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Found 7 result(s)

Southern California Earthquake Center

SCEC

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SCEC's mission includes gathering data on earthquakes, both in Southern California and other locales; integrate the information into a comprehensive understanding of earthquake phenomena; and communicate useful knowledge for reducing earthquake risk to society at large. The SCEC community consists of more than 600 scientists from 16 core institutions and 47 additional participating institutions. SCEC is funded by the National Science Foundation and the U.S. Geological Survey.

Bjerknes Climate Data Centre

BCDC

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The BCDC serves the research data obtained, and the data syntheses assembled, by researchers within the Bjerknes Centre for Climate Research. Furthermore it is open for all interested scientists independent of institution. All data from the different disciplines (e.g. geology, oceanography, biology, model community) will be archived in a long-term repository, interconnected and made publicly available by the BCDC. BCDC has collaborations with many international data repositories and actively archives metadata and data at those ensuring quality and FAIRness. BCDC has it's main focus on services for data management for external and internal funded projects in the field of climate research, provides data management plans and ensures that data is archived accordingly according to the best practices in the field. The data management services rank from project work for small external funded project to top-of-the-art data management services for research infrastructures on the ESFRI roadmap (e.g. RI ICOS – Integrated Carbon Observation System) and for provides products and services for Copernicus Marine Environmental Monitoring Services. In addition BCDC is advising various communities on data management services e.g. IOC UNESCO, OECD, IAEA and various funding agencies. BCDC will become an Associated Data Unit (ADU) under IODE, International Oceanographic Data and Information Exchange, a worldwide network that operates under the auspices of the Intergovernmental Oceanographic Commission of UNESCO and aims at becoming a part of ICSU World Data System.

datastore by Universität Münster

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datastore is the cross-domain research data repository of the University Münster (Germany). In datastore, scientific members of the University Münster can publish their research data following the FAIR principles, including the assignment of a DOI for each dataset as a persistent identifier.

Southern California Earthquake Data Center

SCEDC

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The Southern California Earthquake Data Center (SCEDC) operates at the Seismological Laboratory at Caltech and is the primary archive of seismological data for southern California. The 1932-to-present Caltech/USGS catalog maintained by the SCEDC is the most complete archive of seismic data for any region in the United States. Our mission is to maintain an easily accessible, well-organized, high-quality, searchable archive for research in seismology and earthquake engineering.

datacommons@psu

Penn State Data Commons

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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.

OpenTopography

A Portal to High-Resolution Topography Data and Tools

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OpenTopography facilitates community access to high-resolution, Earth science-oriented, topography data, and related tools and resources. The OpenTopography Facility is based at the San Diego Supercomputer Center at the University of California, San Diego and is operated in collaboration with colleagues in the School of Earth and Space Exploration at Arizona State University and Earthscope Consortium. Core operational support for OpenTopography comes from the National Science Foundation Earth Sciences.

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.