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.
22
datasets available to search
ShareScore release 0.9.0
Dataset results
22 results for “Sample counts”
Species-level estimated abundances and zero counts of nighttime collected female mosquitoes 2014 - 2022 (Derived from NEON Mosquitoes sampled from CO2 traps (DP1.10043.001, RELEASE-2024))
This Level 2 data package contains species level estimated abundances, including zero counts, and estimated mean number of female mosquitoes per trap derived from the NEON Mosquitoes sampled from CO2 traps (DP1.10043.001), RELEASE-2024 Level 0 data (https://doi.org/10.48443/3cyq-6v47). The data set includes mosquito records of traps collecting mosquito samples at night, for up to 24 trap hours, across a total of 20 terrestrial core and 27 terrestrial gradient sites from 2014 to 2022. To ensure high confidence in abundance estimates, records were only included when at least 90% of collected individuals were identified to sex, and 90% of female specimens were identified to species. Information across multiple QC/QA fields within the NEON mosquito data was evaluated to identify and exclude records where confidence in estimated abundances may have been compromised. Species level zero counts were added for all species collected at least once within the sampling year and trap location. Additionally, species level zero counts were included for trap events where only male mosquitoes had been collected or where QC/QA remarks indicated traps were inactive due to cold temperatures. The data set provides an analysis ready time series of estimated abundances across NEON sites and plots. An R Markdown file that contains descriptions of the QC/QA and data filtering steps along with annotated code, as well as data tables used to filter active and inactive trap events based on QC/QA fields, are published with the data package. Any questions about this data package should be directed to Amely Bauer listed under contacts.
Sample dataset: ovitrap sticks pictures and observed egg count
<p>This dataset consists of 300 ovitrap sticks pictures that contain at least one <em>Aedes aegypty</em> egg. The pictures were taken with an iPhone 7 mobile phone and were used to assess the performance of a mosquito egg counter algorithm and application (<a href="https://ovitrap-monitor.netlify.app/">https://ovitrap-monitor.netlify.app/</a>). The ovitraps are part of a weekly surveillance program carried out in the city of Córdoba (Argentina) by the Health Ministry authorities. This dataset is a smaple obtained between December 2021 and March 2022. We also include a text file with the code of the ovitraps and the number of eggs counted by a technician under magnifying glasses (i.e., observed counts).</p>
Microplankton counts from discrete water column samples using flow imaging microscopy (FlowCam) from Lakes Fryxell and Hoare, McMurdo Dry Valleys, Antarctica (2007-2011)
This data package consists of microplankton counts from discrete water column samples collected at various depths in Lake Fryxell and Lake Hoare in the McMurdo Dry Valleys region of Antarctica. Samples were collected and preserved during the austral summer-autumn transition in 2007-2008 and in addition to routine McMurdo Dry Valley Long Term Ecological Research (LTER) core limnological sampling in November and December of 2008, 2010, and 2011. Data were imaged using flow cytometry (FlowCam VS-IV) and classified with statistical image-based software (Visual Spreadsheet, v4.17.14). These data include haptorian ciliates, filamentous cyanobacteria, and coccoidal algae particle counts per milliliter that were automatically classified from user-built libraries and statistical filters based on the morphological characterizations of the plankton.
Model Counting and Uniform Sampling Instances
<p>These instances mainly consist of the formulas that have been used in the evaluation of recent model counting techniques. A significant set of benchmarks involving sampling set, i.e., they are meant for projected model counting.<br> <br> The specification for reading such files can be found at <a href="https://github.com/meelgroup/approxmc">https://github.com/meelgroup/approxmc</a><br> <br> Here is list of some of the papers that have reported results on these instances:</p> <p>1. BIRD: Engineering an Efficient CNF-XOR SAT Solver and its Applications to Approximate Model Counting<br> Mate Soos and Kuldeep S. Meel<br> Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2019.</p> <p>2. Accelerating Approximate Techniques for Counting and Sampling Models Through Refined CNF-XOR Solving<br> Mate Soos, Stephan Gocht, and Kuldeep S. Meel<br> Proceedings of International Conference on Computer-Aided Verification (CAV), 2020.<br> </p>
Figure 3. Critical stop lines for a sequential count plan for T. urticae. For a in Spatial distribution and sampling plan for Tetranychus urticae (Acari: Tetranychidae) in bean crops
Figure 3. Critical stop lines for a sequential count plan for T. urticae. For a precision level of 10 and 25%.
