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Crop yield, soil data, pest surveillance, livestock, food composition, precision farming
19,247 datasets
Relational data for business intelligence from an Indian fast-food retail chain. The dataset is sourced from Kaggle, but the author, organization, and specific time range are unknown. Row count, file formats, and column-level documentation are not provided.
This dataset compiles projections of crop yield changes in Africa under future climate scenarios from 72 peer-reviewed crop modeling studies. It expands on earlier reviews to include grains, tubers, and cash crops, capturing variables like crop type, country, climate scenario, and adaptation measures. The data is harmonized for meta-analysis of climate risks to African agriculture.
zambia-irrigation-labels is a dataset hosted on Kaggle. The title suggests it contains labels related to irrigation systems or land use in Zambia. The dataset's specific content, scale, and origin are not detailed in the provided metadata.
Research data on the production and safety of three farmed macroalgae species—Turkish towel, Pacific dulse, and sea lettuce—from a land-based aquaculture facility in the Pacific Northwest. The dataset likely contains information on proximate composition, contaminant levels, bacterial content, and post-harvest quality. This work was conducted by NOAA's Northwest Fisheries Science Center at the Sol-Sea Farm in Manchester, Washington, with the last metadata update recorded on March 14, 2026.
NOAA research focuses on three local macroalgae species—Turkish towel, Pacific dulse, and sea lettuce—grown in a controlled land-based system. The work, conducted at the Sol-Sea Farm in Manchester, Washington, aims to provide basic information on composition, contaminants, and post-harvest quality to support commercial aquaculture. This data is needed to ensure product safety and reduce operational costs for macroalgae production.
Research data from a NOAA/NMFS project on land-based macroalgae aquaculture production. The dataset likely contains measurements related to the composition, contaminants, bacterial content, and post-harvest quality of three species: Turkish towel, Pacific dulse, and sea lettuce. The work was conducted at the Sol-Sea Farm facility in Manchester, Washington.
UTA_RLDD_CROPPED_MEDIAPIPE is a dataset of cropped images, likely processed using the MediaPipe framework. The dataset is hosted on Kaggle, but its specific content, size, and creation details are not provided in the available metadata. Further details regarding the source, collection method, and specific annotations require verification after download.
More than 300 foods are listed with nutrient amounts for calories, fats, proteins, saturated fats, carbohydrates, and fibers. Foods are categorized into groups like desserts, vegetables, and fruits. The data is sourced from Wikipedia's Food Nutrient List and is licensed for open use.
Reddit posts from the r/wallstreetbets subreddit, a community for discussing stock and option trading. The data was collected using the Python Reddit API Wrapper (PRAW) and is shared under a CC0-1.0 license. It may contain unfiltered content, including harsh language.
A global geospatial dataset maps the distribution of cattle in 2010. The data is expressed as the total number of cattle per pixel at a 5-minute arc resolution, sourced from the Gridded Livestock of the World (GLW 3) database. The dataset was authored by Marius Gilbert of the Université Libre de Bruxelles.
Annual estimates of global man-made methane emissions from 1860 through 1994. The data provides total anthropogenic emissions and breakdowns for categories including flaring, oil and gas systems, coal mining, biomass burning, livestock, rice farming, and landfills. The estimates were developed by David I. Stern of Boston University, using historical time series of variables like population and coal production.
31st Street Harbor in Chicago, Illinois, is covered by a high-resolution vector shoreline dataset compiled from imagery. The data, created by the National Oceanic and Atmospheric Administration (NOAA), is suitable for use in geographic information systems (GIS) and follows a specific attribution scheme (C-COAST) influenced by international standards. The metadata was last updated on March 13, 2026.
High-resolution vector shoreline data for the Hudson River in New York, compiled from imagery. The data uses the NOAA Coastal Cartographic Object Attribute Source Table (C-COAST) attribution scheme. This resource is part of the NOAA InPort catalog item 39808.
A high-resolution historical shoreline dataset for the region from Yonkers to 145th Street, New York and New Jersey, automated for GIS use. The data were derived from shoreline maps produced by the NOAA National Ocean Service and its predecessor agencies, based on imagery interpretation and field surveys. Attribution follows the NGS-developed C-COAST scheme, influenced by the International Hydrographic Organization's S-57 standard.
East River shoreline data from 3rd Street to Hell Gate in New York, compiled by the National Oceanic and Atmospheric Administration. The dataset provides a high-resolution vector shoreline based on office interpretation of imagery, suitable for use as a GIS data layer. It includes both line and point shapefiles with attribution following the NGS-developed C-COAST scheme.
Forest Service R&D research data on live tree species basal area across the contiguous United States for the 2000-2009 period. This archive preserves and shares quality science from U.S. Department of Agriculture researchers, including data from Experimental Forests and Ranges.
Forest Service Research and Development (FS R&D) data archive contains spatial wildfire occurrence records for the United States. The dataset covers a 29-year period from 1992 to 2020. It is a resource for accessing both short and long-term FS R&D research data, including Experimental Forest and Range data.
8,500 rows of synthetic operational and customer satisfaction data simulate the Indonesian food delivery market, authored by ZakyF in 2026. The records mimic services like GoFood or GrabFood and are engineered with intentional data quality issues like outliers and missing values.
Vision Zero Street Team members conducted hands-on safety exercises with the public, covering safe walking, biking, and vehicle blind spots. The dataset documents outreach activities where promotional and educational materials were distributed. It is published by the City of New York and was last updated on March 22, 2026.
Food delivery platform analytics data structured for SQL querying. The dataset is hosted on Kaggle, but its specific origin, size, and creation date are not detailed. Columns and sample data are unknown, requiring verification after download to assess content.