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Found 380 result(s)
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Morph·D·Base has been developed to serve scientific research and education. It provides a platform for storing the detailed documentation of all material, methods, procedures, and concepts applied, together with the specific parameters, values, techniques, and instruments used during morphological data production. In other words, it's purpose is to provide a publicly available resource for recording and documenting morphological metadata. Moreover, it is also a repository for different types of media files that can be uploaded in order to serve as support and empirical substantiation of the results of morphological investigations. Our long-term perspective with Morph·D·Base is to provide an instrument that will enable a highly formalized and standardized way of generating morphological descriptions using a morphological ontology that will be based on the web ontology language (OWL - http://www.w3.org/TR/owl-features/). This, however, represents a project that is still in development.
The National Earth Observation Science Data Center, whose predecessor was the National Integrated Earth Observation Data Sharing Platform, has formed a sustainable, cross-agency, one-stop data sharing service capability after years of construction, and it is also the main channel for international exchange of remote sensing data in China. In the future, it will manage and coordinate scientific data resources in the field of earth observation on behalf of the country, and build a national-level earth observation big data infrastructure. Coordinate various industry data centers, scientific research institutions and enterprises in the field of Earth observation in China to cooperate in building a national strategic, fundamental, scientific, internationalized, and independent and controllable scientific big data environment in the field of Earth observation. On the basis of the already formed data ecology and cooperation mechanism, data sharing services, and international data cooperation, we will actively expand to the whole life cycle management of data and carry out data management work such as the collection, management, analysis and mining, and sharing services of national scientific data resources for Earth observation. Form a unified technical support system and data sharing service environment for Earth observation data in China. Maintain and enhance its international influence and become a domestic and international first-class scientific data center for Earth observation!
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The University of Göttingen preserves one of the most important collections of scientific collections. At more than 30 distributed locations on the Göttingen Campus, the collections reflect its disciplinary diversity: the spectrum ranges from archeology to zoology, from astrophysical instruments to the living cell cultures of the algae collection. Historical legacy dating back to the Age of Enlightenment: The founding holdings of the Royal Academic Museum of Georgia Augusta are largely preserved. Research and teaching to date access to the collection objects and increase the stocks. Get to know our collections in this portal, which have been used to create knowledge for three centuries.
EarthWorks is a discovery tool for geospatial (a.k.a. GIS) data. It allows users to search and browse the GIS collections owned by Stanford University Libraries, as well as data collections from many other institutions. Data can be searched spatially, by manipulating a map; by keyword search; by selecting search limiting facets (e.g., limit to a given format type); or by combining these options.
The WHOI Ship DataGrabber system provides the oceanographic community on-line access to underway ship data collected on the R/V Atlantis, Knorr, Oceanus, and Tioga (TBD). All the shipboard data is co-registered with the ship's GPS time and navigation systems.
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DARTS primarily archives high-level data products obtained by JAXA's space science missions in astrophysics (X-rays, radio, infrared), solar physics, solar-terrestrial physics, and lunar and planetary science. In addition, we archive related space science data products obtained by other domestic or foreign institutes, and provide data services to facilitate use of these data.
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The purpose of the JKU Repository is to record and archive the academic and scientific output of all scholars at Jan Kochanowski University, as well as making the data available, thus ensuring unrestricted access to knowledge and maintaining the principle of transparency.
The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.
The primary focus of the Upper Ocean Processes Group is the study of physical processes in the upper ocean and at the air-sea interface using moored surface buoys equipped with meteorological and oceanographic sensors. UOP Project Map The Upper Ocean Processes Group provides technical support to upper ocean and air-sea interface science programs. Deep-ocean and shallow-water moored surface buoy arrays are designed, fabricated, instrumented, tested, and deployed at sea for periods of up to one year
Teesside University Research Data Repository links to the University's Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to be open access. https://researchdata.tees.ac.uk/about.
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.
The PRISM Climate Group gathers climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns. The resulting datasets incorporate a variety of modeling techniques and are available at multiple spatial/temporal resolutions, covering the period from 1895 to the present. Whenever possible, we offer these datasets to the public, either free of charge or for a fee (depending on dataset size/complexity and funding available for the activity).
Content type(s)
Results from time-series analysis of Landsat images in characterizing global forest extent and change from 2000 through 2016.
MINDS@UW is designed to gather, distribute, and preserve digital materials related to the University of Wisconsin's research and instructional mission. Content, which is deposited directly by UW faculty and staff, may include research papers and reports, pre-prints and post-prints, datasets and other primary research materials, learning objects, theses, student projects, conference papers and presentations, and other born-digital or digitized research and instructional materials.
Content type(s)
<<<!!!<<<The repository is no longer available. <<<!!!<<< TOXNET's TRI is retired. Visit TRI at EPA: https://www.epa.gov/toxics-release-inventory-tri-program >>>!!!>>> As part of a broader NLM reorganization, most of NLM's toxicology information services have been integrated into other NLM products and services.
GENCODE is a scientific project in genome research and part of the ENCODE (ENCyclopedia Of DNA Elements) scale-up project. The GENCODE consortium was initially formed as part of the pilot phase of the ENCODE project to identify and map all protein-coding genes within the ENCODE regions (approx. 1% of Human genome). Given the initial success of the project, GENCODE now aims to build an “Encyclopedia of genes and genes variants” by identifying all gene features in the human and mouse genome using a combination of computational analysis, manual annotation, and experimental validation, and annotating all evidence-based gene features in the entire human genome at a high accuracy.
The UK Solar System Data Centre (UKSSDC) provides a STFC and NERC jointly funded central archive and data centre facility for Solar System science in the UK. The facilities include the World Data Centre for Solar-Terrestrial Physics, Chilton and the Cluster Ground-Based Data Centre. The UKSSDC supports data archives for the whole UK solar system community encompassing solar, inter-planetary, magnetospheric, ionospheric and geomagnetic science. The UKSSDC is part of RAL Space based at the STFC run Rutherford Appleton Laboratory in Oxfordshire.
The goals of the Drosophila Genome Center are to finish the sequence of the euchromatic genome of Drosophila melanogaster to high quality and to generate and maintain biological annotations of this sequence. In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community.
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mdw Repository provides researchers with a robust infrastructure for research data management and ensures accessibility of research data during and after completion of research projects, thus, providing a quality boost to contemporary and future research.
The University of Lincoln's Institutional Repository is for the permanent deposit of research outputs produced by the University. Repository content can be browsed or searched through this website or through searching the internet. Wherever possible, repository content is freely available for download and use according to our Copyright and Use Notice.
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aviDa is the RDC for audio-visual data of empirical qualitative social research at the Department of General Sociology at the Technische Universität Berlin, developed in cooperation between the Technische Universität Berlin and the University of Bayreuth. aviDa aims at opening and sharing videographic research data since 2018.
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.
DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) is an information management system that allows you to discover long-term ecosystem research sites around the globe, along with the data gathered at those sites and the people and networks associated with them. DEIMS-SDR describes a wide range of sites, providing a wealth of information, including each site’s location, ecosystems, facilities, parameters measured and research themes. It is also possible to access a growing number of datasets and data products associated with the sites. All sites and dataset records can be referenced using unique identifiers that are generated by DEIMS-SDR. It is possible to search for sites via keyword, predefined filters or a map search. By including accurate, up to date information in DEIMS, site managers benefit from greater visibility for their LTER site, LTSER platform and datasets, which can help attract funding to support site investments. The aim of DEIMS-SDR is to be the globally most comprehensive catalogue of environmental research and monitoring facilities, featuring foremost but not exclusively information about all LTER sites on the globe and providing that information to science, politics and the public in general.