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Found 11 result(s)
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The Norwegian Marine Data Centre (NMD) at the Institute of Marine Research was established as a national data centre dedicated to the professional processing and long-term storage of marine environmental and fisheries data and production of data products. The Institute of Marine Research continuously collects large amounts of data from all Norwegian seas. Data are collected using vessels, observation buoys, manual measurements, gliders – amongst others. NMD maintains the largest collection of marine environmental and fisheries data in Norway.
Country
<<<!!!<<< The repository is no longer available 2020-02-21: no more access to "Environment Climate Data Sweden" >>>!!!<<< The transfer of records from the Environment Climate Data Sweden (ECDS) database to the Swedish National Dataservice (SND) https://www.re3data.org/repository/r3d100010146 was completed in 2019. SND is a national research infrastructure with a primary function to support the accessibility, preservation, and re-use of research data and related materials. You can search the SND research data portal specifically for Natural Science or Agricultural and Veterinary Sciences datasets. Data descriptions with associated datasets, or a direct reference/URL to data, have been migrated from the ECDS portal to the SND research data portal. Previous links to these data are now automatically directed to an SND catalogue entry. Records in the ECDS catalogue that only contained metadata (ie information that data could be accessed through another portal, e.g. Pangea), now link directly to the portal in question. If you want to make one of those data descriptions searchable in SND’s catalogue, please contact SND on snd@snd.gu.se. A small number of records were neither migrated to SND nor redirected to external providers, and they redirect. Contact SND on snd@snd.gu.se if you want more information about the closing of the ECDS portal and the migration of data descriptions to SND’s research data catalogue.
!!! <<< the repository is offline >>> !!! The CBIF provides primary data on biological species of interest to Canadians. CBIF supports a wide range of social and economic decisions including efforts to conserve our biodiversity in healthy ecosystems, use our biological resources in sustainable ways, and monitor and control pests and diseases. Tools provided by the CBIF include the Integrated Taxonomic Information System (ITIS), Species Access Network, Online Mapping, and the SpeciesBank, including Butterflies of Canada. The CBIF is a member of the Global Biodiversity Information Facility (GBIF).
The NASA Earth Exchange (NEX) represents a platform for the Earth science community that provides a mechanism for scientific collaboration and knowledge sharing. NEX combines supercomputing, Earth system modeling, workflow management, NASA remote sensing data feeds, and a knowledge sharing platform to deliver a complete work environment in which users can explore and analyze large datasets, run modeling codes, collaborate on new or existing projects, and quickly share results among the Earth Science communities. Includes some local data collections as well as links to data on other sites. On January 31st, 2019, the NEX portal will be down-scoped; member logins will be suspended and the portal contents transitioned to a static set of archives. New projects and resources will no longer be possible after this occurs.
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.
PISCO researchers collect biological, chemical, and physical data about ocean ecosystems in the nearshore portions of the California Current Large Marine Ecosystem. Data are archived and used to create summaries and graphics, in order to ensure that the data can be used and understood by a diverse audience of managers, policy makers, scientists and the general public.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
Country
SAFER-Data is a web-based interface to the Environmental Data Archive maintained by the Environmental Research Centre (ERC) in the Environmental Protection Agency (EPA) of Ireland, who has responsibilities for a wide range of licensing, enforcement, monitoring and assessment activities associated with environmental protection.
Country
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.