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Found 31 result(s)
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The CosmoSim database provides results from cosmological simulations performed within different projects: the MultiDark and Bolshoi project, and the CLUES project. The CosmoSim webpage provides access to several cosmological simulations, with a separate database for each simulation. Simulations overview: https://www.cosmosim.org/cms/simulations/simulations-overview/ . CosmoSim is a contribution to the German Astrophysical Virtual Observatory.
This website is a portal that enables access to multi-Terabyte turbulence databases. The data reside on several nodes and disks on our database cluster computer and are stored in small 3D subcubes. Positions are indexed using a Z-curve for efficient access.
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Data Publication Server Forschungszentrum Juelich is a web server for providing large data sets to the general public. It's main application is publishing data belonging to scientific publications.
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.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
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Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat is the Karlsruhe Data Infrastructure for Materials Science, an open source software for managing research data. It is being developed as part of several research projects at the Institute for Applied Materials - Microstructure Modelling and Simulation (IAM-MMS) of the Karlsruhe Institute of Technology (KIT). The goal of this project is to combine the ability to manage and exchange data, the repository , with the possibility to analyze, visualize and transform said data, the electronic lab notebook (ELN). Kadi4Mat supports a close cooperation between experimenters, theorists and simulators, especially in materials science, to enable the acquisition of new knowledge and the development of novel materials. This is made possible by employing a modular and generic architecture, which allows to cover the specific needs of different scientists, each utilizing unique workflows. At the same time, this opens up the possibility of covering other research disciplines as well.
ICARUS is an open access, searchable, web-based infrastructure for storing, sharing, and utilizing atmospheric simulation chamber data. Atmospheric simulation chambers (sometimes called "smog chambers", environmental chambers, flow tubes, and continuously stirred reactors) are indispensable tools for atmospheric chemistry and physics research. The fundamental kinetic, mechanistic, or physical results from atmospheric chambers integrate into chemical transport models and inform scientific decision making. The data available in ICARUS are highly curated, uniform, and freely available to researchers, policy makers, and the general public worldwide.
<<<!!!<<< This MultiDark application is now integrated into CosmoSim (https://www.cosmosim.org/ , all data and much more is available there. The old MultiDark server is no longer available. >>>!!!>>> The MultiDark database provides results from cosmological simulations performed within the MultiDark project. This database can be queried by entering SQL statements directly into the Query Form. The access to that form and thus access to the public & private databases is password protected.
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This data archive of experiments studying the dynamics of pedestrians is build up by the Institute for Advanced Simulation 7: Civil Safety Research of Forschungszentrum Jülich. The landing page provides our own data of experiments. Data of research colleagues are listed within the data archive at https://ped.fz-juelich.de/extda For most of the experiments, the video recordings, as well as the resulting trajectories of single pedestrians, are available. The experiments were performed under laboratory conditions to focus on the influence of a single variable. You are very welcome to use our data for further research, as long as you name the source of the data. If you have further questions feel free to contact Maik Boltes.
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.
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The BonaRes Repository stores, manage and publishes soil and agricultural research data from research projects, agricultural long-term field experiments and soil profiles which contribute significantly to the analysis of changes of soil and soil functions over the long term. Research data are described by the metadata following the BonaRes Metadata Schema (DOI: 10.20387/bonares-5pgg-8yrp) which combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). Metadata includes AGROVOC keywords. Within the BonaRes Repository research data is provided for free reuse under the CC License and can be discovered by advanced text and map search via a number of criteria.
CESM is a fully-coupled, community, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states.
HepSim is a public repository with Monte Carlo simulations for particle-collision experiments. It contains predictions from leading-order (LO) parton shower models, next-to-leading order (NLO) and NLO with matched parton showers. It also includes Monte Carlo events after fast ("parametric") and full (Geant4) detector simulations and event reconstruction.
The SuiteSparse Matrix Collection is a large and actively growing set of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.
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The NOMAD Repository and Archive stands for open access of scientific materials data. It enables the confirmatory analysis of materials data, their reuse, and repurposing. All data is available in their raw format as produced by the underlying code (Repository) and in a common, machine-processable, and well-defined data format (Archive).
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B2SHARE allows publishing research data and belonging metadata. It supports different research communities with specific metadata schemas. This server is provided for researchers of the Research Centre Juelich and related communities.
The Earth System Grid Federation (ESGF) is an international collaboration with a current focus on serving the World Climate Research Programme's (WCRP) Coupled Model Intercomparison Project (CMIP) and supporting climate and environmental science in general. Data is searchable and available for download at the Federated ESGF-CoG Nodes https://esgf.llnl.gov/nodes.html
A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
KiMoSys, a web application for quantitative KInetic MOdels of biological SYStems. Kinetic models, with the aim to understand and subsequently design the metabolism of organism of interest are constructed iteratively and require accurate experimental data for both the generation and verification of hypotheses. Therefore, there is a growing requirement for exchanging experimental data and models between the systems biology community, and to automate as much as possible the kinetic model building, editing, simulation and analysis steps.
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Paris Astronomical Data Centre aims at providing VO access to its data collections, at participating to international standards developments, at implementing VO compliant simulation codes, data visualization and analysis software. This centre hosts high level permanent activities for tools and data distribution under the format of reference services. These sustainable services are recognized at the national level as CNRS labeled services. The various activities are organised as portals whose functions are to provide visibility and information on the projects and to encourage collaboration.
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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.
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The CyberCell database (CCDB) is a comprehensive collection of detailed enzymatic, biological, chemical, genetic, and molecular biological data about E. coli (strain K12, MG1655). It is intended to provide sufficient information and querying capacity for biologists and computer scientists to use computers or detailed mathematical models to simulate all or part of a bacterial cell at a nanoscopic (10-9 m), mesoscopic (10-8 m).The CyberCell database CCDB actually consists of 4 browsable databases: 1) the main CyberCell database (CCDB - containing gene and protein information), 2) the 3D structure database (CC3D – containing information for structural proteomics), 3) the RNA database (CCRD – containing tRNA and rRNA information), and 4) the metabolite database (CCMD – containing metabolite information). Each of these databases is accessible through hyperlinked buttons located at the top of the CCDB homepage. All CCDB sub-databases are fully web enabled, permitting a wide variety of interactive browsing, search and display operations. and microscopic (10-6 m) level.