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Found 16 result(s)
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.
<<<!!!<<< 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 Information Marketplace for Policy and Analysis of Cyber-risk & Trust (IMPACT) program supports global cyber risk research & development by coordinating, enhancing and developing real world data, analytics and information sharing capabilities, tools, models, and methodologies. In order to accelerate solutions around cyber risk issues and infrastructure security, IMPACT makes these data sharing components broadly available as national and international resources to support the three-way partnership among cyber security researchers, technology developers and policymakers in academia, industry and the government.
Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.
FLOSSmole is a collaborative collection of free, libre, and open source software (FLOSS) data. FLOSSmole contains nearly 1 TB of data covering the period 2004 until now, about more than 500,000 different open source projects.
The CONP portal is a web interface for the Canadian Open Neuroscience Platform (CONP) to facilitate open science in the neuroscience community. CONP simplifies global researcher access and sharing of datasets and tools. The portal internalizes the cycle of a typical research project: starting with data acquisition, followed by processing using already existing/published tools, and ultimately publication of the obtained results including a link to the original dataset. From more information on CONP, please visit https://conp.ca
The ColabFit Exchange is an online resource for the discovery, exploration and submission of datasets for data-driven interatomic potential (DDIP) development for materials science and chemistry applications. ColabFit's goal is to increase the Findability, Accessibility, Interoperability, and Reusability (FAIR) of DDIP data by providing convenient access to well-curated and standardized first-principles and experimental datasets. Content on the ColabFit Exchange is open source and freely available.
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.
SourceForge is dedicated to making open source projects successful. We thrive on community collaboration to help us create the leading resource for open source software development and distribution. IT professionals come to Sourceforge to develop, download, review, and publish open source software. Sourceforge is the largest, most trusted destination for Open Source Software discovery and development on the web.
The Energy Data eXchange (EDX) is an online collection of capabilities and resources that advance research and customize energy-related needs. EDX is developed and maintained by NETL-RIC researchers and technical computing teams to support private collaboration for ongoing research efforts, and tech transfer of finalized DOE NETL research products. EDX supports NETL-affiliated research by: Coordinating historical and current data and information from a wide variety of sources to facilitate access to research that crosscuts multiple NETL projects/programs; Providing external access to technical products and data published by NETL-affiliated research teams; Collaborating with a variety of organizations and institutions in a secure environment through EDX’s ;Collaborative Workspaces
US Department of Energy’s Atmospheric Radiation Measurement (ARM) Data Center is a long-term archive and distribution facility for various ground-based, aerial and model data products in support of atmospheric and climate research. ARM facility currently operates over 400 instruments at various observatories (https://www.arm.gov/capabilities/observatories/). ARM Data Center (ADC) Archive currently holds over 11,000 data products with a total holding of over 3 petabytes of data that dates back to 1993, these include data from instruments, value added products, model outputs, field campaign and PI contributed data. The data center archive also includes data collected by ARM from related program (e.g., external data such as NASA satellite).
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. With the collaborative features of GitHub.com, our desktop and mobile apps, and GitHub Enterprise, it has never been easier for individuals and teams to write better code, faster. Originally founded by Tom Preston-Werner, Chris Wanstrath, and PJ Hyett to simplify sharing code, GitHub has grown into the largest code host in the world.
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.