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<<<!!!<<< CRAWDAD has moved to IEEE-Dataport https://www.re3data.org/repository/r3d100012569 The datasets in the Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) repository are now hosted as the CRAWDAD Collection on IEEE Dataport. After nearly two decades as a stand-alone archive at crawdad.org, the migration of the collection to IEEE DataPort provides permanence and new visibility. >>>!!!>>>
TERN provides open data, research and management tools, data infrastructure and site-based research equipment. The open access ecosystem data is provided by TERN Data Discovery Portal , see https://www.re3data.org/repository/r3d100012013
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The CDPP is the French national data centre for natural plasmas of the solar system. The CDPP assures the long term preservation of data obtained primarily from instruments built using French resources, and renders them readily accessible and exploitable by the international community. The CDPP also provides services to enable on-line data analysis (AMDA), 3D data visualization in context (3DView), and a propagation tool which bridges solar perturbations to in-situ measurements. The CDPP is involved in the development of interoperability, participates in several Virtual Observatory projects, and supports data distribution for scientific missions (Solar Orbiter, JUICE).
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depositar — taking the term from the Portuguese/Spanish verb for to deposit — is an online repository for research data. The site is built by the researchers for the researchers. You are free to deposit, discover, and reuse datasets on depositar for all your research purposes.
EUMETSAT's primary objective is to establish, maintain and exploit European systems of operational meteorological satellites. EUMETSAT is responsible for the launch and operation of the satellites and for delivering satellite data to end-users as well as contributing to the operational monitoring of climate and the detection of global climate changes. The EUMETSAT Product Navigator is the catalogue for all EUMETSAT data and products.
The Marine Geoscience Data System (MGDS) is a trusted data repository that provides free public access to a curated collection of marine geophysical data products and complementary data related to understanding the formation and evolution of the seafloor and sub-seafloor. Developed and operated by domain scientists and technical specialists with deep knowledge about the creation, analysis and scientific interpretation of marine geoscience data, the system makes available a digital library of data files described by a rich curated metadata catalog. MGDS provides tools and services for the discovery and download of data collected throughout the global oceans. Primary data types are geophysical field data including active source seismic data, potential field, bathymetry, sidescan sonar, near-bottom imagery, other seafloor senor data as well as a diverse array of processed data and interpreted data products (e.g. seismic interpretations, microseismicity catalogs, geologic maps and interpretations, photomosaics and visualizations). Our data resources support scientists working broadly on solid earth science problems ranging from mid-ocean ridge, subduction zone and hotspot processes, to geohazards, continental margin evolution, sediment transport at glaciated and unglaciated margins.
Launched in December 2013, Gaia is destined to create the most accurate map yet of the Milky Way. By making accurate measurements of the positions and motions of stars in the Milky Way, it will answer questions about the origin and evolution of our home galaxy. The first data release (2016) contains three-dimensional positions and two-dimensional motions of a subset of two million stars. The second data release (2018) increases that number to over 1.6 Billion. Gaia’s measurements are as precise as planned, paving the way to a better understanding of our galaxy and its neighborhood. The AIP hosts the Gaia data as one of the external data centers along with the main Gaia archive maintained by ESAC and provides access to the Gaia data releases as part of Gaia Data Processing and Analysis Consortium (DPAC).