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Found 11 result(s)

ETH Zürich Research Collection

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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.

melbourne.figshare.com

University of Melbourne data repository

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melbourne.figshare.com is a specialised service that has been tailored according to specific needs and requirements of the University and our community of researchers. The service offered at the University is free to use, provides 100GB of data, and stores all data on the University's storage system.

CU Scholar

University of Colorado Boulder's institutional repository

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CU Scholar is an open access institutional repository supporting the research and teaching mission of the University of Colorado Boulder. It is intended to serve as a platform for preserving the research activities of members of the CU Boulder community and for providing public access to that research. CU Scholar is maintained by the University Libraries.

National Science Digital Library

NSDL

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The National Science Digital Library provides high quality online educational resources for teaching and learning, with current emphasis on the sciences, technology, engineering, and mathematics (STEM) disciplines—both formal and informal, institutional and individual, in local, state, national, and international educational settings. The NSDL collection contains structured descriptive information (metadata) about web-based educational resources held on other sites by their providers. These providers have contribute this metadata to NSDL for organized search and open access to educational resources via this website and its services.

Network Repository

Network Data Repository, Graph Data, Social Networks

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Network Repository is the first interactive data repository for graph and network data. It hosts graph and network datasets, containing hundreds of real-world networks and benchmark datasets. Unlike other data repositories, Network Repository provides interactive analysis and visualization capabilities to allow researchers to explore, compare, and investigate graph data in real-time on the web.

SISSA Open Data

Scuola Internazionale Superiore di Studi Avanzati Open Data

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SISSA Open Data is the Sissa repository for the research data managment. It is an institutional repository that captures, stores, preserves, and redistributes the data of the SISSA scientific community in digital form. SISSA Open Data is managed by the SISSA Library as a service to the SISSA scientific community.

UC Irvine Machine Learning Repository

UCI Machine Learning Repository

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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.

Comprehensive R Archive Network

CRAN

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CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information.

Apollo

DSpace@Cambridge

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Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.

NIST Data Discovery

NIST PDR

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Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.

The SuiteSparse Matrix Collection

UFL, Sparse Matrix Collection

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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.