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.
419
datasets available to search
ShareScore release 0.9.0
Dataset results
419 results for “capture data”
Marmot capture history data and growing season length data
Open the record for dataset details and reuse information.
Data from: Wildfire smoke impacts the body condition and capture rates of birds in California
Open the record for dataset details and reuse information.
Data and code from: Recreational fisheries selectively capture and harvest large predators
Open the record for dataset details and reuse information.
Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey
Open the record for dataset details and reuse information.
A simplified method for comprehensive capture of the Staphylococcus aureus proteome: S. aureus proteome data table
Open the record for dataset details and reuse information.
Data from: Optimizing exome captures in species with large genomes using species-specific repetitive DNA blocker
Open the record for dataset details and reuse information.
Data and code for: Combining eddy covariance towers, field measurements, and the MEMS 2 ecosystem model improves confidence in the climate impacts of bioenergy with carbon capture and storage
Open the record for dataset details and reuse information.
Data from: Evaluating UAV captured RGB and multispectral imagery as a proxy for visual rating of leaf spot in cultivated peanut
Open the record for dataset details and reuse information.
Data from: An open spatial capture–recapture model for estimating density, movement, and population dynamics from line-transect surveys
Open the record for dataset details and reuse information.
Data and code from: 3D-SOCS: synchronized video capture for posture estimation
Open the record for dataset details and reuse information.
Data from: Repeated mitochondrial capture with limited genomic introgression in a lizard group
Open the record for dataset details and reuse information.
Data for: The 3-dimensional genome drives the evolution of asymmetric gene duplicates via enhancer capture-divergence
Open the record for dataset details and reuse information.
Data from: How to use discrete choice experiments to capture stakeholder preferences in social work research
Open the record for dataset details and reuse information.
Data from: Natural tree colonisation of organo-mineral soils does not provide a net carbon capture benefit at decadal timescales
Open the record for dataset details and reuse information.
Data from: Development and validation of a RAD-Seq target-capture based genotyping assay for routine application in advanced black tiger shrimp (Penaeus monodon) breeding programs
<p><i><span>Background</span></i></p> <p><span>The development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile. Utilising recent advancements in <i>de-novo</i> genome-wide genotyping technologies, it is now possible to provide aquaculture industries with these same important genotyping resources, even in the absence of existing genome assemblies. Here, we present the development of a genome-wide SNP assay for the Black Tiger shrimp (<i>Penaeus monodon</i>) through utilisation of a reduced-representation whole-genome genotyping approach (DArTseq).</span></p> <p><i><span>Results</span></i></p> <p><span>Based on a single reduced-representation library, 31,262 polymorphic SNPs were identified across 650 individuals obtained from Australian wild stocks and commercial aquaculture populations. After filtering to remove SNPs with low read depth, low MAF, low call rate, deviation from HWE, and non-Mendelian inheritance, 7,542 high-quality SNPs were retained. From these, 4,236 high-quality genome-wide loci were selected for bates-probe development and 4,194 SNPs were included within a finalized target-capture genotype-by-sequence assay (DArTcap). This assay was designed for routine and cost effective commercial application in large scale breeding programs, and demonstrates higher confidence in genotype calls through increased call rate (from 80.2 </span>± 14.7 to 93.0% ± 3.5%<span>), </span>increased read depth (from 20.4 ± 15.6 to 80.0 ± 88.7<span>), as well as a 3-fold reduction in cost over traditional genotype-by-sequencing approaches.</span></p> <p><i><span>Conclusion</span></i></p> <p><span>Importantly, this assay equips the <em>P. monodon</em> industry with the ability to simultaneously assign parentage of communally reared animals, undertake genomic relationship analysis, manage mate pairings between cryptic family lines, as well as undertake advance studies of genome and trait architecture. Critically this assay can be cost effectively applied as <em>P. monodon</em> breeding programs transition to undertaking genomic selection.</span></p>
Data accompanying "Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites"
<p>This dataset contains the spatial data underlying the statistical analysis in:</p> <p><em>Assmann et al. (in press) - Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites</em></p> <p>Together with the code and tabular data contained in <a href="https://github.com/jakobjassmann/qhi_phen_ts/">https://github.com/jakobjassmann/qhi_phen_ts/</a> the data in this repository are required to reproduce the figures, tables and statistics reported in the manuscript.</p> <p>This dataset consists of two components:</p> <ol> <li> <p>Multispectral drone observations from the growing seasons 2016 and 2017 for 8 study plots on Qikiqtaruk - Herschel Island in Canada collected with Parrot Sequioa sensors (62 sets of multispectral orhomosaics in total).</p> </li> <li> <p>Post-porcessed Sentinel-2 MSI L2A scenes covering the same 8 study plots, including all scenes for which the area of the plots and their immediate surroundings were cloud free between May and September in 2016 and 2017.</p> </li> </ol> <p>-----------------------------------------------------------------------------------------------------------------</p> <p><strong>Citation</strong>: Jakob J. Assmann, Isla H. Myers-Smith, Jeffrey T. Kerby, Andrew M. Cunliffe and Gergana N. Daskalova.<em> <strong>In press</strong>.</em> Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites. <a href="https://doi.org/10.32942/osf.io/tqekn">https://doi.org/10.32942/osf.io/tqekn</a></p> <p><strong>Legal notice:</strong> This dataset contains modified Copernicus Sentinel [2016, 2017] data.</p> <p><strong>Acknowledgements (from the manuscript):</strong></p> <p>We would like to thank the Team Shrub field crews of the 2016 and 2017 field seasons for their hard work and effort invested in collecting the data presented in this research, this includes Will Palmer, Santeri Lehtonen, Callum Tyler, Sandra Angers-Blondin and Haydn Thomas. Furthermore, we would like to thank Tom Wade and Simon Gibson-Poole from the University of Edinburgh Airborne GeoSciences Facility, as well as Chris McLellan and Andrew Gray from the NERC Field Spectroscopy Facility for their support in our drone endeavours. We also want to express our gratitude to Ally Phillimore, Ed Midchard, Toke Høye and two anonymous reviewers for providing feedback on earlier versions of this manuscript. Lastly, JJA would like to thank IMS, Ally Phillimore and Richard Ennos for academic mentorship throughout his PhD.</p> <p>We thank the Herschel Island—Qikiqtaruk Territorial Park Team and Yukon Government for providing logistical support for our field research on Qikiqtaruk including: Richard Gordon, Cameron Eckert and the park rangers Edward McLeod, Sam McLeod, Ricky Joe, Paden Lennie and Shane Goosen. We thank the research group of Hugues Lantuit at the Alfred Wegener Institute and the Aurora Research Institute for logistical support. Research permits include Yukon Researcher and Explorer permits (16-48S&E and 17-42S&E) and Yukon Parks Research permits (RE-Inu-02-16 and 17-RE-HI-02). All airborne activities were licensed under the Transport Canada special flight operations certificates ATS 16-17-00008441 RDIMS 11956834 (2016) and ATS 16-17-00072213 RDIMS 12929481 (2017).</p> <p>Funding for this research was provided by NERC through the ShrubTundra standard grant (NE/M016323/1), a NERC E3 Doctoral Training Partnership PhD studentship for Jakob Assmann (NE/L002558/1), a research grant from the National Geographic Society (CP-061R-17), a Parrot Climate Innovation Grant, the Aarhus University Research Foundation, and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement (754513) for Jeffrey Kerby, a NERC support case for use of the NERC Field Spectroscopy Facility (738.1115), equipment loans from the University of Edinburgh Airborne GeoSciences Facility and the NERC Geophysical Equipment Facility (GEF 1063 and 1069).</p> <p>Finally, we would like to thank the Inuvialuit people for the opportunity to conduct research in the Inuvialuit Settlement Region.</p>
Model output data for Marine Wild-Capture Fisheries after Nuclear War
<p>This is the model data material for Scherrer at al., PNAS. [Scherrer K. J. N., et al. Marine wild-capture fisheries after nuclear war, PNAS in press]. Input files include time series of gridded global oceanic Sea Surface Temperature and Net Primary Productivity (output from the CESM model) and socioeconomic input for the global fisheries model (BOATS). Output files include globally integrated time series (used in Figs. 1-3 and 6) and global gridded model output (used in Figs. 4-5) for each of the five ensemble member runs.</p>
Data from: A stable phylogenomic classification of Travunioidea (Arachnida, Opiliones, Laniatores) based on sequence capture of ultraconserved elements
