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E-RA provides a permanent managed repository and knowledgebase for secure storage of metadata and data from Rothamsted's Long-term Experiments, the oldest, continuous agronomic experiments in the world. Together with the accompanying meteorological records, associated documentation and sample archive, it is a unique historical record of experiments that have been measured continuously since 1843. e-RA provides comprehensive descriptions of Rothamsted's long-term experiments including Broadbalk Wheat, Park Grass Hay, Hoosfield Barley, Rothamsted and Woburn Ley Arables, and Long-term Liming. e-RA maintains long-term routine data collections including crop yields, quality traits, agronomic management, soil chemistry, disease, and botanical diversity. The experiments are available as a research infrastructure to scientists and scientists are encouraged to deposit any new data generated with e-RA.
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In the framework of the Collaborative Research Centre/Transregio 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ (CRC/TR32, www.tr32.de), funded by the German Research Foundation from 2007 to 2018, a RDM system was self-designed and implemented. The so-called CRC/TR32 project database (TR32DB, www.tr32db.de) is operating online since early 2008. The TR32DB handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). The data is resulting from several field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected in the TR32DB.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
The International Center for Tropical Agriculture (CIAT), a member of the CGIAR Consortium, believes that open access contributes to its mission of reducing hunger and poverty, and improving human nutrition in the tropics through research aimed at increasing the eco-efficiency of agriculture. Research data produced by CIAT and its Partners is distributed freely whenever possible. Kindly note that these datasets require proper citation and citation information is included with the metadata for each dataset.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) consists in the merging, in 2016, of two previously-existing CZOs: BVET (India and Cameroon) and MSEC (Laos and Vietnam). The CZO Multiscale TROPIcal CatchmentS (M-TROPICS) provides the international scientific community with unique decennial time series of meteorological, hydrological, geochemical, and ecological variables in tropical environments. The CZO M-TROPICS involves academic and governmental partners in tropical countries (Cameroun, India, Lao PDR, and Vietnam) and is included in the Research Infrastructure OZCAR, the French contribution to the international CZO initiative.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.