Converging Computing Methodologies in Astronomy: Scientific Background

The increasing integration in an astronomical setting of various methodologies in pattern recognition, information retrieval and data analysis is a characteristic of modern computational astronomy. Large astronomical databases and archives from space-borne missions, ground-based observatories, and large wide-field surveys, provide the technological infrastructure.

Against this backdrop, boundaries between theoretical domains have been lowered. A number of leading cases, and lessons to be drawn, will be described briefly.

The astronomical application domain offers a unique test-bed for establishing strengths and limitations of these methodologies (and it offers in addition an exportable model for other domains also). Astronomy is an on-line, nearly all-digital science, with high visibility, and a specifiable research community: these characteristics provide a fertile basis for dissemination of research results.

Current and on-going organisational and meeting-related initiatives include the following. These provide a backdrop to the project which can be beneficially used to communicate the project's results to a wider audience. From the project point of view, they are driven by subsets of the overall domain of interest.

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