Molecular phylogenetics has transitioned into the phylogenomic era, with data derived from next-generation sequencing technologies allowing unprecedented phylogenetic resolution in all animal groups, including understudied invertebrate taxa. Within the most diverse harvestmen suborder, Laniatores, most relationships at all taxonomic levels have yet to be explored from a phylogenomics perspective. Travunioidea is an early-diverging lineage of laniatorean harvestmen with a Laurasian distribution, with species distributed in eastern Asia, eastern and western North America, and south-central Europe. This clade has had a challenging taxonomic history, but the current classification consists of ~77 species in three families, the Travuniidae, Paranonychidae, and Nippononychidae. Travunioidea classification has traditionally been based on structure of the tarsal claws of the hind legs. However, it is now clear that tarsal claw structure is a poor taxonomic character due to homoplasy at all taxonomic levels. Here, we utilize DNA sequences derived from capture of ultraconserved elements (UCEs) to reconstruct travunioid relationships. Data matrices consisting of 317–677 loci were used in maximum likelihood, Bayesian, and species tree analyses. Resulting phylogenies recover four consistent and highly supported clades; the phylogenetic position and taxonomic status of the enigmatic genus Yuria is less certain. Based on the resulting phylogenies, a revision of Travunioidea is proposed, now consisting of the Travuniidae, Cladonychiidae, Paranonychidae (Nippononychidae is synonymized), and the new family Cryptomastridae Derkarabetian & Hedin, fam. n., diagnosed here. The phylogenetic utility and diagnostic features of the intestinal complex and male genitalia are discussed in light of phylogenomic results, and the inappropriateness of the tarsal claw in diagnosing higher-level taxa is further corroborated.
Data from: Capture enrichment of aquatic environmental DNA: a first proof of concept
Environmental DNA (eDNA) sampling – the detection of genetic material in the environment to infer species presence – has rapidly grown as a tool for sampling aquatic animal communities. A potentially powerful feature of environmental sampling is that all taxa within the habitat shed DNA and so may be detectable, creating opportunity for whole-community assessments. However, animal DNA in the environment tends to be comparatively rare, making it necessary to enrich for genetic targets from focal taxa prior to sequencing. Current metabarcoding approaches for enrichment rely on bulk amplification using conserved primer annealing sites, which can result in skewed relative sequence abundance and failure to detect some taxa because of PCR bias. Here we test capture enrichment via hybridization as an alternative strategy for target enrichment using a series of experiments on environmental samples and lab-generated, known-composition DNA mixtures. Capture enrichment resulted in detecting multiple species in both kinds of samples, and post-capture relative sequence abundance accurately reflected initial relative template abundance. However, further optimization is needed to permit reliable species detection at the very low DNA quantities typical of environmental samples (< 0.1 ng DNA). We estimate that our capture protocols are comparable to, but less sensitive than, current PCR-based eDNA analyses.
VCF files and regression analyses for: Assessing fine-scale pondscape connectivity with amphibian eyes: an integrative approach using genomic and capture-mark-recapture data
<p><span>In the face of habitat loss, preserving functional connectivity is essential to maintain genetic diversity and the demographic dynamics required for the viability of biotic communities. This requires knowledge of the dispersal behavior of target species, which can be modeled as kernels, or probability density functions of dispersal distances at increasing geographic distances. We present an integrative approach to investigate the relationships between genetic connectivity and demographic parameters in organisms with low vagility focusing on five syntopic pond-breeding amphibians. We genotyped 1,056 individuals of two anuran and three urodele species (1,732–3,913 SNPs per species) from populations located in a landscape comprising 64 ponds to characterize fine-scale genetic structure in a comparative framework and combined this genetic data with information obtained in a previous two-year capture-mark-recapture (CMR) study. Specifically, we contrasted graphs reconstructed from genomic data with connectivity graphs based on dispersal kernels and demographic information obtained from CMR data from previous studies and assessed the effects of population size, population density, geographical distances, inverse movement probabilities and the presence of habitat patches potentially functioning as stepping stones on genetic differentiation. Our results suggest a significant influence of local population sizes on patterns of genetic connectivity at small spatial scales. In addition, m</span><span>ovement records and cluster-derived kernels provide robust inferences on most likely dispersal paths that are consistent with </span><span>genomic inferences on genetic connectivity. The integration of genetic and CMR data holds great potential for understanding genetic connectivity at spatial scales relevant to individual organisms, with applications for the implementation of management actions at the landscape level. </span></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.