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Found 201 result(s)
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
The Data Library and Archives (DLA) is part of the joint library system supported by the Marine Biological Laboratory and the Woods Hole Oceanographic Institution. The DLA holds collections of administrative records, photographs, scientists' data and papers, film and video, historical instruments, as well as books, journals and technical reports.
Neotoma is a multiproxy paleoecological database that covers the Pliocene-Quaternary, including modern microfossil samples. The database is an international collaborative effort among individuals from 19 institutions, representing multiple constituent databases. There are over 20 data-types within the Neotoma Paleoecological Database, including pollen microfossils, plant macrofossils, vertebrate fauna, diatoms, charcoal, biomarkers, ostracodes, physical sedimentology and water chemistry. Neotoma provides an underlying cyberinfrastructure that enables the development of common software tools for data ingest, discovery, display, analysis, and distribution, while giving domain scientists control over critical taxonomic and other data quality issues.
PISCO researchers collect biological, chemical, and physical data about ocean ecosystems in the nearshore portions of the California Current Large Marine Ecosystem. Data are archived and used to create summaries and graphics, in order to ensure that the data can be used and understood by a diverse audience of managers, policy makers, scientists and the general public.
The University of Waterloo Dataverse is a data repository for research outputs of our faculty, students, and staff. Files are held in a secure environment on Canadian servers. Researchers can choose to make content available to the public, to specific individuals, or to keep it private.
The EXFOR library contains an extensive compilation of experimental nuclear reaction data. Neutron reactions have been compiled systematically since the discovery of the neutron, while charged particle and photon reactions have been covered less extensively.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
LINCS Data Portal provides access to LINCS data from various sources. The program has six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.
The Astromaterials Data System (AstroMat) is a data infrastructure to store, curate, and provide access to laboratory data acquired on samples curated in the Astromaterials Collection of the Johnson Space Center. AstroMat is developed and operated at the Lamont-Doherty Earth Observatory of Columbia University and funded by NASA.
The CCHDO provides access to standard, well-described datasets from reference-quality repeat hydrography expeditions. It curates high quality full water column Conductivity-Temperature-Depth (CTD), hydrographic, carbon and tracer data from over 2,500 cruises from ~30 countries. It is the official data center for CTD and water sample profile data from the Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP), as well as for WOCE, US Hydro, and other high quality repeat hydrography lines (e.g. SOCCOM, HOT, BATS, WOCE, CARINA.)
FRED is an online database consisting of hundreds of thousands of economic data time series from scores of national, international, public, and private sources. FRED, created and maintained by the Research Department at the Federal Reserve Bank of St. Louis, goes far beyond simply providing data: It combines data with a powerful mix of tools that help the user understand, interact with, display, and disseminate the data. In essence, FRED helps users tell their data stories.
Modern signal processing and machine learning methods have exciting potential to generate new knowledge that will impact both physiological understanding and clinical care. Access to data - particularly detailed clinical data - is often a bottleneck to progress. The overarching goal of PhysioNet is to accelerate research progress by freely providing rich archives of clinical and physiological data for analysis. The PhysioNet resource has three closely interdependent components: An extensive archive ("PhysioBank"), a large and growing library of software ("PhysioToolkit"), and a collection of popular tutorials and educational materials
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.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
This hub supports the geospatial modeling, data analysis and visualization needs of the broad research and education communities through hosting of groups, datasets, tools, training materials, and educational contents.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
ScholarSphere is an institutional repository managed by Penn State University Libraries. Anyone with a Penn State Access ID can deposit materials relating to the University’s teaching, learning, and research mission to ScholarSphere. All types of scholarly materials, including publications, instructional materials, creative works, and research data are accepted. ScholarSphere supports Penn State’s commitment to open access and open science. Researchers at Penn State can use ScholarSphere to satisfy open access and data availability requirements from funding agencies and publishers.
The UCD Digital Library is a platform for exploring cultural heritage, engaging with digital scholarship, and accessing research data. The UCD Digital Library allows you to search, browse and explore a growing collection of historical materials, photographs, art, interviews, letters, and other exciting content, that have been digitised and made freely available.
The aim of CfA Library Datasets Dataverse is creating a better information system to respond to the changing needs of astronomers not only at the CfA, but worldwide as well. As part of this growing partnership with the ADS, the CfA Library is expanding its metadata and data curation services, and in the process, creating datasets that the astronomy community may find useful. The CfA Library Datasets Dataverse has been created to share these datasets with the greater community with the hope that some members may find it useful. Please remember to acknowledge the CfA Library and the ADS and cite the work using the "Data Citation" presented under each study's "Cataloging Information" section.
LONI’s Image and Data Archive (IDA) is a secure data archiving system. The IDA uses a robust infrastructure to provide researchers with a flexible and simple interface for de-identifying, searching, retrieving, converting, and disseminating their biomedical data. With thousands of investigators across the globe and more than 21 million data downloads to data, the IDA guarantees reliability with a fault-tolerant network comprising multiple switches, routers, and Internet connections to prevent system failure.
The EarthEnv project is a collaborative project of biodiversity scientists and remote sensing experts to develop near-global standardized, 1km resolution layers for monitoring and modeling biodiversity, ecosystems, and climate. The work is supported by NCEAS, NASA, NSF, and Yale University.