Due to the highly distributed nature of modern information systems, data management has reached another advanced level. The relational data sets no longer support a variety of requirements, and often deal with less structured data and purposefully tailored data types. As a result, XML and its integration with relational databases has become a frequent necessity. EII is in a very strong position to contribute to this research program through collaboration with experts in inter-organisational computing, and cultivating industry links to bring additional insights to established expertise in the field.

Relational databases are often employed in order to store the content of a web site. At the same time, XML is fast emerging as the dominant standard for data interchange and publication. Thus, the integration of XML documents with relational database systems to enable the storage, retrieval, and update of XML documents is of major importance. Data model heterogeneity and schema heterogeneity, however, make this a challenging task. In this research, we investigate approaches for integrating XML documents, and mapping between XML documents/databases and relational databases, in order to build up applications that use the integrated documents/resources. Other issues that must be investigated include: formal approaches for XML document/database design, various constraints specification and enforcement, query processing, and updating methods and optimisation.

Knowledge management (KM) is defined as "a multi-disciplinary approach to achieving organisational objectives by making the best use of knowledge. It involves the design, review and implementation of both social and technological processes to improve the application of knowledge, in the collective interest of stakeholders" (Standards Australia International, 2003). The nature of many KM systems is pervasive with an enterprise wide or community wide scope. The intelligent activities of organisations and communities are increasingly mediated and recorded in digitised form, providing histories of useful records which are relevant to smarter decision making and for enacting informed choices. Also, as we increasingly share our social and living environment with intelligent and (semi) autonomous devices and agents, the is critical to ensure that the technological and human aspects of knowledge are aligned.

Program Coordinator

Prof. Xuemin Lin is a Professor in the School of Computer Science and Engineering at the University of New South Wales. His principal research areas are database systems and graph visualisation with the goal is to develop efficient and effective techniques that are fundamental to modern applications of database systems. Currently, he is working on data streams, approximate query processing, and spatial query processing.