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Found 58 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.
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 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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idUS is the digital archive that gives access to full text of the scientific production of the University of Seville and their datasets. Its objective is to gather, preserve and disseminate the documents and data resulting from the scientific activity of the University, making the documents visible, accessible, recoverable, usable and preservable for any user.
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It's a multidisciplinary repository that collect and diseminate research, academic, institutional and learning results from Universitat Jaume I. It also includes digitised documentary material on the province of Castelló and other information resources from different institutions, like Spain-European Union Digital Archive (SEDAS).
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The edoc-Server, start 1998, is the Institutional Repository of the Humboldt-Universität zu Berlin and offers the posibility of text- and data-publications. Every item is published for Open-Access with an optional embargo period of up to five years. Data publications since 01.01.2018.
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
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.
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PANGAEA - Data Publisher for Earth & Environmental Sciences has an almost 30-year history as an open-access library for archiving, publishing, and disseminating georeferenced data from the Earth, environmental, and biodiversity sciences. Originally evolving from a database for sediment cores, it is operated as a joint facility of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) and the Center for Marine Environmental Sciences (MARUM) at the University of Bremen. PANGAEA holds a mandate from the World Meteorological Organization (WMO) and is accredited as a World Radiation Monitoring Center (WRMC). It was further accredited as a World Data Center by the International Council for Science (ICS) in 2001 and has been certified with the Core Trust Seal since 2019. The successful cooperation between PANGAEA and the publishing industry along with the correspondent technical implementation enables the cross-referencing of scientific publications and datasets archived as supplements to these publications. PANGAEA is the recommended data repository of numerous international scientific journals.
ModelDB is a curated database of published models in the broad domain of computational neuroscience. It addresses the need for access to such models in order to evaluate their validity and extend their use. It can handle computational models expressed in any textual form, including procedural or declarative languages (e.g. C++, XML dialects) and source code written for any simulation environment. The model source code doesn't even have to reside inside ModelDB; it just has to be available from some publicly accessible online repository or WWW site.
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Open At LaTrobe (OPAL) is La Trobe University’s official repository for Open Access materials generated by academic and professional staff and HDR students. These include publications and other research outputs, theses, open data, and educational resources. OPAL enables the storage, sharing, and selective publication of files and the assignment of a persistent DOI. Users maintain control over who can see their private files and all uploads are stored in La Trobe University approved storage. Access is via La Trobe University login credentials. La Trobe produces a wide range of useful datasets including supplementary data associated with publications and stand-alone datasets and collections.
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 Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, genetic information and health care expenditures.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
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The Biodiversity Information System of Ecuador, SiB-Ec, is a technological tool that will become the core of the national information exchange network that promotes and facilitates interoperability, standardisation and implementation of guidelines for the management of data and information on biodiversity, through the National Catalogue of Biological Objects (CNOB), so that this information is available with different levels of access, and is used for the benefit of conservation, sustainable use of biodiversity, decision making and generation of public policy. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. Within SIB-Ec there is an IPT (The Integrated Publishing Toolkit) which is connected to GBIF for the exchange of biodiversity data in this network.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
MINDS@UW is designed to gather, distribute, and preserve digital materials related to the University of Wisconsin's research and instructional mission. Content, which is deposited directly by UW faculty and staff, may include research papers and reports, pre-prints and post-prints, datasets and other primary research materials, learning objects, theses, student projects, conference papers and presentations, and other born-digital or digitized research and instructional materials.
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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The Scientific Database of the Federal University of Paraná aims to gather the scientific data used in the researches that were published by the UFPR community in theses, dissertations, journal articles, and other bibliographic materials. BDC joins RDI / UFPR as an innovative service that tracks the worldwide trend in research planning, management, production, organization, storage, dissemination and reuse. The availability of research data contributes to the transparency and optimization of scientific production through the reuse of data sets and the possibility of new analyzes and approaches
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.