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Found 13 result(s)
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Welcome to the National Yang Ming Chiao Tung University Dataverse research data knowledge management website, where you can learn how to obtain, upload, cite and explore research data in the National Yang Ming Chiao Tung University Dataverse.
Country
Agri-environmental Research Data collection is part of the University of Guelph Research Data Repositories (University of Guelph Dataverse). The purpose of this collection is to provide access to, and long-term stewardship of, agricultural and environmental data created at or in cooperation with the University of Guelph.
For datasets from individual researchers or research groups affiliated with Stockholm University, who do not want set up a separate Dataverse for a project or institution. Metadata provisions for Geospatial, Social Science, Humanities, Astronomy, Astrophysics, Life Sciences and Journals (all optional, by choice) are included. Data curation help from Stockholm University Library possible on request.
Arca Data is Fiocruz's official repository for archiving, publishing, disseminating, preserving and sharing digital research data produced by the Fiocruz community or in partnership with other research institutes or bodies, with the aim of promoting new research, ensuring the reproducibility or replicability of existing research and promoting an Open and Citizen Science. Its objective is to stimulate the wide circulation of scientific knowledge, strengthening the institutional commitment to Open Science and free access to health information, in addition to providing transparency and fostering collaboration between researchers, educators, academics, managers and graduate students, to the advancement of knowledge and the creation of solutions that meet the demands of society.
The University of Guelph Research Data Repositories provide long-term stewardship of research data created at or in cooperation with the University of Guelph. The Data Repositories are guided by the FAIR Guiding Principles for scientific data management and stewardship which aim to improve the Findability, Accessibility, Interoperability and Reuse of research data. The Data Repositories is composed of two main collections: the Agri-environmental Research Data collection which houses agricultural and environmental research data, and the Cross-disciplinary Research Data collection which houses all other disciplinary research data.
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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.
Queen's University Dataverse is the institutional open access research data repository for Queen's University, featuring Queen's University Biological Station (QUBS) which includes research related to ecology, evolution, resource management and conservation, GIS, climate data, and environmental science.
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.
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 UK Data Service is a national data service funded by the ESRC to provide research access to the UK’s largest collection of social, economic and population data including UK government-sponsored surveys, cross-national surveys, longitudinal studies, UK census data, international aggregate, business data, and qualitative data. Designed to meet the data needs of researchers, students and teachers from all sectors, including academia, central and local government, charities and foundations, independent research centres, think tanks, business consultants and analysts, communities and the commercial sector, the UK Data Service provides access to high-quality social and economic data; support for policy-relevant research; guidance and training for the development of skills in data use, and the development of best practice in digital preservation and sharing. Data users can browse collections online and register to analyse and download them. Open Data collections are available for anyone to use. Key partners include JISC, the University of Manchester, University of Southampton, University of Leeds, University of Edinburgh and University College London (UCL). The lead partner is the UK Data Archive (https://service.re3data.org/repository/r3d100010215) based at the University of Essex, a Trusted Digital Repository (TDR) certified against the CoreTrustSeal (https://www.coretrustseal.org/) and certified against ISO27001 for Information Security (https://www.iso.org/standard/27001). The UK Data Service replaces the earlier ESRC investments of the Economic and Social Data Service (ESDS), the Secure Data Service (SDS), the Survey Question Bank and elements of the ESRC Census Programme.