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Found 84 result(s)
Maddison's work contains the Project Dataset with estimates of GDP per capita for all countries in the world between 1820 and 2010 in a format amenable to analysis in R. The database was last updated in January 2013. The update incorporates much of the latest research in the field, and presents new estimates of economic growth in the world economic between AD 1 and 2010 The Maddison Project database presented builts on Angus Maddison's original dataset. The original estimates are kept intact, and only revised or adjusted when there is more and better information available. Angus Maddison's unaltered final dataset remains available on the Original Maddison Homepage https://www.rug.nl/ggdc/historicaldevelopment/maddison/original-maddison
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The GIGA (German Institute of Global and Area Studies) researchers generate a large number of qualitative and quantitative research data. On this page you will find descriptions of this research data ("metadata") as well as information about the available access options. To facilitate its reuse, and to enhance research transparency, a large part of the GIGA research data is published in datorium, a repository hosted by the GESIS Leibniz Institute for the Social Sciences: https://www.re3data.org/repository/r3d100011062 Our objective is to offer free access to as much of our data as possible, to guarantee the possibility of its citation, and to secure its safe storage. Metadata of research data that cannot be published open access due to its sensitivity is also shown on this page.
The National Collaborative on Childhood Obesity Research (NCCOR) brings together four of the nation's leading research funders — the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), the Robert Wood Johnson Foundation (RWJF), and the U.S. Department of Agriculture (USDA) — to address the problem of childhood obesity in America. The Tools of the NCCOR are: Catalogue of Surveillance Systems, Measures Registry and Registry of Studies.
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.
Eurostat is the statistical office of the European Union situated in Luxembourg. Its task is to provide the European Union with statistics at European level that enable comparisons between countries and regions. Eurostat offers a whole range of important and interesting data that governments, businesses, the education sector, journalists and the public can use for their work and daily life.
The United States Census Bureau (officially the Bureau of the Census, as defined in Title 13 U.S.C. § 11) is the government agency that is responsible for the United States Census. It also gathers other national demographic and economic data. As a part of the United States Department of Commerce, the Census Bureau serves as a leading source of data about America's people and economy. The most visible role of the Census Bureau is to perform the official decennial (every 10 years) count of people living in the U.S. The most important result is the reallocation of the number of seats each state is allowed in the House of Representatives, but the results also affect a range of government programs received by each state. The agency director is a political appointee selected by the President of the United States.
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.
The Medical Expenditure Panel Survey (MEPS) is a set of large-scale surveys of families and individuals, their medical providers, and employers across the United States. MEPS is the most complete source of data on the cost and use of health care and health insurance coverage.