Learning objectives
The main emphasis of the course lies on information as a resource, and we will examine approaches to a more efficient and effective usage with the help of appropriate data management.
The successful participation will provide the students with the following competences: The students will be familiar with different scenarios of information integration, and how to represent data appropriately. They will understand the basic importance of heterogeneity and will be able to assess different architectures regarding their influence on information integration. Furthermore the students will be capable to apply different methods of the Schemaund meta data management, and will be familiar with approaches for semantic integration and data integration. In particular students should be able to understand what role integrated information systems and data warehouses are playing in this context. And they should be aware of and able to solve the typical problems of a successful integration. They will be familiar with different methods of data mining, and will be able to apply them to make the most of the integration.
Content
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| Basics: the emphasis lies on information integration scenarios, in particular the representation of data, especially the relational data model and XML, as well as corresponding query languages. Further emphasis lies on elementary concepts of distribution, autonomy and especially heterogeneity, and finally the architecture of information systems. |
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| Information integration techniques: first of all we will have a look at integrating, mapping and matching schemes. Since the schemes have to reproduce the semantics of the application fields adequately, ontologies and the semantic web play an important role in the semantic integration. But since the information is generated from data, we also have to consider the aspect of data integration and its influence on the quality of information. |
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| Systems and Applications: in the meantime the data warehouse can be considered as a classical approach to information integration, and its components will be examined and related with the different techniques introduced. The same applies for different infrastructures like Enterprise Application Integration or web services. At the end of the course we will work with different data mining case studies, i.e. using the integrated information. |
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