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Found 14 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.
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The Common Research Data Repository (Deposita Dados) is a database for archiving, publishing, disseminating, preserving and sharing digital research data and its mission is to promote, support and facilitate the adoption of open access to the datasets of Brazilian researchers linked to scientific institutions that do not yet have their own research data repositories and/or of Brazilian researchers who have executed their datasets through scientific collaboration in foreign teaching and research institutions.
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.
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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.
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 George Mason University Dataverse is available for George Mason faculty, staff, and students to publish, share, and preserve their research data of enduring value. It is a companion to the Mason Archival Repository Service (https://mars.gmu.edu).
The Maine Dataverse Network is a cloud-based data repository intended to act as a long-term archive and to facilitate data sharing among the research community in accordance with NSF, NIH, NASA and other granting authority data management plan requirements. The Maine Dataverse Network offers a convenient and secure method of sharing and archiving data and is made available to the Maine research community at no cost.
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The Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.
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REDU is the institutional open research data repository of the University of Campinas, Brazil. It contains research data produced by all research groups of the University, in a wide range of scientific domains, which are indexed by DataCite DOI. Created at the end of 2020, it is coordinated by a scientific and technical committee composed by data librarians, IT professionals, and scientists representing user groups. Implemented on top of Dataverse, it exports metadata using OAIS. Files with sensitive content (due to ethics or legal constraints) are not stored therein - rather, only their metadata is recorded in REDU, as well as contact information so that interested researchers can contact the persons responsible for the files for conditional subsequent access. It is being little by little populated, following the University's Open Science policies.