TY - JOUR T1 - Smooth, Efficient, and Interruptible Zooming and Panning JF - IEEE Transactions on Visualization & Computer Graphics Y1 - 2018 A1 - Reach, Caleb A1 - North, Chris ER - TY - CONF T1 - Bandlimited OLAP cubes for interactive big data visualization T2 - Large Data Analysis and Visualization (LDAV), 2015 IEEE 5th Symposium on Y1 - 2015 A1 - Reach, Caleb A1 - North, Chris AB - Visualizations backed by data cubes can scale to massive datasets while remaining interactive. However, the use of data cubes introduces artifacts, causing these visualizations to appear noisy at best and deceptive at worst. Moreover, data cubes highly constrain the space of possible visualizations. For example, a histogram backed by a data cube is constrained to have a bin width that is a multiple of the data cube bin size. Similarly, for dynamic queries backed by data cubes, query extents must be aligned with bin boundaries. We present bandlimited OLAP (online analytical processing) cubes (BLOCs), a technique that uses established tools from digital signal processing to generate interactive visualizations of very large datasets. Based on kernel density plots and Gaussian filtering, BLOCs suppress the artifacts that occur in data cubes and allow for a continuous range of zoom/pan positions and continuous dynamic queries. JF - Large Data Analysis and Visualization (LDAV), 2015 IEEE 5th Symposium on PB - IEEE CY - Chicago, IL, USA ER -