CUBE

Working Paper Series

Issue No. 59 (December 2009 – January 2010)

Stelios Eliakis, Eleni Zampou and Katerina Pramatari

Information sharing and interoperability is a key ingredient for any system that participates in Service oriented architectures (SOA) and wants to communicate and exchange information with other partners. Although, there are many technologies that support interoperability, there is no research which extracts and aggregates the requirements of a system, the necessary architecture entities and tools. In this chapter we review the constraints and the principles that affect architecture design and the research efforts about interoperability infrastructures. Finally, we propose a set of architecture entities and tools that can enable, support and maintain interoperability in heterogonous, dynamic and constantly changing environments.

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Center of Studies on Business Intelligence and Database

Scientific Coordinator: Dr Damianos Chatziantoniou, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Research streams

Data Warehousing
Multi-Dimensional Analysis, Decision Support and OLAP
Data Mining and Knowledge Discovery in Databases
Data Stream Management Systems
Management of RFID Data Sets
Data Models, Query Languages and Optimization

Research Objectives

Perform basic research on all aspects of data warehousing: ETL processes, implementation and maintenance of data cubes, data modelling and design principles, query processing and optimization, indexing methods, tools. Develop languages, algorithms and tools to express easily and evaluate efficiently complex data analysis reports. Current work involves large telecom, internet, financial and healthcare data sets.
Develop best practices, derive success factors and understand common pitfalls of Business Intelligence implementations in the Greek public and private sectors.
Data stream systems are the focus of intense research activities
Sensor measurements, financial data, network packets and RFID data can all be seen as data streams. The ability to analyze data streams at real time is of increasing importance and has been identified as a crucial element for modern organizations and agencies. There are many open issues under investigation, such as how to model data streams, what is the best architecture for stream management systems, what kind of reports are appropriate, how to warehouse, index and mine stream data, etc.