Computer Science – Artificial Intelligence
Scientific paper
Jul 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998spie.3349..450b&link_type=abstract
Proc. SPIE Vol. 3349, p. 450-455, Observatory Operations to Optimize Scientific Return, Peter J. Quinn; Ed.
Computer Science
Artificial Intelligence
Scientific paper
One of the manually intensive efforts of HST observing is the specification and validation of the detailed proposals for scientists observing with the telescope. In order to meet the operational cost objectives for the next generation telescope, this process needs to be dramatically less time consuming and less costly. We are prototyping a new proposal development system, the Scientist's Expert Assistant (SEA), using a combination of artificial intelligence and user interface techniques to reduce the time and effort involved for both scientists and the telescope operations staff. The advanced architectures and automation branch or Goddard's Information Systems Center is working with the Space Telescope Science Institute to explore SEA alternatives, using an iterative prototype-review-revise cycle. We are testing the usefulness of rule-based expert systems to painlessly guide a scientist to his or her desired observation specification. We are also examining several potential user interface paradigms and explore data visualization schemes to see which techniques are more intuitive. Our prototypes will be validated using HST's Advanced Camera for Surveys instrument as a live test instrument. Having an operational test-bed will ensure the most realistic feedback possible for the prototyping cycle. In addition, when the instruments for NGST are better defined, the SEA will already be a proven platform that simply needs adapting to NGST specific instruments.
Brooks Tom
Dallas Lisa
Grosvenor Sandy
Jones Jeremy E.
Koratkar Anuradha
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