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The DNB Household Survey (DHS) supplies longitudinal data to the international academic community, with a focus on the psychological and economic aspects of financial behavior. The study comprises information on work, pensions, housing, mortgages, income, assets, loans, health, economic and psychological concepts, and personal characteristics. The DHS data are collected from 2,000 households participating in the CentERpanel. The CentERpanel is an Internet panel that reflects the composition of the Dutch-speaking population in the Netherlands. Both the DHS as well as the CentERpanel, in which the study in conducted, are run by CentERdata
From now on you no longer deposit archaeological data here in EASY . Please see: https://archaeology.datastations.nl/ EASY is the online archiving system of Data Archiving and Networked Services (DANS). EASY offers you access to thousands of datasets in the humanities, the social sciences and other disciplines. EASY can also be used for the online depositing of research data.
PWT version 10.0 is a database with information on relative levels of income, output, input and productivity, covering 183 countries between 1950 and 2019.
TiU Dataverse is the central online repository for research data at Tilburg University. The TiU Dataverse is managed by the Research Data Office (RDO) at Library and IT Services (LIS). TiU Dataverse takes part of the DataverseNL network. DataverseNL is a shared data service of several Dutch universities and institutions. The data management is in the hands of the member organizations, while the national organization Data Archiving and Networked Services (DANS) manages the network
The ICTWSS database covers four key elements of modern political economies: trade unionism, wage setting, state intervention and social pacts. The database contains annual data for all OECD and EU member states - Australia; Austria; Belgium; Bulgaria; Canada; Chile, Cyprus, the Czech Republic; Denmark; Estonia; Germany; Greece; Finland; France; Hungary; Iceland; Ireland; Israel, Italy; Japan; Korea, Latvia; Lithuania; Luxembourg; Malta; Mexico; the Netherlands; New Zealand; Norway; Poland; Portugal; Romania; Spain; Slovakia; Slovenia; Sweden; Switzerland; Turkey; the United Kingdom; and the United States – with some additional data for emerging economies Brazil; China; India; Indonesia; Russia; and South Africa; and it runs from 1960 till 2014.
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.