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Scientific Database Management


Description

Scientific applications (e.g. climate research, manufacturing process control, marketing research) require data management support that differs significantly from traditional database applications like finance and administration. Even so-called non-standard database systems do not adequately address issues prevailing in scientific areas, for example time series analysis or multi- dimensional data modelling. Some substantial research has been carried out in the spatial and time domain, but mostly independently from one another and not focussed on the specific demands of scientific computing. In particular, little attention has been given to data modelling and administration tasks found in scientific computing in conjunction with physical database design and query optimization.

The research at IMMD VI concentrates on multi-dimensional arrays as a generic data model for scientific applications. Typically, some measured values (e.g. temperature values) can be described by a multitude of dimensions (e.g. space, time). Queries against these data make use of categorizations that can be defined for the different dimensions (e.g. days-weeks-months-years in the time domain). Our approach is to store data according to the dimensional categorizations in so-called packages and support query processing by materializing summary data (e.g. mean temperature for different month) for selected packages. Often, queries can be answered using the summary data instead of the raw data. The package model also allows for an integration of hierarchical storage management into query optimization.

More information

As this is an ongoing research effort, more information should be requested by sending an e-mail or fax to Thomas Ruf.

Contact

Thomas Ruf
ruf@informatik.uni-erlangen.de