We are witnessing a tremendous proliferation of database sources in many aspects of our lives. These sources contain large volumes of information, and are heterogeneous in their design and content. To make meaningful use of this information, modern information systems need to be able to understand, process, query, integrate and maintain it.
In successfully performing these tasks, metadata plays an important role. Metadata examples include schema information, data constraints, user comments, ontologies, quality parameters, data annotations, provenance information, etc. Unfortunately, existing database systems do not provide true support for metadata. This forces data administrators to manually perform the metadata management task which is laborious, time consuming and error-prone. Although there are a few systems developed for that goal, they are usually ad hoc applications and are limited to certain kinds of metadata only.
The objective of this initiative is to promote research in that area. The ultimate goal is to provide common techniques and tools for efficiently and effectively managing data and metadata. This direction is justified by two main observations. The first is the fact that the volume and the different kinds of metadata have grown extremely large, and manual techniques will soon become practically impossible to apply. The second is that the distinction between data and metadata has been blurred to the point where the same piece of information is seen as data by some people and as metadata by others.
Our research will focus on two different approaches. One is the development of sophisticated techniques to support the metadata processing requirements, and enhance with them the existing database management systems. The second is the reduction of the different kinds of metadata and their techniques into one common framework. We propose to develop and evaluate research prototypes exploring concepts and techniques from the mature data management area.
Fields of science
Call for proposal
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