DBLab School of Computer and Electrical Engineering KDBSL NTUA
Friday, November 17, 2017

Research

Data Warehouses

Data warehousing & On-Line Analytical Processing (OLAP) are core database technologies that comprise the driving forces behind modern business intelligence. The need for the novel integration of many incompatible data sources, the efficient storage and querying of vast amounts of multidimensional hierarchical data and the expressive presentation of results to the end user pose many new problems.

Web and Databases

We study models and techniques for managing Web data, and we explore alternative ways of interaction between databases and Web pages. XML has become a standard for information exchange in the Web, facilitating automatic processing of Web data sources. Since XML can be seen at a logical level as a data model that structures data in a hierarchy, a lot of interesting research issues emerge concerning the management of XML Web data.

Pattern Management

The vast volumes of information produced nowadays, makes the handling and storing of data increasingly harder. It is obvious that the huge volumes of data do not constitute knowledge per se, but special extraction methods have to be employed in order to produce knowledge artefacts. We call these artefacts, patterns. Till now, patterns had not been treated as primary citizens in most data models. The challenge from the database perspective is to develop models and tools for storing, querying and linking patterns with the underlying data.

Data Management for Location-based Services

Knowing where people are and how objects (e.g., vehicles) move in space is expected to be widely utilized in the near future. The so-called Location-Based Services (LBS, for short) take advantage of this basically spatiotemporal information so as to provide to users notification about events that just happened or are about to occur. Our approach stems from the necessity to manage and efficiently process the huge amounts of spatiotemporal and thematic data that are gathered in sources (e.g., sensors, GPS) and transferred through a network. Furthermore, developing capabilities to serve in almost real-time multiple concurrent requests from thousands of users is considered as a major challenge.