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Found 86 result(s)
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Institutional Repository of the University of Agriculture in Krakow (Poland). It includes the scientific achievements of the university's staff and students, including raw research data, as well as full texts of journals published by the University of Agriculture in Krakow.
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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.
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The Mansfeld's World Database of Agriculture and Horticultural Crops is an online database. As a contribution to the project "Federal Information System on Genetic Resources" (BIG, http://www.big-flora.de/). It reflects the contents of "Mansfeld's Encyclopedia of Agricultural and Horticultural Crops" (Hanelt and IPK 2001) and contains information on 6,100 crop plant species, excluding forestry and ornamental plants. Each species entry provides nomenclature and synonymy, common names in different languages, spontaneous distribution and regions of cultivation, uses, images, references, but also the ancestral species and notes on the phylogeny, variation and history.
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INRAE is the world’s first organisation specialized on agricultural, food and environmental sciences. Data INRAE is offered by INRAE as part of its mission to open the results of its research. Data INRAE will share research data in relation with food, nutrition, agriculture and environment. It includes experimental, simulation and observation data, omic data, survey and text data. Only data produced by or in collaboration with INRAE will be hosted in the repository, but anyone can access the metadata and the open data.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
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The Ontario Natural Heritage Information Centre (NHIC) compiles, maintains and provides information on rare, threatened and endangered species and spaces in Ontario. This information is stored in a central repository composed of computerized databases, map files and an information library, which are accessible for conservation applications, land use development planning, park management, etc. Ministry of Natural Resources, Ontario.
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The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is a community-driven climate impact modeling initiative that aims to contribute to a quantitative and cross-sectoral synthesis of the various impacts of climate change, including associated uncertainties. It is designed as a continuous model intercomparison and improvement process for climate impact models and is supported by the international climate impact research community. ISIMIP is organized into simulation rounds, for which a simulation protocol specifies a set of common experiments. The protocol further describes a set of climate and direct human forcing data to be used as input data for all ISIMIP simulations. Based on this information, modelling groups from different sectors (e.g. agriculture, biomes, water) perform simulations using various climate impact models. After the simulations are performed, the data is collected by the ISIMIP data team, quality controlled and eventually published on the ISIMIP Repository. From there, it can be freely accessed for further research and analyses. The data is widely used within academia, but also by companies and civil society. ISIMIP was initiated by the Potsdam Institute for Climate Impact Research (PIK) and the International Institute for Applied Systems Analysis (IIASA).
The Met Office is the UK's National Weather Service. We have a long history of weather forecasting and have been working in the area of climate change for more than two decades. As a world leader in providing weather and climate services, we employ more than 1,800 at 60 locations throughout the world. We are recognised as one of the world's most accurate forecasters, using more than 10 million weather observations a day, an advanced atmospheric model and a high performance supercomputer to create 3,000 tailored forecasts and briefings a day. These are delivered to a huge range of customers from the Government, to businesses, the general public, armed forces, and other organisations.
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.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
The USDA Agricultural Marketing Service (AMS) Cotton Program maintains a National Database (NDB) in Memphis, Tennessee for owner access to cotton classification data. The NDB is computerized telecommunications system which allows owners or authorized agents of owners to retrieve classing data from the current crop and/or the previous four crops. The NDB stores classing information from all 10 regional classing offices.
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Phaidra Vetmeduni Vienna is the Universitys platform for long-term archiving of digital collections such as Thesis and Research Data. In two years we would enlarge the collection for archive materials such as fotos, books an dias f.e.
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.
The International Soil Carbon Network (ISCN) is a science-based network that facilitates data sharing, assembles databases, identifies gaps in data coverage, and enables spatially explicit assessments of soil carbon in context of landscape, climate, land use, and biotic variables. The ISCN Database is an evolving data resource. Because it is too large to present in one file, it is available as a set of documents, reports, and tables; because it changes over time, it is important to note the version date stamped in the upper-left corner of any dataset that you access.