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Found 24 result(s)
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
B2FIND is a discovery service based on metadata steadily harvested from research data collections from EUDAT data centres and other repositories. The service offers faceted browsing and it allows in particular to discover data that is stored through the B2SAFE and B2SHARE services. The B2FIND service includes metadata that is harvested from many different community repositories.
The Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
Country
The purpose of the Canadian Urban Data Repository (CUDR) is to provide a “home” for urban datasets. While primarily focused on datasets created by academe, it will also contain datasets created by NGOs, governments, citizens, and industry. Datasets stored in the repository will be open-access and will not contain personally identifiable information. The purpose of the Canadian Urban Data Catalogue (CUDC) is to enhance the awareness of urban datasets that exist across Canada by providing a catalogue of Canadian and Canadian-created urban datasets. It will catalogue datasets available in CUDR and external datasets available on other platforms and as web services. These external datasets may be open or closed. CUDC uses a rich metadata model that supports the documentation and search for datasets relevant to a user’s needs. Catalogue entry metadata may be exported and imported from/to CUDC.
The Conserved Domain Database is a resource for the annotation of functional units in proteins. Its collection of domain models includes a set curated by NCBI, which utilizes 3D structure to provide insights into sequence/structure/function relationships
The NCBI Short Genetic Variations database, commonly known as dbSNP, catalogs short variations in nucleotide sequences from a wide range of organisms. These variations include single nucleotide variations, short nucleotide insertions and deletions, short tandem repeats and microsatellites. Short Genetic Variations may be common, thus representing true polymorphisms, or they may be rare. Some rare human entries have additional information associated withthem, including disease associations, genotype information and allele origin, as some variations are somatic rather than germline events. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017***
Country
depositar — taking the term from the Portuguese/Spanish verb for to deposit — is an online repository for research data. The site is built by the researchers for the researchers. You are free to deposit, discover, and reuse datasets on depositar for all your research purposes.
EBAS is a database hosting observation data of atmospheric chemical composition and physical properties. EBAS hosts data submitted by data originators in support of a number of national and international programs ranging from monitoring activities to research projects. EBAS is developed and operated by the Norwegian Institute for Air Research (NILU). We hope the information found on the web-site is self explanatory, and we would particularly ask you to consider the text found in the data disclaimer and in the “info” pages associated to the filter criteria.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
IATI is a voluntary, multi-stakeholder initiative that seeks to improve the transparency of aid, development, and humanitarian resources in order to increase their effectiveness in tackling poverty. IATI brings together donor and recipient countries, civil society organisations, and other experts in aid information who are committed to working together to increase the transparency and openness of aid. - See more at: https://iatistandard.org/en/about/#sthash.BYPZ6NPt.dpuf
Here you will find authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world.
LinkedEarth is an EarthCube-funded project aiming to better organize and share Earth Science data, especially paleoclimate data. LinkedEarth facilitates the work of scientists by empowering them to curate their own data and to build new tools centered around those.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
NCEP delivers national and global weather, water, climate and space weather guidance, forecasts, warnings and analyses to its Partners and External User Communities. The National Centers for Environmental Prediction (NCEP), an arm of the NOAA's National Weather Service (NWS), is comprised of nine distinct Centers, and the Office of the Director, which provide a wide variety of national and international weather guidance products to National Weather Service field offices, government agencies, emergency managers, private sector meteorologists, and meteorological organizations and societies throughout the world. NCEP is a critical national resource in national and global weather prediction. NCEP is the starting point for nearly all weather forecasts in the United States. The Centers are: Aviation Weather Center (AWC), Climate Prediction Center (CPC), Environmental Modeling Center (EMC), NCEP Central Operations (NCO), National Hurricane Center (NHC), Ocean Prediction Center (OPC), Storm Prediction Center (SPC), Space Weather Prediction Center (SWPC), Weather Prediction Center (WPC)
TPA is a database that contains sequences built from the existing primary sequence data in GenBank. TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.
<<<!!!<<< The demand for high-value environmental data and information has dramatically increased in recent years. To improve our ability to meet that demand, NOAA’s former three data centers—the National Climatic Data Center, the National Geophysical Data Center, and the National Oceanographic Data Center, which includes the National Coastal Data Development Center—have merged into the National Centers for Environmental Information (NCEI). >>>!!!>>> The National Oceanographic Data Center includes the National Coastal Data Development Center (NCDDC) and the NOAA Central Library, which are integrated to provide access to the world's most comprehensive sources of marine environmental data and information. NODC maintains and updates a national ocean archive with environmental data acquired from domestic and foreign activities and produces products and research from these data which help monitor global environmental changes. These data include physical, biological and chemical measurements derived from in situ oceanographic observations, satellite remote sensing of the oceans, and ocean model simulations.
OpenKIM is an online suite of open source tools for molecular simulation of materials. These tools help to make molecular simulation more accessible and more reliable. Within OpenKIM, you will find an online resource for standardized testing and long-term warehousing of interatomic models and data, and an application programming interface (API) standard for coupling atomistic simulation codes and interatomic potential subroutines.
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.
TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.
<<<!!!<<< USHIK was archived because some of the metadata are maintained by other sites and there is no need for duplication. The USHIK metadata registry was a neutral repository of metadata from an authoritative source used to promote interoperability and reuse of data. The registry did not attempt to change the metadata content but rather provided a structured way to view data for the technical or casual user. Complete information see: https://www.ahrq.gov/data/ushik.html >>>!!!>>>
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
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.