A Genetic Algorithm Approach to Regenerate Image from a Reduce Scaled Image Using Bit Data Count-Figure 5. Image down sample
<p>Our proposal is to store each column and row bits count in a separate file and used that to reproduce the image using genetic algorithm.If we take 10% of an image size and the row and column image hamming bit count our total size will be approximately below 15% of the actual image size. We proposed a method to reproduce original image from using this 15% information.</p>
A Genetic Algorithm Approach to Regenerate Image from a Reduce Scaled Image Using Bit Data Count-Figure 8. Sample Data Extraction for a 20*20 size image
<p>As in figure 7 we are storing the extra data which is look like figure 8. Where a 20*20 size image of alphabet ‘A’ data has been stored. When we regenerate image, we are using these data.</p>
Monitoring wildlife population trends with sample counts: A case study on the Alpine ibex (Capra ibex)
<p><span>Monitoring population dynamics is of fundamental importance in conservation but assessing trends in abundance can be costly, especially in large and rough areas. Obtaining trend estimations from counts performed in only a portion of the total area (sample counts) can be a cost-effective method to improve the monitoring and conservation of species difficult to count. </span></p> <p><span>We tested the effectiveness of sample counts in monitoring population trends of wild animals, using as a model population the Alpine ibex (<em>Capra ibex</em>) in the Gran Paradiso National Park (Italy), both with computer simulations and using historical count data collected over the last 65 years. Despite sample counts failed to correctly estimate the true population abundance, sampling half of the target area could reliably monitor the trend of the target population. In case of strong changes in abundance, an even lower proportion of the total area could be sufficient to identify the direction of the population trend. However, when there is a high yearly trend variability, the required number of samples increases and even counting in the entire area can be ineffective to detect population trends. The effect of other parameters, such as which portion of the area is sampled and detectability, was lower, but these should be tested case by case. </span></p> <p><span>Sample counts could therefore constitute a viable alternative to assess population trends, allowing for important, cost-effective improvements in the monitoring of wild animals of conservation interest. </span></p>
Monitoring wildlife population trends with sample counts: A case study on the Alpine ibex (Capra ibex)
Open the record for dataset details and reuse information.
Raw nucleotide counts for clinal Misty Lake and stream stickleback samples
<div> <p class="x_MsoNormal"><span>How ecological divergence causes strong reproductive isolation between populations in close geographic contact remains poorly understood at the genomic level. We here study this question in a stickleback fish population pair adapted to contiguous, ecologically different lake and stream habitats. Clinal whole-genome sequence data reveal numerous genome regions (nearly) fixed for alternative alleles over a distance of just a few hundred meters. This strong polygenic adaptive divergence must constitute a genome-wide barrier to gene flow because a steep cline in allele frequencies is observed across the entire genome, and because the cline center co-localizes with the habitat transition. Simulations confirm that such strong divergence can be maintained by polygenic selection despite high dispersal and small per-locus selection coefficients. Finally, comparing samples from near the habitat transition before and after an unusual ecological perturbation demonstrates the fragility of the balance between gene flow and selection. Overall, our study highlights the efficacy of divergent selection in maintaining reproductive isolation without physical isolation, and the analytical power of studying speciation at a fine eco-geographic and genomic scale.</span></p> </div> <p> </p>
Weekly travel times by direction and sample count for each link in Development of AIS Model of Texas Gulf Intracoastal Waterway Travel Times
<p>Excel spreadsheet containing all of the travel times and sample counts for each link (by direction).</p>
Data from: Colorado aquatic macroinvertebrate samples and duck counts
<p>Food availability varies considerably over space and time in wetland systems, and consumers must be able to track those changes during nutrient demanding points in the life cycle like breeding. Resource tracking has been studied frequently among herbivores, but receives less attention among consumers of macroinvertebrates. We evaluated the change in resource availability across habitat types and time, and the simultaneous density of waterfowl consumers throughout their breeding season in a high-elevation, flood-irrigated system. We also assessed whether the macroinvertebrate resource density better predicted waterfowl density across habitats, compared to consistency (i.e., temporal evenness) of the invertebrate resource or taxonomic richness. Resource density varied marginally across wetland types but was highest in basin wetlands (i.e., ponds) and peaked early in the breeding season, whereas it remained relatively low and stable in other wetland habitats. Breeding duck density was positively related to resource density, more so than temporal resource stability, for all species. Resource density was negatively related to duckling density, however. These results have the potential to not only elucidate mechanisms of habitat selection among breeding ducks in flood-irrigated landscapes, but also suggest there is not a consequential trade-off to selecting wetland sites based on energy density versus temporal resource stability and that good-quality wetland sites provide both.</p>
Data from: Colorado aquatic macroinvertebrate samples and duck counts
Open the record for dataset details and reuse information.
Raw nucleotide counts for clinal Misty Lake and stream stickleback samples
Open the record for dataset details and reuse information.
Data from: Counting cats: spatially explicit population estimates of cheetah (Acinonyx jubatus) using unstructured sampling data
Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.22 ± 0.301 and 1.28 ± 0.322 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.
Data from: Counting cats: spatially explicit population estimates of cheetah (Acinonyx jubatus) using unstructured sampling data
Open the record for dataset details and reuse information.
Mite counts from manure samples
Open the record for dataset details and reuse information.
Operational Taxonomic Unit (OTU) Counts at Sampling Subplots at HJA, HFR, BCI, CWT, LUQ, and NWT for N2O-reducing Microbial Communities
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. N2O is reduced to N2 exclusively by microorganisms but little is known about the diversity and geographic distribution of N2O-reducing communities in forest soils across a temperature gradient. To this end, nosZ (N2O-reducing) amplicons were sequenced by MiSeq and sorted into Operational Taxonomic Units (OTUs) which could then be compared across sites for distribution, richness, and diversity indices. This work was completed by the University of Oklahoma Institute for Environmental Genomics as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Data from: Comparing the sampling performance of sound recorders versus point counts in bird surveys: a meta-analysis
Open the record for dataset details and reuse information.
DNA methylome analysis of skin samples from punch tissue biopsy of 322 healthy female individuals and total body naevus count
GEO Series GSE90124. Homo sapiens. 322 samples. Type: Methylation profiling by array.
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.