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Found 20 result(s)
WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
Vivli is a non-profit organization working to advance human health through the insights and discoveries gained by sharing and analyzing data. It is home to an independent global data-sharing and analytics platform which serves all elements of the international research community. The platform includes a data repository, in-depth search engine and cloud-based analytics, and harmonizes governance, policy and processes to make sharing data easier. Vivli acts as a neutral broker between data contributor and data user and the wider data sharing community.
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 AstrofĂ­sica 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 fĂĽr Astrophysik Potsdam (AIP), Max-Planck-Institut fĂĽr Astrophysik (MPA Garching), Max-Planck-Institut fĂĽr Extraterrestrische Physik (MPE), Max-Planck-Institut fĂĽr 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 AutĂłnoma de MĂ©xico, 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.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
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.
Insect Images is part of the Center for Invasive Species and Ecosystem Health’s BugwoodImages. It provides an easily accessible archive of high quality images for use in educational applications. The focus of InsectImages is images related to entomology. Insect Images hosts Archives from the Ohio State University (OARDC), Southern Forest Insect Work Conference (SFIWC), Florida Department of Agriculture & Consumer Services, United States National Collection of Scale Insects Photographs (ScaleNet), Mactode Publications, The University of Georgia Museum of Natural History, the United States Geological Surveys Nonindigenous Aquatic Speies (NAS)and the collaborative survey 'Viruses in Imported and Domestically Produced Ornamentals'. In most cases, the images found in this system were taken by and loaned to us by photographers other than ourselves. Most are in the realm of public sector images. The photographs are in this system to be used
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.
The THREDDS Data Server (TDS) is a web server that provides metadata and data access for scientific datasets, using OPeNDAP, OGC WMS and WCS, HTTP, and other remote data access protocols. Unidata is a diverse community of over 250 institutions vested in the common goal of sharing data, and tools to access and visualize that data. For more than 25 years Unidata has been providing data, tools, and support to enhance earth-system education and research. In an era of increasing data complexity, accessibility, and multidisciplinary integration, Unidata provides a rich set of services and tools.
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.
Databrary is a data library for researchers to share research data and analytical tools with other investigators. It is a web-based repository for open sharing and preservation of video data and associated metadata in the area of behavioral sciences. The project aims to increase the openness in scientific research and dedicated to transforming the culture of science through building a community of researchers empowering them with an unprecedented set of tools for discovery. Databrary is complemented by Datavyu (an open source video-coding software).
The Artstor Digital Library is a nonprofit resource that provides more than one million digital images in the arts, architecture, humanities, and sciences with an accessible suite of software tools for teaching and research. Its community-built collections comprise contributions from outstanding international museums, photographers, libraries, scholars, photo archives, and artists and artists' estates.
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/
SimTK is a free project-hosting platform for the biomedical computation community that enables researchers to easily share their software, data, and models and provides the infrastructure so they can support and grow a community around their projects. It has over 126.656 members, hosts 1.648 projects from researchers around the world, and has had more than 2.095.783 files downloaded from it. Individuals have created SimTK projects to meet publisher and funding agencies’ software and data sharing requirements, run scientific challenges, create a collection of their community’s resources, and much more.