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Found 13 result(s)

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.

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.

Australian Urban Research Infrastructure Network

AURIN

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AURIN is a collaborative national network of leading researchers and data providers across the academic, government, and private sectors. We provide a one-stop online workbench with access to thousands of multidisciplinary datasets, from over 100 different data sources.

Center for International Earth Science Information Network

CIESIN

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CIESIN is an interdisciplinary research and data center that provides access to a wide range of global data, associated documentation, and visualization and analysis tools to improve understanding of human interactions in the environment.

Secondary Analysis to Generate Evidence (SAGE) Dataverse

Secondary Analysis to Generate Evidence

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SAGE is a data and research platform that enables the secondary use of data related to child and youth development, health and well-being. It currently contains research data, and at a later stage we aim to also house administrative and community service delivery data. Technical infrastructure and governance processes are in place to ensure ethical use and the privacy of participants. This dataverse provides metadata for the various data holdings available in SAGE (Secondary Analysis to Generate Evidence), a research data repository based in Edmonton Alberta and an intiative of PolicyWise for Children & Families. In general, SAGE contains data holdings too sensitive for open access. Each study lists a security level which indicates the procedure required to access the data.

ICRISAT Dataverse

International Crops Research Institute for the Semi-Arid Tropics Dataverse Network

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ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.

Ortolang

Outils et Ressources pour un Traitement Optimisé de la LANGue

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ORTOLANG is an EQUIPEX project accepted in February 2012 in the framework of investissements d’avenir. Its aim is to construct a network infrastructure including a repository of language data (corpora, lexicons, dictionaries etc.) and readily available, well-documented tools for its processing. Expected outcomes comprize: promoting research on analysis, modelling and automatic processing of our language to their highest international levels thanks to effective resource pooling; facilitating the use and transfer of resources and tools set up within public laboratories to industrial partners, notably SMEs which often cannot develop such resources and tools for language processing given the cost of investment; promoting French language and the regional languages of France by sharing expertise acquired by public laboratories. ORTOLANG is a service for the language, which is complementary to the service offered by Huma-Num (très grande infrastructure de recherche). Ortolang gives access to SLDR for speech, and CNRTL for text resources.

openLandscapes

The Knowledge Collection for Landscape Science

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<<<!!!<<< This repository is no longer available. 2018-10-15: no more access to OpenLandscapes >>>!!!>>>

Centre National de Ressources Textuelles et Lexicales

CNRTL

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Created in 2005 by the CNRS, CNRTL unites in a single portal, a set of linguistic resources and tools for language processing. The CNRTL includes the identification, documentation (metadata), standardization, storage, enhancement and dissemination of resources. The sustainability of the service and the data is guaranteed by the backing of the UMR ATILF (CNRS - Université Nancy), support of the CNRS and its integration in the excellence equipment project ORTOLANG .

OpenML

Open Machine Learning

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OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.

Forschungsdatenzentrum am IQB

Forschungsdatenzentrum am Institut zur Qualitätsentwicklung

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The Research Data Centre (Forschungsdatenzentrum, FDZ) at the Institute for Educational Quality Improvement (Institut zur Qualitätsentwicklung im Bildungswesen, IQB) archives and documents data sets resulting from national and international assessment studies (such as DESI, PIRLS, PISA, IQB-Bildungstrends). Moreover, the FDZ makes these data sets available for re- and secondary analysis. Members of the scientific community can apply for access to the data sets archived at the FDZ.

Open Science Framework

OSF

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The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.

International Food Policy Research Institute Dataverse

IFPRI Dataverse

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The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.