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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
3,080 datasets
Five lettuce cultivars ('Summer Star', 'Grand Rapid', 'Tango', 'Bingo', and 'Black Rose') were evaluated in a controlled aeroponic environment. The dataset likely contains statistical analysis results, including ANOVA, Pearson correlation, and Principal Component Analysis, where the first two principal components explained 86.13% of total variance. The data was uploaded by Anand Sahil on figshare in March 2026.
Analysis files from a neuroscience study on brain state regulation include Matlab scripts for processing EEG data and a Prism file for statistical analysis. The scripts handle tasks like resampling EEG signals to 256 Hz, calculating spectral power density, and identifying sleep episodes and brief awakenings. Author Elise Meijer published these resources under a CC BY 4.0 license in March 2026.
Medicinal chemistry data details the discovery and optimization of a series of selective piperazine-based glucocorticoid receptor antagonists. The dataset describes compounds derived from a simplified scaffold, with three key molecules progressed to in vivo proof-of-concept studies. It was authored by Lorna A. Duffy and shared via figshare in April 2026.
Youhong Gao's dataset provides a multi-media biogeochemical record from Lake Dian, a shallow eutrophic plateau lake in southwest China. It includes sediment cores with high-resolution chronologies, surface and water column samples, pore water, and organic matter source data. The collection supports research on eutrophication, carbon cycling, and nutrient dynamics in plateau lake systems.
5.5 KB of statistical comparison data derived from 10 repetition-wise mean accuracies. The data was generated using a 10 × 5 repeated stratified cross-validation procedure and authored by Divya Kesavulu. It was last updated on April 21, 2026, and is available under a CC-BY-4.0 license.
Model fit statistics from Leave-One-Out Cross-Validation (LOO-CV) and the Widely Applicable Information Criterion (WAIC) for a Bayesian hierarchical logistic regression model. The dataset is a 5.5 KB Excel file authored by Maurice Wanyonyi and last updated on April 21, 2026.
Reality Drift Archive provides an early working paper introducing descriptive terms for patterns in digitally mediated environments. The document defines concepts like Synthetic Realness, Filter Fatigue, Optimization Trap, and Cognitive Drift as labels for recurring observations about algorithmic systems. It is retained as an archival record for historical continuity and was last updated on 2026-04-26.
Spatial predictions of mud, sand, and gravel percentages for the UK shelf and North Sea. Compositional fractions were modelled using a statistical regression model and are provided as raster files. The dataset also includes predicted sediment classifications according to EUNIS habitat and Folk class systems.
Historical shoreline positions for the entire Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rates of change at 25-meter intervals. The dataset includes statistics like Net Shoreline Movement and Linear Regression Rate, providing a dynamic picture of coastal evolution.
Ulster University and OpenDataNI provide a historical shoreline analysis for the Northern Ireland coastline. The dataset visualizes shoreline change and calculates rates of change using statistics like Net Shoreline Movement and Linear Regression Rate, derived from Ordnance Survey maps and aerial imagery. It was last updated on March 18, 2026.
Historical shoreline positions for the Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery. Ulster University analyzed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset provides a dynamic picture of coastal change from the early 1800s to 1906.
Historical shoreline analysis for the entire Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset provides a dynamic picture of coastal retreat and accretion over annual to decadal time periods.
Historical shoreline analysis for the entire Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset provides a dynamic picture of coastal change from the early 1800s, with the last update recorded on 2026-03-18.
Historical shoreline position and geometry data for the Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery. Ulster University produced this dataset using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The analysis provides a dynamic picture of coastal change from the early 1800s onward.
Ulster University and OpenDataNI provide a historical shoreline analysis for the entire Northern Ireland coastline. The dataset quantifies coastal change since the early 1800s using Ordnance Survey maps and aerial imagery, processed with the Digital Shoreline Analysis System (DSAS). It includes rate-of-change statistics like Net Shoreline Movement and Linear Regression Rate, calculated at 25-meter intervals.
Northern Ireland's coastline is analyzed for historical shoreline position and geometry changes from the early 1800s onward. Ulster University produced this dataset by analyzing Ordnance Survey maps and aerial imagery using the Digital Shoreline Analysis System (DSAS). The data includes rate-of-change statistics calculated at 25-meter intervals, such as Net Shoreline Movement and Linear Regression Rate.
Historical shoreline positions for the entire Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset includes metrics like Net Shoreline Movement and Linear Regression Rate to visualize coastal retreat and accretion.
Historical shoreline positions for the entire Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rates of change at 25-meter intervals. The dataset includes statistics like Net Shoreline Movement and Linear Regression Rate, providing a dynamic picture of coastal evolution over annual to decadal periods.
Historical shoreline position and geometry data for the entire Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. The dataset was processed using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The end product was provided by Ulster University and is managed by OpenDataNI.
Historical shoreline positions for the Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. The data was processed using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The end product was provided by Ulster University and is hosted by OpenDataNI.