AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

AG Audience

English

90 Minutes

Saarbrücken

Today's scientific processes heavily depend on fast and accurate analysis of experimental data. Scientists are routinely overwhelmed by the effort needed to manage the volumes of data produced either by observing phenomena or by sophisticated simulations. As database systems have proven inefficient, inadequate, or insufficient to meet the needs of scientific applications, the scientific community typically uses special-purpose legacy software. When compared to a general-purpose data management system, however, application-specific systems require more resources to maintain, and in order to achieve acceptable performance they often sacrifice data independence and hinder the reuse of knowledge. With the exponential growth of dataset sizes, data management technology are no longer luxury; they are the sole solution for scientific applications.

I will discuss some of the work from teams around the world and the requirements of their applications, as well as how these translate to challenges for the data management community. As an example I will describe a challenging application on brain simulation data, and its needs; I will then present how we were able to simulate a meaningful percentage of the human brain as well as access arbitrary brain regions fast, independently of increasing data size or density. Finally I will present some of the data management challenges that lie ahead in domain sciences, and will introduce NoDB, a new query processor which explores raw, never-before-seen data in-situ, using full querying power.

Susanne Rock

0631-9303-9600

--email hidden

Yes

Kaiserslautern

G26

206

passcode not visible

logged in users only