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Found 16 result(s)
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
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.
RADAR service offers the ability to search for research data descriptions of the Natural Resources Institute Finland (Luke). The service includes descriptions of research data for agriculture, forestry and food sectors, game management, fisheries and environment. The public web service aims to facilitate discovering subjects of natural resources studies. In addition to Luke's research data descriptions one can search metadata of the Finnish Environment Institute (SYKE). The interface between Luke and SYKE metadata services combines Luke's research data descriptions and SYKE's descriptions of spatial datasets and data systems into a unified search service.
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.
NKN is now Research Computing and Data Services (RCDS)! We provide data management support for UI researchers and their regional, national, and international collaborators. This support keeps researchers at the cutting-edge of science and increases our institution's competitiveness for external research grants. Quality data and metadata developed in research projects and curated by RCDS (formerly NKN) is a valuable, long-term asset upon which to develop and build new research and science.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
eCommons is a service of the Cornell University Library that provides long-term access to a broad range of Cornell-related digital content of enduring value. eCommons accepts both educational and research-oriented content, including pre- and post-publication papers, datasets, technical reports, theses and dissertations, books, lectures, presentations and more.
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.
The purpose of the Virginia Tech Data Repository is to highlight, preserve, and provide access to research products (e.g. datasets) of the Virginia Tech community, and in doing so help to disseminate the intellectual output of the university in its land-grant mission. The Virginia Tech Data Repository and Virginia Tech serve the Commonwealth of Virginia, the nation, and the world’s community through the discovery and dissemination of new knowledge.
Research Data Repository of the Instituto Federal Goiano - Campus Urutaí, a Brazilian public institution of the Ministry of Education. The project is an initiative of the Directorate of Post-Graduate Studies, Research and Innovation of the Federal Institute of Goiás - Campus Urutaí, which follows the philosophy of Open Science, for expansion and valuation of scientific research, aiming to provide data from technical-scientific observations and experimentation, ensuring that its authors, researchers and students receive all the credit they deserve as agents generating data. At the same time, the appropriate reuse of data is envisaged, whether in didactic-pedagogical activities or in new research.