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Found 13 result(s)
CORD is Cranfield University's research data repository, for secure preservation of institutional research data outputs. Cranfield is an exclusively postgraduate university that is a global leader for transformational research in technology and management. We are focused on the specialist themes of aerospace, defence and security, energy and power, environment and agrifood, manufacturing, transport systems, and water. The Cranfield School of Management is world leader in management education and research.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
The U.S. Antarctic Program Data Center (USAP-DC) provides the central Project Catalog for projects funded by the NSF for the U.S. Antarctic Program and Data Repository for multi-disciplinary investigator research datasets derived from these projects. Services provided support investigators in documenting, preserving, and disseminating their research results. All data are openly accessible to the international community for browse, search, and data download. Datasets are registered in the Antarctic Master Directory to comply with the Antarctic Treaty.
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Scicat allows users to access the metadata of raw and derived data which is taken at experiment facilities. Scientific datasets are linked to proposals and samples. Scientific datasets are can be linked to publications (DOI, PID). SciCat helps keeping track of data provenance (i.e. the steps leading to the final results). Scicat allows users to find data based on the metadata (both your own data and other peoples’ public data). In the long term, SciCat will help to automate scientific analysis workflows.
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.