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Found 107 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.
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.
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.
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!!!This site has been decomissioned!!!! The Geographic Information Support Team (GIST) Repository at the University of Georgia is a USAID-funded global archive of spatial data collected and distributed for the greater humanitarian community. If you want to search for data, you will need a valid email address to create an account.
>>>!!!<<< 2019-01: Global Land Cover Facility goes offline see https://spatialreserves.wordpress.com/2019/01/07/global-land-cover-facility-goes-offline/ ; no more access to http://www.landcover.org >>>!!!<<< The Global Land Cover Facility (GLCF) provides earth science data and products to help everyone to better understand global environmental systems. In particular, the GLCF develops and distributes remotely sensed satellite data and products that explain land cover from the local to global scales.
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.
COViMS (COVID-19 Infections in MS & Related Diseases) is a joint effort of the National MS Society, Consortium of MS Centers and Multiple Sclerosis Society of Canada to capture information on outcomes of people with MS and other CNS demyelinating diseases (Neuromyelitis Optica, or MOG antibody disease) who have developed COVID-19.
The Objectively Analyzed air-sea Fluxes (OAFlux) project is a research and development project focusing on global air-sea heat, moisture, and momentum fluxes. The project is committed to produce high-quality, long-term, global ocean surface forcing datasets from the late 1950s to the present to serve the needs of the ocean and climate communities on the characterization, attribution, modeling, and understanding of variability and long-term change in the atmosphere and the oceans.
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.
AmoebaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for Entamoeba and Acanthamoeba parasites. In its first iteration (released in early 2010), AmoebaDB contains the genomes of three Entamoeba species (see below). AmoebaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers . The database includes supplemental bioinformatics analyses and a web interface for data-mining.
The Netlib repository contains freely available software, documents, and databases of interest to the numerical, scientific computing, and other communities.
RAVE (RAdial Velocity Experiment) is a multi-fiber spectroscopic astronomical survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Leibniz-Institut für Astrophysik Potsdam. As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE's primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE's vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.
The NOAA Repository is a digital library of scientific literature and research produced by the National Oceanic and Atmospheric Administration. The repository contains NOAA publications, as defined in the NOAA Publications Policy, dating from NOAA’s formation in 1970 to present and NOAA-authored and -funded journal articles from 2015 forward.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
Archiving data and housing geological collections is an important role the Bureau of Geology plays in improving our understanding of the geology of New Mexico. Aside from our numerous publications, several datasets are available to the public. Data in this repository supplements published papers in our publications. Please refer to both the published material and the repository documentation before using this data. Please cite repository data as shown in each repository listing.
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.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
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).
The Wolfram Data Repository is a public resource that hosts an expanding collection of computable datasets, curated and structured to be suitable for immediate use in computation, visualization, analysis and more. Building on the Wolfram Data Framework and the Wolfram Language, the Wolfram Data Repository provides a uniform system for storing data and making it immediately computable and useful. With datasets of many types and from many sources, the Wolfram Data Repository is built to be a global resource for public data and data-backed publication.
<<<!!!<<< 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 >>>!!!>>>
ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. ClinVar thus facilitates access to and communication about the relationships asserted between human variation and observed health status, and the history of that interpretation. ClinVar processes submissions reporting variants found in patient samples, assertions made regarding their clinical significance, information about the submitter, and other supporting data. The alleles described in submissions are mapped to reference sequences, and reported according to the HGVS standard. ClinVar then presents the data for interactive users as well as those wishing to use ClinVar in daily workflows and other local applications. ClinVar works in collaboration with interested organizations to meet the needs of the medical genetics community as efficiently and effectively as possible
Data Basin is a science-based mapping and analysis platform that supports learning, research, and sustainable environmental stewardship.