Thursday 14th June, 2012
4:30pm to 5:10pm
Semantic zooming involves providing the right type of information depending on the resolution of viewer. A canonical example is the map viewer, where country outlines are visible at one level and, as the user zooms in, provinces and roadways become increasingly visible. High-performance zooming technologies are critically dependent on the efficient materialization of views from the data resources and, for big data resources like sensor data, econometrics, social networks, biological databases, and networking performance data, they are impeded by the scale of the data and the need to preprocess the information into aggregate views in advance, reducing the granularity and timeliness of the insights that can be obtained from the zooming technology. Through parallelization, however, semantic zooming that operates directly on the data becomes possible. In this highly visual presentation and demo, we will show our ZettaZoom visualization engine that provides a protocol for Hadoop and HBase marshaling of data signals into visual representations that preserve the relationships present within the data, enabling semantic zooming over massive data collections.
CTO — Kitenga, Inc.
Mark Davis has 20 years experience in intelligent systems design and practice, including working on big data problems in unstructured information management before they were fashionable and only of interest to librarians and spies. As a program manager at Microsoft and then helping to spin-out Inxight from Xerox PARC, Mark has developed search engines and computational linguistic technologies that support enterprises and government programs. Currently CTO of Hadoop application vendor Kitenga, Mark is driven by a desire to make big data technologies accessible by mere mortals.
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