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Found 18 result(s)
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IDOC-DATA is a department of IDOC IDOC (Integrated Data & Operation Center) has existed since 2003 as a satellite operations center and data center for the Institute of Space Astrophysics (IAS) in Orsay, France. Since then, it has operated within the OSUPS (Observatoire des Sciences de l'Univers de l'Université Paris-Saclay - first french university in shanghai ranking), which includes three institutes: IAS, AIM (Astrophysique, Interprétation, Modélisation - IRFU, CEA) and GEOPS (Geosciences Paris-Saclay) . IDOC participates in the space missions of OSUPS and its partners, from mission design to long-term scientific data archiving. For each phase of the missions, IDOC offers three kinds of services in the scientific themes of OSUPS and therefore IDOC's activities are divided into three departments: IDOC-INSTR: instrument design and testing, IDOC-OPE: instrument operations, IDOC-DATA: data management and data value chain: to produce the different levels of data constructed from observations of these instruments and make them available to users for ergonomic and efficient scientific interpretation (IDOC-DATA). It includes the responsibility: - To build access to these datasets. - To offer the corresponding services such as catalogue management, visualization tools, software pipeline automation, etc. - To preserve the availability and reliability of this hardware and software infrastructure, its confidentiality where applicable and its security.
ISG' activities are on educational, research, and data distribution sides: principal purposes of ISG are the collection and distribution of geoid models, the collection and distribution of software for geoid computation, and the organization of technical schools on geoid determinations. ISG collects and disseminates worldwide local and regional geoid models estimated by geodetic Institutions and researchers of many countries. More than 30 countries are represented, listed in alphabetic order or localized on a map
The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy. Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008; SDSS-III 2008-2014; SDSS-IV 2013 ongoing), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. DSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), Max-Planck-Institut für Astronomie (MPIA Heidelberg), National Astronomical Observatory of China, New Mexico State University, New York University, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Portsmouth, University of Utah, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.
This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
Country
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).
Country
Multidisciplinary research data repository, hosted by DTU, the Danish Technical University.
A planetary-scale platform for Earth science data & analysis. Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. Scientists, researchers, and developers use Earth Engine to detect changes, map trends, and quantify differences on the Earth's surface.
The NCAR Climate Data Gateway provides data discovery and access services for global and regional climate model data, knowledge, and software. The NCAR Climate Data Gateway supports community access to data products from many of NCAR's community modeling efforts, including the IPCC, PCM, AMPS, CESM, NARCCAP, and NMME activities. Data products are generally open and available, however, download access may require a login.
Country
TUdatalib is the institutional repository of the TU Darmstadt for research data. It enables the structured storage of research data and descriptive metadata, long-term archiving (at least 10 years) and, if desired, the publication of data including DOI assignment. In addition there is a fine granular rights and role management.
Repository for New Mexico Experimental Program to Stimulate Competitive Research Data Collection. Provides access to data generated by the Energize New Mexico project as well as data gathered in our previous project that focused on Climate Change Impacts (RII 3). NM EPSCoR contributes its data to the DataONE network as a member node: https://search.dataone.org/#profile/NMEPSCOR Digital Repository NM EPSCoR is part of UNM Digital Repository https://digitalrepository.unm.edu/ see also: https://data.nmepscor.org/
The ChemBio Hub vision is to provide the tools that will make it easier for Oxford University scientists to connect with colleagues to improve their research, to satisfy funders that the data they have paid for is being managed according to their policies, and to make new alliances with pharma and biotech partners. Funding and development of the ChemBio Hub was ending on the 30th June 2016. Please be reassured that the ChemBio Hub system and all your data will continue to be secured on the SGC servers for the foreseeable future. You can continue to use the services as normal.