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Found 143 result(s)
The Materials Data Facility (MDF) is set of data services built specifically to support materials science researchers. MDF consists of two synergistic services, data publication and data discovery (in development). The production-ready data publication service offers a scalable repository where materials scientists can publish, preserve, and share research data. The repository provides a focal point for the materials community, enabling publication and discovery of materials data of all sizes.
The LINZ Data Service provides free online access to New Zealand’s most up-to-date land and seabed data. The data can be searched, browsed and downloaded. The LINZ web services can be also integrated into other applications.
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.
Country
The CSIRO National Collections and Marine Infrastructure (NCMI) Information and Data Centre has managed marine data for Australia's government research organisation for over 30 years. They have an enduring archive of marine and climate research data, and regularly publish data (including physical, chemical, bathymetric and biological data) collected on board RV Investigator as part of the Marine National Facility. Data from the MNF is freely and publicly available.
Country
Maenduar in Tupi means "to remember". The Maenduar repository, created by LARHUD is an institutional repository (IBICT) dedicated to research data in Digital Humanities and Humanities. The repository encompasses the production of LARHUD members and partners and extends to the public space as a public deposit repository. Researchers, professors, students linked to any institutions will be able to deposit their research data, understanding that Maenduar becomes, from this action, a public, national repository, dedicated to the production of knowledge in the Humanities in the face of the development of digital culture in all areas of the world. social world.
The SICAS Medical Image Repository is a freely accessible repository containing medical research data including medical images, surface models, clinical data, genomics data and statistical shape models. The data can freely be organized and shared on SMIR and made publicly accessible with a DOI. Dedicated data sets are organized as collections of anatomical regions (e.g Cochlea). The data can be filtered using a modular search and accessed on the web or through the SMIR API.
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The TERN Data Discovery Portal (TDDP) is a gateway to search and access all the datasets published by the Australian Terrestrial Ecosystem Research Network. In the TERN data discovery portal, users can conduct textual and graphical searches on the metadata catalogue using a web interface with temporal, spatial, and eco science related controlled vocabulary keywords. Requests to download data discovered through different data services associated with TERN. Downloading, using and sharing data will be subjected to the TERN data licensing framework (https://www.tern.org.au/datalicence/).
XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization. NOTICE: Central XNAT will be decommissioned on October 15, 2023. New project creation is no longer permitted.
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EaSy Data (for Earth System Data) is the French data repository for the environmental domain. It allows researchers in the Environmental and Earth sciences to publish their data and obtain a DOI. Submissions must comply with the scope defined by the communities. Data are moderated by community scientists before validation. Metadata are based on community standards (ISO 19115) and are exposed via standard API (CSW and OGC API)
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.
The Cornell Center for Social Sciences (CCSS) houses an extensive collection of research data files in the social sciences with particular emphasis on data that matches the interests of Cornell University researchers. CCSS intentionally uses a broad definition of social sciences in recognition of the interdisciplinary nature of Cornell research. CCSS collects and maintains digital research data files in the social sciences, with a current emphasis on Cornell-based social science research, Results Reproduction packages, and potentially at-risk datasets. Our archive historically has focused on a broad range of social science data, including data on demography, economics and labor, political and social behavior, family life, and health. You can search our holdings or browse studies by subject area.
TreeBASE is a repository of phylogenetic information, specifically user-submitted phylogenetic trees and the data used to generate them. TreeBASE accepts all types of phylogenetic data (e.g., trees of species, trees of populations, trees of genes) representing all biotic taxa. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, book, conference proceedings, or thesis. Data used in publications that are in preparation or in review can be submitted to TreeBASE but are only available to the authors, publication editors, or reviewers using a special access code.
The SuiteSparse Matrix Collection is a large and actively growing set of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.
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The geophysical database, GERDA, is a strong tool for data storage, handling and QC. Data are uploaded to and downloaded from the GERDA database through this website. GERDA is the Danish national database on shallow geophysical data. Since its establishment in 1998-2000, the database has been continuously developed. The database is hosted by the Geological Survey of Denmark and Greenland (GEUS).
Launched in December 2013, Gaia is destined to create the most accurate map yet of the Milky Way. By making accurate measurements of the positions and motions of stars in the Milky Way, it will answer questions about the origin and evolution of our home galaxy. The first data release (2016) contains three-dimensional positions and two-dimensional motions of a subset of two million stars. The second data release (2018) increases that number to over 1.6 Billion. Gaia’s measurements are as precise as planned, paving the way to a better understanding of our galaxy and its neighborhood. The AIP hosts the Gaia data as one of the external data centers along with the main Gaia archive maintained by ESAC and provides access to the Gaia data releases as part of Gaia Data Processing and Analysis Consortium (DPAC).
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. PRIDE encourages and welcomes direct user submissions of mass spectrometry data to be published in peer-reviewed publications.