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Found 156 result(s)
The Chesapeake Bay Environmental Observatory (CBEO) is a prototype to demonstrate the utility of newly developed Cyberinfrastructure (CI) components for transforming environmental research, education, and management. The CBEO project uses a specific problem of water quality (hypoxia) as means of directly involving users and demonstrating the prototype’s utility. Data from the Test Bed are being brought into a CBEO Portal on a National Geoinformatics Grid developed by the NSF funded GEON. This is a cyberinfrastructure netwrok that allows users access to datasets as well as the tools with which to analyze the data. Currently, Test Bed data avaialble on the CBEO Portal includes Water Quality Model output and water quality monitorig data from the Chesapeake Bay Program's CIMS database. This data is also available as aggregated "data cubes". Avaialble tools include the Data Access System for Hydrology (DASH), Hydroseek and an online R-based interpolator.
---<<< This repository is no longer available. This record is out-dated >>>--- The ONS challenge contains open solubility data, experiments with raw data from different scientists and institutions. It is part of the The Open Notebook Science wiki community, ideally suited for community-wide collaborative research projects involving mathematical modeling and computer simulation work, as it allows researchers to document model development in a step-by-step fashion, then link model prediction to experiments that test the model, and in turn, use feeback from experiments to evolve the model. By making our laboratory notebooks public, the evolutionary process of a model can be followed in its totality by the interested reader. Researchers from laboratories around the world can now follow the progress of our research day-to-day, borrow models at various stages of development, comment or advice on model developments, discuss experiments, ask questions, provide feedback, or otherwise contribute to the progress of science in any manner possible.
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
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Silkworm Pathogen Database (SilkPathDB) is a comprehensive resource for studying on pathogens of silkworm, including microsporidia, fungi, bacteria and virus. SilkPathDB provides access to not only genomic data including functional annotation of genes and gene products, but also extensive biological information for gene expression data and corresponding researches. SilkPathDB will be help with researches on pathogens of silkworm as well as other Lepidoptera insects.
The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.
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>>> !!! the repository is offline !!! The current successor is https://www.lovd.nl/USH1C. <<< The database contains all the variants published as pathogenic mutations in the international literature up to November 2007. In addition, unpublished Usher mutations and non-pathogenic variants from the laboratory of Montpellier have been included.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
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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.
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.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
Museum explorers travel to ocean depths, the peaks of the Andes, Africa's Rift Valley, the rainforests of South America, and the deserts of Central Asia. Perhaps even to a field site or research institution in your own state, territory or country. In each area, researchers collect specimens: fossils, minerals, and rocks, plants and animals, tools and artworks. Collections care professionals have meticulously preserved, labeled, cataloged, and organized items of this kind for more than 150 years. Taken together, the NMNH collections form the largest, most comprehensive natural history collection in the world. By comparing items gathered in different eras and regions, scientists learn how our world has varied across time and space.
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.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
State of the Salmon provides data on abundance, diversity, and ecosystem health of wild salmon populations specific to the Pacific Ocean, North Western North America, and Asia. Data downloads are available using two geographic frameworks: Salmon Ecoregions or Hydro 1K.
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The Human Genetic Variation Database (HGVD) aims to provide a central resource to archive and display Japanese genetic variation and association between the variation and transcription level of genes. The database currently contains genetic variations determined by exome sequencing of 1,208 individuals and genotyping data of common variations obtained from a cohort of 3,248 individuals.
Climate Data Record (CDR) is a time series of measurements of sufficient length, consistency and continuity to determine climate variability and change. The fundamental CDRs include sensor data, such as calibrated radiances and brightness temperatures, that scientists have improved and quality-controlled along with the data used to calibrate them. The thematic CDRs include geophysical variables derived from the fundamental CDRs, such as sea surface temperature and sea ice concentration, and they are specific to various disciplines.
The GOES Space Environment Monitor archive is an important component of the National Space Weather Program --a interagency program to provide timely and reliable space environment observations and forecasts. GOES satellites carry onboard a Space Environment Monitor subsystem that measures X-rays, Energetic Particles and Magnetic Field at the Spacecraft.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
Lithuania became a full member of CLARIN ERIC in January of 2015 and soon CLARIN-LT consortium was founded by three partner universities: Vytautas Magnus University, Kaunas Technology University and Vilnius University. The main goal of the consortium is to become a CLARIN B centre, which will be able to serve language users in Lithuania and Europe for storing and accessing language resources.
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The Canadian Astronomy Data Centre (CADC) was established in 1986 by the National Research Council of Canada (NRC), through a grant provided by the Canadian Space Agency (CSA). Over the past 30 years the CADC has evolved from an archiving centre---hosting data from Hubble Space Telescope, Canada-France-Hawaii Telescope, the Gemini observatories, and the James Clerk Maxwell Telescope---into a Science Platform for data-intensive astronomy. The CADC, in partnership with Shared Services Canada, Compute Canada, CANARIE and the university community (funded through the Canadian Foundation for Innovation), offers cloud computing, user-managed storage, group management, and data publication services, in addition to its ongoing mission to provide permanent storage for major data collections. Located at NRC Herzberg Astronomy and Astrophysics Research Centre in Victoria, BC, the CADC staff consists of professional astronomers, software developers, and operations staff who work with the community to develop and deliver leading-edge services to advance Canadian research. The CADC plays a leading role in international efforts to improve the scientific/technical landscape that supports data intensive science. This includes leadership roles in the International Virtual Observatory Alliance and participation in organizations like the Research Data Alliance, CODATA, and the World Data Systems. CADC also contributes significantly to future Canadian projects like the Square Kilometre Array and TMT. In 2019, the Canadian Astronomy Data Centre (CADC) delivered over 2 Petabytes of data (over 200 million individual files) to thousands of astronomers in Canada and in over 80 other countries. The cloud processing system completed over 6 million jobs (over 1100 core years) in 2019.
<<<!!!<<< This repository is no longer available. The Environmental Dataset Gateway (EDG) has provided access to EPA's Open Data resources. Metadata records contributed by EPA Regions, Program Offices, and Research Laboratories that link to geospatial and non-geospatial resources (e.g., data, Web services, or applications) are now discoverable through Data.gov. https://www.re3data.org/repository/r3d100010078 >>>!!!>>>
Open Power System Data is a free-of-charge data platform dedicated to electricity system researchers. We collect, check, process, document, and publish data that are publicly available but currently inconvenient to use. The project is a service provider to the modeling community: a supplier of a public good. Learn more about its background or just go ahead and explore the data platform.