Advances in technology have enabled the collection of data from
scientific observations, simulations, and experiments at an
ever-increasing pace. For the scientist and engineer to benefit
from these enhanced data collecting capabilities, it is becoming
clear that semi-automated data analysis techniques must be applied
to find the useful information in the data. Computational
scientific discovery methods can be used to this end: they focus on
applying computational methods to automate scientific activities,
such as finding laws from observational data. In contrast to mining
scientific data, which focuses on building highly predictive
models, computational scientific discovery puts a strong emphasis
on discovering knowledge represented in formalisms used by
scientists and engineers, such as numeric equations and reaction
pathways.
This state-of-the-art survey provides an introduction to
computational approaches to the discovery of scientific knowledge
and gives an overview of recent advances in this area, including
techniques and applications in environmental and life sciences. The
15 articles presented are partly inspired by the contributions of
the International Symposium on Computational Discovery of
Communicable Knowledge, held in Stanford, CA, USA in March 2001.
More representative coverage of recent research in computational
scientific discovery is achieved by a significant number of
additional invited contributions.
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