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Found 14 result(s)
The Centre’s vision is a rural transformation in the developing world as smallholder households strategically increase their use of trees in agricultural landscapes to improve their food security, nutrition, income, health, shelter, social cohesion, energy resources and environmental sustainability. The Centre’s mission is to generate science-based knowledge about the diverse roles that trees play in agricultural landscapes, and to use its research to advance policies and practices, and their implementation, that benefit the poor and the environment.
Discovery is the digital repository of research, and related activities, undertaken at the University of Dundee. The content held in Discovery is varied and ranges from traditional research outputs such as peer-reviewed articles and conference papers, books, chapters and post-graduate research theses and data to records for artefacts, exhibitions, multimedia and software. Where possible Discovery provides full-text access to a version of the research. Discovery is the data catalogue for datasets resulting from research undertaken at the University of Dundee and in some instances the publisher of research data.
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The China National GeneBank database (CNGBdb) is a unified platform for biological big data sharing and application services. CNGBdb has now integrated a large amount of internal and external biological data from resources such as CNGB, NCBI, and the EBI. There are several sub-databases in CNGBdb, including literature, variation, gene, genome, protein, sequence, organism, project, sample, experiment, run, and assembly. Based on underlying big data and cloud computing technologies, it provides various data services, including archive, analysis, knowledge search, and management authorization of biological data. CNGBdb adopts data structures and standards of international omics, health, and medicine, such as The International Nucleotide Sequence Database Collaboration (INSDC), The Global Alliance for Genomics and Health GA4GH (GA4GH), Global Genome Biodiversity Network (GGBN), American College of Medical Genetics and Genomics (ACMG), and constructs standardized data and structures with wide compatibility. All public data and services provided by CNGBdb are freely available to all users worldwide. CNGB Sequence Archive (CNSA) is the bionomics data repository of CNGBdb. CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in life science, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, and Sequence. Moreover, CNSA has achieved the correlation of sample entities, sample information, and analyzed data on some projects. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in the life science of CNGBdb, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, Sequence. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.
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LIVIVO is an interdisciplinary search engine for literature and information in the field of life sciences. It is run by ZB MED – Information Centre for Life Sciences. LIVIVO automatically searches for the terms you enter in a central index of all the databases. The ZB MED Searchportal already provides a large amount of research data from DataCite data centres (e.g. Beijing Genomics Institute, Natural Environment Research Council) in the field of life sciences. These can be searched directly using the "Documenttype=research data" filter. A further integration of data from life science data repositories is planned.
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.
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.
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.
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.