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Found 11 result(s)
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The information system Graffiti in Germany (INGRID) is a cooperation project between the linguistics department at the University of Paderborn and the art history department at the Karlsruhe Institute of Technology (KIT). As part of the joint project, graffiti image collections will be compiled, stored in an image database and made available for scientific use. At present, more than 100,000 graffiti from the years 1983 to 2018 from major German cities are recorded, including Cologne, Mannheim and Munich.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
ForestPlots.net is a web-accessible secure repository for forest plot inventories in South America, Africa and Asia. The database includes plot geographical information; location, taxonomic information and diameter measurements of trees inside each plot; and participants in plot establishment and re-measurement, including principal investigators, field assistants, students.
The name Earth Online derives from ESA's Earthnet programme. Earthnet prepares and attracts new ESA Earth Observation missions by setting the international cooperation scheme, preparing the basic infrastructure, building the scientific and application Community and competency in Europe to define and set-up own European Programmes in consultation with member states. Earth Online is the entry point for scientific-technical information on Earth Observation activities by the European Space Agency (ESA). The web portal provides a vast amount of content, grown and collected over more than a decade: Detailed technical information on Earth Observation (EO) missions; Satellites and sensors; EO data products & services; Online resources such as catalogues and library; Applications of satellite data; Access to promotional satellite imagery. After 10 years of operations on distinct sites, the two principal portals of ESA Earth Observation - Earth Online (earth.esa.int) and the Principal Investigator's Portal (eopi.esa.int) have moved to a new platform. ESA's technical and scientific earth observation user communities will from now on be served from a single portal, providing a modern and easy-to-use interface to our services and data.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDA’s services include automated archiving of imaging studies from all of the University’s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
LONI’s Image and Data Archive (IDA) is a secure data archiving system. The IDA uses a robust infrastructure to provide researchers with a flexible and simple interface for de-identifying, searching, retrieving, converting, and disseminating their biomedical data. With thousands of investigators across the globe and more than 21 million data downloads to data, the IDA guarantees reliability with a fault-tolerant network comprising multiple switches, routers, and Internet connections to prevent system failure.
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CosmoHub is a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets