In this project, we wish to highlight and exploit convergence of methods and techniques. The application domain, astronomy, is probably unique (it may well be) in facilitating and driving this convergence. From the astronomer's viewpoint, a coordinated global view of methods and techniques allows optimal exploitation of available information.
European research in these fields has always been innovative and productive. European-based teams were among the first to carry out assessments in astronomy of mathematical morphology, wavelets, neural networks, fractals, and so on, and to advance theory and practice of these methods.
The nature of this work is such that a greater merging of efforts will pay dividends. It will lead to focusing on the relevant information, rather than artifacts. It will clarify the implications of data compression strategies (and, in a broad sense compression includes data summarization, or analysis). The problems sketched out are not limited to scaling up traditional problem-tackling approaches, since major scale differences lead to qualitative differences. Significant methodological gains must be complimented with transfer of such knowledge to other researchers, to young researchers, and to the reindustrializing economies of eastern Europe and beyond.
A network would serve to consolidate European leadership. It would provide the necessary platform for coordination work. It would give a powerful boost to a range of methodological developments.
Problems which are described here are currently being worked on, in different ways, in different laboratories and departments. Different pairwise linkages and influences exist. Our goal instead is to make progress in this area be driven by rational study of the problems and their methodological solutions. We are seeking harmonization and coordination, together with comparative advantages which accrue from this. Such an ongoing and coherent commitment to this field is not currently available from any of the European organisations involved in astronomy or computing methodologies.
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