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Found 4 result(s)

Centre for Environmental Data Analysis

CEDA

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The Centre for Environmental Data Analysis (CEDA) serves the environmental science community through managing data centres, data analysis environments, and participation in a host of relevant research projects. We aim to support environmental science, further environmental data archival practices, and develop and deploy new technologies to enhance access to data. Additionally we provide services to aid large scale data analysis. The CEDA Archive operates the atmospheric and earth observation data centre functions on behalf of NERC for the UK atmospheric science and earth observation communities. It covers climate, composition, observations and NWP data as well as various earth observation datasets, including airborne and satellite data and imagery. Prior to November 2016 these functions were operted by CEDA under the titles of the British Atmospheric Data Centre (BADC) and the NERC Earth Observation Data Centre (NEODC). CEDA also operates the UK Solar System Data Centre (UKSSDC), which curates and provides access to archives of data from the upper atmosphere, ionosphere and Earth's solar environment.

Biological and Chemical Oceanography Data Management Office

BCO-DMO

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The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is a publicly accessible earth science data repository created to curate, publicly serve (publish), and archive digital data and information from biological, chemical and biogeochemical research conducted in coastal, marine, great lakes and laboratory environments. The BCO-DMO repository works closely with investigators funded through the NSF OCE Division’s Biological and Chemical Sections and the Division of Polar Programs Antarctic Organisms & Ecosystems. The office provides services that span the full data life cycle, from data management planning support and DOI creation, to archive with appropriate national facilities.

KNB Data Repository

Knowledge Network for Biocomplexity

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The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.

HydroShare

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HydroShare is a system operated by The Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) that enables users to share and publish data and models in a variety of flexible formats, and to make this information available in a citable, shareable and discoverable manner. HydroShare includes a repository for data and models, and tools (web apps) that can act on content in HydroShare providing users with a gateway to high performance computing and computing in the cloud. With HydroShare you can: share data and models with colleagues; manage access to shared content; share, access, visualize, and manipulate a broad set of hydrologic data types and models; publish data and models and obtain a citable digital object identifier (DOI); aggregate resources into collections; discover and access data and models published by others; use the web services application programming interface (API) to programmatically access resources; and use integrated web applications to visualize, analyze and run models with data in HydroShare.