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Found 13 result(s)

KONECT

Koblenz Network Collection

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This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.

Stanford Network Analysis Project

SNAP

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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.

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.

CRAWDAD

Community Resource for Archiving Wireless Data At Dartmouth (US site)

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<<<!!!<<< CRAWDAD has moved to IEEE-Dataport https://www.re3data.org/repository/r3d100012569 The datasets in the Community Resource for Archiving Wireless Data at Dartmouth (CRAWDAD) repository are now hosted as the CRAWDAD Collection on IEEE Dataport. After nearly two decades as a stand-alone archive at crawdad.org, the migration of the collection to IEEE DataPort provides permanence and new visibility. >>>!!!>>>

The Content Name Collection

CNC

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<<<!!!<<< The repository is offline >>>!!!>>> A collection of open content name datasets for Information Centric Networking. The "Content Name Collection" (CNC) lists and hosts open datasets of content names. These datasets are either derived from URL link databases or web traces. The names are typically used for research on Information Centric Networking (ICN), for example to measure cache hit/miss ratios in simulations.

Antimicrobial Combination Networks

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The database aims to bridge the gap between agent repositories and studies documenting the effect of antimicrobial combination therapies. Most notably, our primary aim is to compile data on the combination of antimicrobial agents, namely natural products such as AMP. To meet this purpose, we have developed a data curation workflow that combines text mining, manual expert curation and graph analysis and supports the reconstruction of AMP-Drug combinations.

PermaSense High-Alpine Permafrost Data

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Data from high-alpine mountain permafrost research sites.

Social Computing Data Repository

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Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.

Ocean Networks Canada

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Ocean Networks Canada maintains several observatories installed in three different regions in the world's oceans. All three observatories are cabled systems that can provide power and high bandwidth communiction paths to sensors in the ocean. The infrastructure supports near real-time observations from multiple instruments and locations distributed across the Arctic, NEPTUNE and VENUS observatory networks. These observatories collect data on physical, chemical, biological, and geological aspects of the ocean over long time periods, supporting research on complex Earth processes in ways not previously possible.

VENUS in the Salish Sea

VENUS

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>>>!!!<<<VENUS coastal network, is now part of the Ocean Networks Canada Observatory>>>!!!<<< VENUS is a cabled undersea laboratory for ocean researchers and explorers. VENUS delivers real time information from seafloor instruments via fibre optic cables to the University of Victoria, BC. You can see ocean data live, recent and archived as well as learn more about on-going research

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.

Reality Commons

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Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.

LINDAT/CLARIAH-CZ repository

LINDAT/CLARIN repository

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LINDAT/CLARIN is designed as a Czech “node” of Clarin ERIC (Common Language Resources and Technology Infrastructure). It also supports the goals of the META-NET language technology network. Both networks aim at collection, annotation, development and free sharing of language data and basic technologies between institutions and individuals both in science and in all types of research. The Clarin ERIC infrastructural project is more focused on humanities, while META-NET aims at the development of language technologies and applications. The data stored in the repository are already being used in scientific publications in the Czech Republic. In 2019 LINDAT/CLARIAH-CZ was established as a unification of two research infrastructures, LINDAT/CLARIN and DARIAH-CZ.