Abstract: In today‘s world, interactive visualization of large data is a must. Since the very beginning, filtering, sampling and aggregation were the three basic ways of dealing with large amounts of data. All of those methods helped and still help to squeeze a large number of objects into a limited number of pixels on a computer‘s screen. Among those three, the aggregation however, seems to be the most meaningful way of preprocessing data for visualization. Thus, the aggregation, specifically so-called inductive aggregation, became the matter of our research.
During the presentation we will discuss challenges and architectures of early visuzalization system and present our prototype visualization called Skydive. We will also and try to explain why the inductive aggregation may be useful for data visualization (in terms of efficiency and meaningfulness); why it is not obvious which aggregation function could be used as a data aggregation function; and
how graphical channels paucity problem could be addressed by using modern graphics cards capabilities.
Bio: Piotr Lasek is currently an Assistant Professor at the University Rzeszów, Poland. He obtained his PhD at the Warsaw University of Technology in the field of data mining - his thesis was devoted to
density-based data clustering. Over the past 2 years he was a Postdoctoral Fellow with the Database Laboratory at York University, Toronto working on efficient data visualization methods employing the
concept of inductive aggregation. His current research interests span both interactive data exploration through visualization as well as density-based clustering with constraints.