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Found 42 result(s)
SCEC's mission includes gathering data on earthquakes, both in Southern California and other locales; integrate the information into a comprehensive understanding of earthquake phenomena; and communicate useful knowledge for reducing earthquake risk to society at large. The SCEC community consists of more than 600 scientists from 16 core institutions and 47 additional participating institutions. SCEC is funded by the National Science Foundation and the U.S. Geological Survey.
LEPR is a database of results of published experimental studies involving liquid-solid phase equilibria relevant to natural magmatic systems. TraceDs is a database of experimental studies involving trace element distribution between liquid, solid and fluid phases.
The Eurac Research CLARIN Centre (ERCC) is a dedicated repository for language data. It is hosted by the Institute for Applied Linguistics (IAL) at Eurac Research, a private research centre based in Bolzano, South Tyrol. The Centre is part of the Europe-wide CLARIN infrastructure, which means that it follows well-defined international standards for (meta)data and procedures and is well-embedded in the wider European Linguistics infrastructure. The repository hosts data collected at the IAL, but is also open for data deposits from external collaborators.
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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.
Bitbucket is a web-based version control repository hosting service owned by Atlassian, for source code and development projects that use either Mercurial or Git revision control systems.
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.
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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.
nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.
The Spiral Digital Repository is the Imperial College London institutional open access repository. This system allows you, as an author, to make your research documents open access without incurring additional publication costs. When you self-archive a research document in Spiral it becomes free for anyone to read. You can upload copies of your publications to Spiral using Symplectic Elements. All deposited content becomes searchable online.
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.
This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.
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
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The Canadian Open Genetics Repository is a collaborative effort for the collection, storage, sharing and robust analysis of variants reported by medical diagnostics laboratories across Canada. As clinical laboratories adopt modern genomics technologies, the need for this type of collaborative framework is increasingly important. If you want to join COGR project and get data please send an email at cogr@opengenetics.ca and the introduction to the project will be arranged.
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MathRepo is a repository of the Max Planck Institute for Mathematics in the Sciences in Leipzig, dedicated to mathematical research data. Research data are all digital objects that arise during the process of doing research or are a result thereof. In particular, the purpose of this repository is to collect scripts and code, to explain applications of mathematical software, to showcase additional examples to paper publications, and more generally to host supplementary material developed for research projects or discussed in workshops.
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.
The EUR Data Repository [EDR] is the institutional data repository from the Erasmus University Rotterdam. The EUR Data Repository is an online platform where you showcase your research and make it findable, citable, and reusable for others.
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.
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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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In order to control access to the experimental data obtained at the ILL in a coherent and secure fashion, the ILL has recently developed a single portal for consulting, downloading and managing your data. Here “data” is understood to mean raw data (i.e. numor files), processed data, and meta-data (e.g. log files or “logs”).
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 CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
The main goal of the ECCAD project is to provide scientific and policy users with datasets of surface emissions of atmospheric compounds, and ancillary data, i.e. data required to estimate or quantify surface emissions. The supply of ancillary data - such as maps of population density, maps of fires spots, burnt areas, land cover - could help improve and encourage the development of new emissions datasets. ECCAD offers: Access to global and regional emission inventories and ancillary data, in a standardized format Quick visualization of emission and ancillary data Rationalization of the use of input data in algorithms or emission models Analysis and comparison of emissions datasets and ancillary data Tools for the evaluation of emissions and ancillary data ECCAD is a dynamical and interactive database, providing the most up to date datasets including data used within ongoing projects. Users are welcome to add their own datasets, or have their regional masks included in order to use ECCAD tools.