Tools for Astronomical Big Data
Tucson, Arizona, March 9-11, 2015
Talk Abstracts (Submitted)
Consider exploration of large multidimensional spatiotemporal datasets with billions of entries. Are certain attributes correlated spatially or temporally? How do we even look at data of this size? In this talk, I will present the techniques and algorithms to compute and query a nanocube, a data structure that enables interactive visualizations of data sources in the range of billions of elements.
Data cubes are widely used for exploratory data analysis. Although they are sometimes assumed to take a prohibitively large amount of space (and to consequently require disk storage), nanocubes fit in a modern laptop's main memory, even for hundreds of millions of entries. I will present live demos of the technique on a variety of real-world datasets, together with comparisons to the previous state of the art with respect to memory, timing, and network bandwidth measurements.
Authors: Carlos Scheidegger