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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
It is a common platform to deposit, store and share the research data in the area of social and behavioral sciences. openICPSR is undergoing development commiting international archiving standard and is currently free for all users to share their data up to a 2GB limit. It has a distribution network of over 760 institutions, governed by the Attribution 4.0 Creative Commons License and its' data catalog indexed by major search engines. OpenICPSR is a research data-sharing service that allows depositors to rapidly self-publish research data, enabling the public to access the data without charge. Otherwise via standard ICPSR deposits, one can publish and preserve reseach data with restricted-use having nominal charge. ICPSR is part of the Institute for Social Research at the University of Michigan.
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