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Found 7 result(s)
The Virtual Research Environment (VRE) is an open-source data management platform that enables medical researchers to store, process and share data in compliance with the European Union (EU) General Data Protection Regulation (GDPR). The VRE addresses the present lack of digital research data infrastructures fulfilling the need for (a) data protection for sensitive data, (b) capability to process complex data such as radiologic imaging, (c) flexibility for creating own processing workflows, (d) access to high performance computing. The platform promotes FAIR data principles and reduces barriers to biomedical research and innovation. The VRE offers a web portal with graphical and command-line interfaces, segregated data zones and organizational measures for lawful data onboarding, isolated computing environments where large teams can collaboratively process sensitive data privately, analytics workbench tools for processing, analyzing, and visualizing large datasets, automated ingestion of hospital data sources, project-specific data warehouses for structured storage and retrieval, graph databases to capture and query ontology-based metadata, provenance tracking, version control, and support for automated data extraction and indexing. The VRE is based on a modular and extendable state-of-the art cloud computing framework, a RESTful API, open developer meetings, hackathons, and comprehensive documentation for users, developers, and administrators. The VRE with its concerted technical and organizational measures can be adopted by other research communities and thus facilitates the development of a co-evolving interoperable platform ecosystem with an active research community.
Junar provides a cloud-based open data platform that enables innovative organizations worldwide to quickly, easily and affordably make their data accessible to all. In just a few weeks, your initial datasets can be published, providing greater transparency, encouraging collaboration and citizen engagement, and freeing up precious staff resources.
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Launched in November 1995, RADARSAT-1 provided Canada and the world with an operational radar satellite system capable of timely delivery of large amounts of data. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. RADARSAT-1 was a Canadian-led project involving the Canadian federal government, the Canadian provinces, the United States, and the private sector. It provided useful information to both commercial and scientific users in such fields as disaster management, interferometry, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. In 2007, RADARSAT-2 was launched, producing over 75,000 images per year since. In 2019, the RADARSAT Constellation Mission was deployed, using its three-satellite configuration for all-condition coverage. More information about RADARSAT-2 see https://mda.space/en/geo-intelligence/ RADARSAT-2 PORTAL see https://gsiportal.mda.space/gc_cp/#/map
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
The National Trauma Data BankĀ® (NTDB) is the largest aggregation of trauma registry data ever assembled. The goal of the NTDB is to inform the medical community, the public, and decision makers about a wide variety of issues that characterize the current state of care for injured persons. Registry data that is collected from the NTDB is compiled annually and disseminated in the forms of hospital benchmark reports, data quality reports, and research data sets. Research data sets that can be used by researchers. To gain access to NTDB data, researchers must submit requests through our online application process