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Found 8 result(s)
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
SEDAC, the Socioeconomic Data and Applications Center, is one of the Distributed Active Archive Centers (DAACs) in the Earth Observing System Data and Information System (EOSDIS) of the U.S. National Aeronautics and Space Administration. SEDAC is a regular member of the World Data System and focuses on human interactions in the environment. Its mission is to develop and operate applications that support the integration of socioeconomic and Earth science data and to serve as an "Information Gateway" between the Earth and social sciences.
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The Household, Income and Labour Dynamics in Australia (HILDA) Survey is a household-based panel study that collects valuable information about economic and personal well-being, labour market dynamics and family life.
The Scientific Data Repository Hosting Service (SARDC) intends to provide a platform for free access to data created and used in the scope of the research work of national institutions. It is characterized by the availability of a repository platform ( DSpace ) and support for the entire data maintenance component, such as backups, monitoring, updating, security, etc., thus keeping researchers out of the concern of these tasks. Finally, the SARDC service intends to make the data deposited in the repository available through the RCAAP Portal.
Arch is an open access repository for the research and scholarly output of Northwestern University. Log in with your NetID to deposit, describe, and organize your research for public access and long-term preservation. We'll use our expertise to help you curate, share, and preserve your work.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.