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Found 7 result(s)
The Genomic Observatories Meta-Database (GEOME) is a web-based database that captures the who, what, where, and when of biological samples and associated genetic sequences. GEOME helps users with the following goals: ensure the metadata from your biological samples is findable, accessible, interoperable, and reusable; improve the quality of your data and comply with global data standards; and integrate with R, ease publication to NCBI's sequence read archive, and work with an associated LIMS. The initial use case for GEOME came from the Diversity of the Indo-Pacific Network (DIPnet) resource.
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B2SHARE allows publishing research data and belonging metadata. It supports different research communities with specific metadata schemas. This server is provided for researchers of the Research Centre Juelich and related communities.
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BLLAST is a research programme aimed at exploring the late afternoon transition of the atmospheric boundary layer. The late afternoon period of the diurnal cycle of the boundary layer is poorly understood. This is yet an important transition period that impacts the transport and dillution of water vapour and trace species. The main questions adressed by the project are: - How the turbulence activity fades when heating by the surface decreases? - What is the impact on the transport of chemical species? - How relevant processes can be represented in numerical models? To answer all these questions, a field campaign was carried out during the summer of 2011 (from June 14 to July 8). Many observation systems were then deployed and operated by research teams coming from France and abroad. They were spanning a large spectrum of space and time scales in order to achieve a comprehensive description of the boundary layer processes. The observation strategy consisted in intensifying the operations in the late afternoon with tethered balloons, resarch aircrafts and UAVs.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
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The Climate Change Centre Austria - Data Centre provides the central national archive for climate data and information. The data made accessible includes observation and measurement data, scenario data, quantitative and qualitative data, as well as the measurement data and findings of research projects.
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Finnish Meteorological Institute (FMI) research data repository METIS is provided by EUDAT and enables the institute data to be preserved, discovered, and accessed. FMI covers a wide range of research on weather, sea, climate and space. According to the FMI's Research Data policy , publicly funded research data must be made available to the widest possible audience (under CC BY license, at the minimum), as the best way to maximize the data impact but also to do justice to all the hard labor put into collecting, cleaning, and analyzing the data.