PATTERN • SYMBOL • PERFORMANCE

Object-Oriented Music™ (“OOM”) is a generative symbolic framework for representing musical structure as reusable spatial objects rather than fixed notation alone.

Instead of treating music only as notes on a page, OOM models relationships such as rhythm, interval, repetition, variation, phrase structure, fingering, timing, and performance movement as manipulable symbolic objects that can be translated across visual, spatial, computational, and embodied forms.

Object-Oriented Music™ focuses on the sequence of actions the performer’s body must execute over time. Musical performance is therefore explored not only as abstract notation, but as an integrated structure of movement, memory, coordination, timing, repetition, and spatial pattern recognition.

The system developed through over fifteen years of teaching, performance, systems research, and experimentation in music pedagogy, visual abstraction, symbolic systems design, and computational modeling.

Music is used as the foundational domain because it is one of the earliest symbolic systems most people learn intuitively. Long before formal training, people understand repetition, variation, rhythm, tension, release, harmony, and form through listening and physical interaction. Object-Oriented Music™ uses this shared symbolic literacy as a basis for exploring broader systems of cognition, composition, symbolic representation, and human-centered system design.

At the center of the framework is a diatonic sequence structure derived from instructional work shared with Amy Lynn Freeman by musician Glenn “Houston” Pomianek and later expanded into a broader generative teaching model for students at Mountain View Piano™. These harmonic relationships were later abstracted into coordinate systems, visual grids, color structures, modular symbolic objects, and computational representations.

The framework draws from studies in Philosophy of Science at SUNY, Artificial Intelligence and Machine Learning training through Caltech, generative music education through the Simply Music™ piano method, developmental cognition, visual abstraction through Kandinsky and Klee, and color relationship studies inspired in part by Leonardo da Vinci.

Painting Music™ applies Object-Oriented Music™ to visual musical representation and embodied performance learning. Color Harmonics™ extends the same object relationships into visual abstraction and symbolic color systems. SaaSi Cubes™ expand the framework into modular symbolic environments for computational thinking, organizational systems, and information architecture.

The diagrams, sketches, charts, software experiments, visual systems, and teaching artifacts presented throughout this project document the evolution of Object-Oriented Music™ through experimentation, composition, teaching, and applied systems research over time.

Object-Oriented Music™ approaches musical learning as a generative process involving perception, memory, symbolic compression, movement, experimentation, visual structure, and embodied performance.