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Found 14 result(s)

National Agricultural Statistics Service

NASS

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As a department of the United States Department of Agriculture (USDA) the National Agricultural Statistics Service (NASS) continually surveys and reports on U.S. agriculture. NASS reports include production and supplies of food and fiber, prices paid and received by farmers, farm labor and wages, farm finances, chemical use, and changes in the demographics of U.S. producers. NASS provides objective and unbiased statistics of states and counties, while safeguarding the privacy of farmers and ranchers.

USDA Economics, Statistics and Market Information System

ESMIS

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The USDA Economics, Statistics and Market Information System contains reports and datasets of multiple agencies within the United States Department of Agriculture, including the Agricultural Marketing Service, the Economic Research Service, the Foreign Agricultural Service, the National Agricultural Statistics Service, and the World Agricultural Outlook Board. Historical and current reports and datasets are included.

Alberta Food Composition Database

AFCDB

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The Alberta Food Composition Database (AFCDB) is the first comprehensive resource on food constituents, chemistry and biology dedicated to major Alberta-grown produce. It provides information on both macronutrients and micronutrients, including many of the constituents that give foods their flavor, color, taste, texture and aroma. Users can view the contents of the AFCDB from the “FoodView” (listing foods by their chemical composition) or the “ChemView” (listing chemicals by their food sources).

DaKS

Datenrepositorium Kassel

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DaKS is the institutional repository of the University of Kassel for research data. It offers structured storage of research data alongside with descriptive metadata, long-term archiving for at least 10 years and – if requested – the publication of the dataset with a DOI.

EarthWorks

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EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.

Chesapeake Bay Data Hub

Chesapeake Bay Program

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This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.

CSISA Data Repository

Cereal Systems Initiative for South Asia (CSISA) Research Data

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In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.

CIRAD Dataverse

Données de recherche du CIRAD

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The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.

NASC

The European Arabidopsis Stock Centre

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The Nottingham Arabidopsis Stock Centre (NASC) provides seed and information resources to Europe researchers.

Web Soil Survey

NRCS Web Soil Survey

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Web Soil Survey (WSS) provides soil data and information produced by the National Cooperative Soil Survey. It is operated by the USDA Natural Resources Conservation Service (NRCS) and provides access to the largest natural resource information system in the world. NRCS has soil maps and data available online for more than 95 percent of the nation’s counties and anticipates having 100 percent in the near future. The site is updated and maintained online as the single authoritative source of soil survey information.

Natural Resources Conservation Service Soils

USDA NRCS Soils

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Soils is part of the National Cooperative Soil Survey, an effort of Federal and State agencies, universities, and professional societies to deliver science-based soil information.

UNAVCO

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UNAVCO promotes research by providing access to data that our community of geodetic scientists uses for quantifying the motions of rock, ice and water that are monitored by a variety of sensor types at or near the Earth's surface. After processing, these data enable millimeter-scale surface motion detection and monitoring at discrete points, and high-resolution strain imagery over areas of tens of square meters to hundreds of square kilometers. The data types include GPS/GNSS, imaging data such as from SAR and TLS, strain and seismic borehole data, and meteorological data. Most of these can be accessed via web services. In addition, GPS/GNSS datasets, TLS datasets, and InSAR products are assigned digital object identifiers.

University of Manitoba Dataverse

University of Manitoba Libraries Dataverse

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UM Dataverse is part of the Dataverse Project conceived of by Harvard University. It is an open source repository to assist researchers in the creation, management and dissemination of their research data. UM Dataverse allows for the creation of multiple collaborative environments containing datasets, metadata and digital objects. UM Dataverse provides formal scholarly data citations and can help with data requirements from publishers and funders.

Pig Expression Data Explorer

PEDE

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The Pig Expression Data Explorer (PEDE) database system stores full-length cDNA libraries of swine data accesible via keyword and ID searches. Data is publically available, and may specifically interest genetic researchers interested in disease sucsceptibly, and major and minor porcine specific antigens.