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Found 360 result(s)
As a department of the United States Department of Agriculture (USDA) the National Agricultural Statistics Service (NASS) continually surveys and reports on U.S. agriculture. NASS reports include production and supplies of food and fiber, prices paid and received by farmers, farm labor and wages, farm finances, chemical use, and changes in the demographics of U.S. producers. NASS provides objective and unbiased statistics of states and counties, while safeguarding the privacy of farmers and ranchers.
Chempound is a new generation repository architecture based on RDF, semantic dictionaries and linked data. It has been developed to hold any type of chemical object expressible in CML and is exemplified by crystallographic experiments and computational chemistry calculations. In both examples, the repository can hold >50k entries which can be searched by SPARQL endpoints and pre-indexing of key fields. The Chempound architecture is general and adaptable to other fields of data-rich science. The Chempound software is hosted at http://bitbucket.org/chempound and is available under the Apache License, Version 2.0
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
The GHDx is our user-friendly and searchable data catalog for global health, demographic, and other health-related datasets. It provides detailed information about datasets ranging from censuses and surveys to health records and vital statistics, globally. It also serves as a platform for data owners to share their data with the public. The GDB Compare visualization, which allows the user to see rate of change in disease incidence, globally or by country, by age or across all ages, is especially powerful as a tool. Be sure to try adding a bottom chart, like the map, to augment the treemap that loads by default in the top chart.
>>>!!!<<< The repository is no longer available. >>>!!!<<< The eagle-i National Network and eagle-i resource search at www.eagle-.net was retired on November 4, 2021.!!! Groundbreaking biomedical research requires access to cutting edge scientific resources; however such resources are often invisible beyond the laboratories or universities where they were developed. eagle-i is a discovery platform that helps biomedical scientists find previously invisible, but highly valuable, resources.
The Northern California Earthquake Data Center (NCEDC) is a permanent archive and distribution center primarily for multiple types of digital data relating to earthquakes in central and northern California. The NCEDC is located at the Berkeley Seismological Laboratory, and has been accessible to users via the Internet since mid-1992. The NCEDC was formed as a joint project of the Berkeley Seismological Laboratory (BSL) and the U.S. Geological Survey (USGS) at Menlo Park in 1991, and current USGS funding is provided under a cooperative agreement for seismic network operations.
The centerpiece of the Global Trade Analysis Project is a global data base describing bilateral trade patterns, production, consumption and intermediate use of commodities and services. The GTAP Data Base consists of bilateral trade, transport, and protection matrices that link individual country/regional economic data bases. The regional data bases are derived from individual country input-output tables, from varying years.
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.
>>>!!!<<< The repository is no longer available. >>>!!!<<< Here you will find a collection of atomic microstructures that have been built by the atomic modeling community. Feel free to download any of these and use them in your own scientific explorations.The focus of this cyberinfrastructure is to advance the field of atomic-scale modeling of materials by acting as a forum for disseminating new atomistic scale methodologies, educating non-experts and the next generation of computational materials scientists, and serving as a bridge between the atomistic and complementary (electronic structure, mesoscale) modeling communities.
The OpenMadrigal project seeks to develop and support an on-line database for geospace data. The project has been led by MIT Haystack Observatory since 1980, but now has active support from Jicamarca Observatory and other community members. Madrigal is a robust, World Wide Web based system capable of managing and serving archival and real-time data, in a variety of formats, from a wide range of ground-based instruments. Madrigal is installed at a number of sites around the world. Data at each Madrigal site is locally controlled and can be updated at any time, but shared metadata between Madrigal sites allow searching of all Madrigal sites at once from any Madrigal site. Data is local; metadata is shared.
Water DAMS (Water Data Analysis and Management System) provides access to foundational water treatment technology data that enable researchers and decision-makers to identify and quantify opportunities for technology innovations to reduce the cost and energy intensity of desalination. It is the submission point for all data generated by research conducted by the National Alliance for Water Innovation (NAWI) and is designed to be used by the broader water research community. With publicly accessible contributions from a variety of academic and industrial partners, Water DAMS seeks to enable data discoverability, improve accessibility, and accelerate collaboration that contributes to pipe parity and innovation in water treatment technologies.
