p> <p><strong>Abstract:</strong> </p> <ol> <li>Specialization, contextualized in a resource axis of an organism niche, is a core concept in ecology. In biotic interactions, specialization can be determined by the range of interacting partners. Evolutionary and ecological factors, in combination with the surveyed scale (spatial, temporal, biological and/or taxonomic) influence the conception of specialization.</li> <li>This study aimed to assess the specialization patterns and drivers in the lichen symbiosis, considering the interaction between the principal fungus (mycobiont) and the associated <em>Nostoc</em> (cyanobiont), from a community perspective considering different spatial scales. Thus, we determined <em>Nostoc</em> phylogroup richness and composition of lichen communities in eleven <em>Nothofagus pumilio</em> forests across a wide latitudinal gradient in Chile. To measure specialization, cyanobiont richness, Simpson’s, and d’ indices were estimated for 37 mycobiont species in these communities. Potential drivers that might shape <em>Nostoc</em> composition and specialization measures along the environmental gradient were analysed. Limitations in lichen distributional ranges due to the availability of their cyanobionts were studied. Turnover patterns of cyanobionts were identified at multiple spatial scales.</li> <li>The results showed that environmental factors shaped the <em>Nostoc</em> composition of these communities, thus limiting cyanobiont availability to establish the symbiotic association. Besides, specialization changed with the spatial scale and with the metric considered. Cyanolichens were more specialized than cephalolichens when considering partner richness and Simpson’s index, whereas the d’ index was mostly explained by mycobiont identity. Little evidence of lichen distributional ranges due to the distribution of their cyanobionts was found. Thus, lichens with broad distributional ranges either associated with several cyanobionts or with widely distributed cyanobionts. Comparisons between local vs. regional scales showed a decreasing degree of specialization at larger scales due to an increase in cyanobiont richness.</li> <li><em>Synthesis</em>. The results support the context dependency of specialization and how its consideration changes with the metric and the spatial scale considered. Subsequently, we suggest considering the entire community, and widening the spatial scale studied as it is crucial to understand factors determining specialization.</li> </ol>
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.