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Found 10 result(s)
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Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).
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 farmersā€™ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISAā€™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. CSISAā€™s repository contains rich datasets, including on-station trial data from 2009ā€“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 ā€“ 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 2012ā€“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. CSISAā€™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 farmersā€™ 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.
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.
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The Australian Data Archive (ADA) provides a national service for the collection and preservation of digital research data and to make these data available for secondary analysis by academic researchers and other users. Data are stored in seven sub-archives: Social Science, Historical, Indigenous, Longitudinal, Qualitative, Crime & Justice and International. Along with Australian data, ADA International is also a repository for studies by Australian researchers conducted in other countries, particularly throughout the Asia-Pacific region. The ADA International data catalogue includes links to studies from countries including New Zealand, Bangladesh, Cambodia, China, Indonesia, and several other countries. In 2017 the archive systems moved from the existing Nesstar platform to the new ADA Dataverse platform https://dataverse.ada.edu.au/
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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The TRR170-DB was set up to manage data products of the collaborative research center TRR 170 'Late Accretion onto Terrestrial Planets' (https://www.trr170-lateaccretion.de/). However, meanwhile the repository also stores data by other institutions and researchers. Data include laboratory and other instrumental data on planetary samples, remote sensing data, geological maps and model simulations.
UNC Dataverse is an open-source repository software application for archiving, sharing, and accessing research data of all kinds. Each dataverse within the larger repository contains a multitude of datasets, and each dataset contains descriptive metadata and data files. UNC Dataverse is hosted by Odum Institute for Research in Social Science.
The International Maize and Wheat Improvement Center (CIMMYT) provides a free, open access repository of research software, studies, and datasets produced and developed by CIMMYT scientists as well as the results of the Seeds of Discovery project, which makes available genetic profiles of wheat and maize, two of mankind's three major cereal crops.