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Found 27 result(s)
China Earthquake Data Center provides Seismic data, geomagnetic data, geoelectric data, terrain data and underground fluid change data. It is only open in the Seismological Bureau.
The CiardRING is a global directory of web-based information services and datasets for agricultural research for development (ARD). It is the principal tool created through the CIARD initiative to allow information providers to register their services and datasets in various categories and so facilitate the discovery of sources of agriculture-related information across the world. The RING aims to provide an infrastructure to improve the accessibility of the outputs of agricultural research and of information relevant to agriculture.
>>>!!!<<< 2019-01: Global Land Cover Facility goes offline see https://spatialreserves.wordpress.com/2019/01/07/global-land-cover-facility-goes-offline/ ; no more access to http://www.landcover.org >>>!!!<<< The Global Land Cover Facility (GLCF) provides earth science data and products to help everyone to better understand global environmental systems. In particular, the GLCF develops and distributes remotely sensed satellite data and products that explain land cover from the local to global scales.
The EUROLAS Data Center (EDC) is one of the two data centers of the International Laser Ranging Service (ILRS). It collects, archives and distributes tracking data, predictions and other tracking relevant information from the global SLR network. Additionally EDC holds a mirror of the official Web-Pages of the ILRS at Goddard Space Flight Center (GSFC). And as result of the activities of the Analysis Working Group (AWG) of the ILRS, DGFI has been selected as analysis centers (AC) and as backup combination center (CC). This task includes weekly processing of SLR observations to LAGEOS-1/2 and ETALON-1/2 to compute station coordinates and earth orientation parameters. Additionally the combination of SLR solutions from the various analysis centres to a combinerd ILRS SLR solution.
The US Virtual Astronomical Observatory (VAO) is the VO effort based in the US, and it is one of many VO projects currently underway worldwide. The primary emphasis of the VAO is to provide new scientific research capabilities to the astronomy community. Thus an essential component of the VAO activity is obtaining input from US astronomers about the research tools that are most urgently needed in their work, and this information will guide the development efforts of the VAO. >>>!!!<<< Funding discontinued in 2014 and all software, documentation, and other digital assets developed under the VAO are stored in the VAO Project Repository https://sites.google.com/site/usvirtualobservatory/ . Code is archived on Github https://github.com/TomMcGlynn/usvirtualobservatory . >>>!!!<<<
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
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.
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
The Square Kilometre Array (SKA) is a radio telescope with around one million square metres of collecting area, designed to study the Universe with unprecedented speed and sensitivity. The SKA is not a single telescope, but a collection of various types of antennas, called an array, to be spread over long distances. The SKA will be used to answer fundamental questions of science and about the laws of nature, such as: how did the Universe, and the stars and galaxies contained in it, form and evolve? Was Einstein’s theory of relativity correct? What is the nature of ‘dark matter’ and ‘dark energy’? What is the origin of cosmic magnetism? Is there life somewhere else in the Universe?
The global data compilation consisting of ca. 60,000 data points may be downloaded in csv/xml format. This compilation does not contain the descriptive codes relating to metadata that were included in the previous compilations. Users are advised to consult the references and make their own interpretations as to the quality of the data.
-----<<<<< The repository is no longer available. This record is out-dated. The Matter lab provides the archived database version of 2012 and 2013 at https://www.matter.toronto.edu/basic-content-page/data-download. Data linked from the World Community Grid - The Clean Energy Project see at https://www.worldcommunitygrid.org/research/cep1/overview.do and on fighshare https://figshare.com/articles/dataset/moldata_csv/9640427 >>>>>----- The Clean Energy Project Database (CEPDB) is a massive reference database for organic semiconductors with a particular emphasis on photovoltaic applications. It was created to store and provide access to data from computational as well as experimental studies, on both known and virtual compounds. It is a free and open resource designed to support researchers in the field of organic electronics in their scientific pursuits. The CEPDB was established as part of the Harvard Clean Energy Project (CEP), a virtual high-throughput screening initiative to identify promising new candidates for the next generation of carbon-based solar cell materials.
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Launched in November 1995, RADARSAT-1 provided Canada and the world with an operational radar satellite system capable of timely delivery of large amounts of data. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. RADARSAT-1 was a Canadian-led project involving the Canadian federal government, the Canadian provinces, the United States, and the private sector. It provided useful information to both commercial and scientific users in such fields as disaster management, interferometry, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. In 2007, RADARSAT-2 was launched, producing over 75,000 images per year since. In 2019, the RADARSAT Constellation Mission was deployed, using its three-satellite configuration for all-condition coverage. More information about RADARSAT-2 see https://mda.space/en/geo-intelligence/ RADARSAT-2 PORTAL see https://gsiportal.mda.space/gc_cp/#/map
The DBCP is an international program coordinating the use of autonomous data buoys to observe atmospheric and oceanographic conditions, over ocean areas where few other measurements are taken.
The MPC is responsible for the designation of minor bodies in the solar system: minor planets; comets, in conjunction with the Central Bureau for Astronomical Telegrams (CBAT); and natural satellites (also in conjunction with CBAT). The MPC is also responsible for the efficient collection, computation, checking and dissemination of astrometric observations and orbits for minor planets and comets
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
EMSC collects real time parametric data (source parmaters and phase pickings) provided by 65 seismological networks of the Euro-Med region. These data are provided to the EMSC either by email or via QWIDS (Quake Watch Information Distribution System, developped by ISTI). The collected data are automatically archived in a database, made available via an autoDRM, and displayed on the web site. The collected data are automatically merged to produce automatic locations which are sent to several seismological institutes in order to perform quick moment tensors determination.
The Atlas of Living Australia (ALA) combines and provides scientifically collected data from a wide range of sources such as museums, herbaria, community groups, government departments, individuals and universities. Data records consist of images, literature, molecular DNA data, identification keys, species interaction data, species profile data, nomenclature, source data, conservation indicators, and spatial data.
Forestry Images provides an accessible and easy to use archive of high quality images related to forest health and silviculture
Provides quick, uncluttered access to information about Heliophysics research data that have been described with SPASE resource descriptions.
The IUCN Red List of Threatened Species provides taxonomic, conservation status and distribution data on plants and animals that are critically endangered, endangered and vulnerable. Data are available in Esri File Geodatabase format, Esri Shapefile format, and Excel format.
This database is a global archive and describes plant traits from throughout the globe. TRY is a network of vegetation scientists headed by DIVERSITAS, IGBP, iDiv, the Max Planck Institute for Biogeochemistry and an international Advisory Board. About half of the data are geo-referenced, providing a global coverage of more than 8000 measurement sites.
virus mentha archives evidence about viral interactions collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. virus mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". virus mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. virus mentha offers direct access to viral families such as: Orthomyxoviridae, Orthoretrovirinae and Herpesviridae plus, it offers the unique possibility of searching by host organism. The website and the graphical application are designed to make the data stored in virus mentha accessible and analysable to all users.virus mentha superseeds VirusMINT. The Source databases are: MINT, DIP, IntAct, MatrixDB, BioGRID.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, we end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, we capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome.