  Recent advances in the quantitative, computational methodology for the
modeling and analysis of heterogeneous large-scale data are leading to new
opportunities for understanding of human behaviors and faculties, including the
manifestation of creativity that drives creative enterprises such as science.
While innovation is crucial for novel and influential achievements, quantifying
these qualities in creative works remains a challenge. Here we present an
information-theoretic framework for computing the novelty and influence of
creative works based on their generation probabilities reflecting the degree of
uniqueness of their elements in comparison with other works. Applying the
formalism to the data set of a high-quality, large-scale classical piano
compositions represented as symbolic progressions of chords-works of
significant scientific and intellectual value-spanning several centuries of
musical history, we find that the enterprise's developmental history can be
characterized as a dynamic process of the emergence of dominant, paradigmatic
creative styles that define distinct historical periods. These findings can
lead to a deeper understanding of innovation, human creativity, and the
advancement of creative enterprises.