The NREL Data Catalog is where descriptive information (i.e., metadata) is maintained about public data resulting from federally funded research conducted by the National Renewable Energy Laboratory (NREL) researchers and analysts. Our Goal: Making Federally Funded Data Publicly Available NREL's mission is to develop clean energy and energy efficiency technologies and practices, advance related science and engineering, and provide knowledge and innovations to integrate energy systems at all scales. The NREL Data Catalog helps accomplish this by ensuring the data behind the science and engineering are well-documented and useful to the scientific community at large.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
OBIS strives to document the ocean's diversity, distribution and abundance of life. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States. Operated by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, HMCA preserves and disseminates data collected by selected research projects funded by the Foundation and facilitates secondary analyses of the data. Our goal is to increase understanding of health and health care in the United States through secondary analysis of RWJF-supported data collections
SeaBASS, the publicly shared archive of in situ oceanographic and atmospheric data maintained by the NASA Ocean Biology Processing Group (OBPG). High quality in situ measurements are prerequisite for satellite data product validation, algorithm development, and many climate-related inquiries. As such, the NASA Ocean Biology Processing Group (OBPG) maintains a local repository of in situ oceanographic and atmospheric data to support their regular scientific analyses. The SeaWiFS Project originally developed this system, SeaBASS, to catalog radiometric and phytoplankton pigment data used their calibration and validation activities. To facilitate the assembly of a global data set, SeaBASS was expanded with oceanographic and atmospheric data collected by participants in the SIMBIOS Program, under NASA Research Announcements NRA-96 and NRA-99, which has aided considerably in minimizing spatial bias and maximizing data acquisition rates. Archived data include measurements of apparent and inherent optical properties, phytoplankton pigment concentrations, and other related oceanographic and atmospheric data, such as water temperature, salinity, stimulated fluorescence, and aerosol optical thickness. Data are collected using a number of different instrument packages, such as profilers, buoys, and hand-held instruments, and manufacturers on a variety of platforms, including ships and moorings.
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. OMIM is authored and edited at the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, under the direction of Dr. Ada Hamosh. Its official home is omim.org.
The Digital Archaeological Record (tDAR) is an international digital repository for the digital records of archaeological investigations. tDAR’s use, development, and maintenance are governed by Digital Antiquity, an organization dedicated to ensuring the long-term preservation of irreplaceable archaeological data and to broadening the access to these data.
The World Ocean Database (WOD) is a collection of scientifically quality-controlled ocean profile and plankton data that includes measurements of temperature, salinity, oxygen, phosphate, nitrate, silicate, chlorophyll, alkalinity, pH, pCO2, TCO2, Tritium, Δ13Carbon, Δ14Carbon, Δ18Oxygen, Freon, Helium, Δ3Helium, Neon, and plankton. WOD contains all data of "World Data Service Oceanography" (WDS-Oceanography).
The World Ocean Atlas (WOA) contains objectively analyzed climatological fields of in situ temperature, salinity, oxygen, and other measured variables at standard depth levels for various compositing periods for the world ocean. Regional climatologies were created from the Atlas, providing a set of high resolution mean fields for temperature and salinity. A new version of the WOA is released in conjunction with each major update to the WOD, the largest collection of publicly available, uniformly formatted, quality controlled subsurface ocean profile data in the world.
NED is a comprehensive database of multiwavelength data for extragalactic objects, providing a systematic, ongoing fusion of information integrated from hundreds of large sky surveys and tens of thousands of research publications. The contents and services span the entire observed spectrum from gamma rays through radio frequencies. As new observations are published, they are cross- identified or statistically associated with previous data and integrated into a unified database to simplify queries and retrieval. Seamless connectivity is also provided to data in NASA astrophysics mission archives (IRSA, HEASARC, MAST), to the astrophysics literature via ADS, and to other data centers around the world.
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. SNAP is also available through the NodeXL which is a graphical front-end that integrates network analysis into Microsoft Office and Excel. The SNAP library is being actively developed since 2004 and is organically growing as a result of our research pursuits in analysis of large social and information networks. Largest network we analyzed so far using the library was the Microsoft Instant Messenger network from 2006 with 240 million nodes and 1.3 billion edges. The datasets available on the website were mostly collected (scraped) for the purposes of our research. The website was launched in July 2009.
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
A community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Spinal Cord Injury research through sharing of data from basic and clinical research.