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Found 11 result(s)
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The USN Research Data Archive is an institutional archive where research data produced and collected by University of South-East Norway's reseachers can be stored, made visible and accessible. The researcher can apply the necessary licenses and possibly put embargo and access restrictions on the research data.
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The Edition Topoi research platform is an innovative, reliable information infrastructure. It serves the publication of citable research data such as 3D models, high-resolution pictures, data and databases. The content and its meta data are subject to peer review and made available on an Open Access basis. The published or publishable combination of citable research content and its technical and contextually relevant meta data is defined as Citable. The public data are generated via a cloud and can be directly connected with the individual computing environment.
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BCCM/MUCL is a generalist fungal culture collection of over 30000 filamentous fungi, yeasts and arbuscular mycorrhizal fungi including type, reference and test strains. It provides curated documentation and information on these bioresourced in its database. The collections activities include the distribution of its holdings, the accession of new material in its public, safe and patent domains, and services valorising its holdings and/or expertise to cultivate, isolate and identify fungal diversity in natural and anthropological ecosystems, agro-food (food and feed transformation and spoilage), and fungal-plant interactions.
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.
IEDA2 is currently undergoing a website reconstruction and will be back soon. IEDA is a community-based facility that serves to support, sustain, and advance the geosciences by providing data services for observational Geoscience data from the Ocean, Earth, and Polar Sciences. IEDA welcomes and encourages investigators to contribute their data to the IEDA collections so that the data can be discovered and reused by a diverse community now and in the future. The IEDA collections are: EarthChem, Geochron, System for Earth Sample Registration (SESAR), Marine Geoscience Data System (MGDS), and USAP Data Center. Meta-Search provided on the portal through IEDA Data Browser http://www.iedadata.org/databrowser .
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The eAtlas is a website, mapping system and set of data visualisation tools for presenting research data in an accessible form that promotes greater use of this information. The eAtlas will serve as the primary data and knowledge repository for all NERP Tropical Ecosystems Hub projects, which focus on the on the Great Barrier Reef, Wet Tropics rainforest and Torres Strait. The eAtlas will capture and record research outcomes and make them available to research-users in a timely, readily accessible manner. It will host meta-data records and provide an enduring repository for raw data. It will also develop and host web visualisations to view information using a simple and intuitive interface. This will assist scientists with data discovery and allow environmental managers to access and investigate research data.
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SAMD is a repository for Standardized Atmospheric Measurement Data: Central Europe is a region with one of the most comprehensive networks for cloud and precipitation observations worldwide. To unify these observations, establish the infrastructure to store it and make it accessible to the research community is the goal of SAMD. SAMD is one result of the project "High Definition of Clouds and Precipitation in advancing Climate Prediction" (HD(CP)²).