Data and knowledge base research at Hong Kong University of Science and Technology

Abstract

The National Technical University of Athens (NTUA) is the leading Technical University in Greece. The Computer Science Division of the Electrical and Computer Engineering Department covers several fields of practical, theoretical and technical computer science and is involved in several research projects supported by the EEC, the government and industrial companies. The Knowledge and Data Base Systems (KDBS) Laboratory was established in 1992 at the National Technical University of Athens. It is recognised internationally, evidenced by its participation as a central node in the Esprit Network of Excellence IDOMENEUS. The Information and Data on Open MEdia for NEtworks of USers, project aims to coordinate and improve European efforts in the development of next-generation information environments which will be capable of maintaining and communicating a largely extended class of information in an open set of media. The KDBS Laboratory employs one full-time research engineer and several graduate students. Its infrastructure includes a LAN with several DECstation 5000/200 and 5000/240 workstations, an HP Multimedia Workstation, several PCs and software for database and multimedia applications. The basic research interests of our Laboratory include: Spatial Database Systems, Multimedia Database Systems and Active Database Systems . Apart from the above database areas, interests of the KDBS Laboratory span several areas of Information Systems, such as Software Engineering Databases, Transactional Systems, Image Databases, Conceptual Modeling, Information System Development, Temporal Databases, Advanced Query Processing and Optimization Techniques. The group's efforts on Spatial Database Systems, include the study of new data structures, storage techniques, retrieval mechanisms and user interfaces for large geographic data bases. In particular, we look at specialized, spatial data structures (R-Trees and their variations) which allow for the direct access of the data based on their spatial properties, and not some sort of encoded representation of the objects' coordinates. We study implementation and optimization techniques of spatial data structures and develop models that make performance estimation. Finally, we are investigating techniques for the efficient representation of relationships and reasoning in space. The activities on Multimedia Database Systems, include the study of advanced data models, storage techniques, retrieval mechanisms and user interfaces for large multimedia data bases. The data models under study include the object-oriented model and the relational model with appropriate extensions to support multimedia data. We are also investigating content-based search techniques for image data bases. In a different direction, we are studying issues involved in the development of multimedia front-ends for conventional, relational data base systems. In the area of Active Database Systems, we are developing new mechanisms for implementing triggers in relational databases. Among the issues involved, we address the problem of efficiently finding qualifying rules against updates in large sets of triggers. This problem is especially critical in database system implementations of triggers, where large amounts of data may have to be searched in order to find out if a particular trigger may qualify to run or not. Continuing work that started at the Foundation for Research and Technology (FORTH), Institute of Computer Science, the group is investigating reuse-oriented approaches to information systems application development. The approaches are based on a repository that has been implemented at FORTH as a special purpose object store, with emphasis on multimodal and fast retrieval. Issues of relating and describing software artifacts (designs, code, etc.) are among the topics under investigation. A new important research direction of the group is on Data Warehouses, which are seen as collections of materialized views captured over a period of time from a heterogeneous distributed information system. Issues such as consistent updates, data warehouse evolution, view reconciliation and data quality are being investigated. Research in Image Databases deals with the retrieval by image content, that uses techniques from the area of Image Processing. We are currently at early stage in this direction, having collected many segmentation and edge detection algorithms, which will be used and evaluated in images of various contents. Our work on Advanced Query Processing and Optimization Techniques includes dynamic or parametric query optimization techniques. In most database systems, the values of many important runtime parameters of the system, the data, or the query are unknown at query optimization time. Dynamic, or parametric, query optimization attempts to identify several execution plans, each one of which is optimal for a subset of all possible values of the run time parameters. In the next sections we present in detail our research efforts on the three main research areas of the KDBS Laboratory: Spatial, Multimedia and Active Databases.