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Monday, June 27, 2016


World Music Visualisation Environment - Preferences and Population

A central strength in an aggregator platform such as in focus here lies in simple, visual customization according to own needs and at every level, and in allowing these customizations to be shared -individually or as a collection, according to needs- across the user community. Here some pointers as to how this can be achieved.

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User Environment Preferences

World Music Aggregator Platform Preferences and Population #VisualFutureOfMusic #WorldMusicInstrumentsAndTheory
Aggregator Platform Preferences & Population
Data visualisation is concerned with the visual representation of patterns in data.

In musical terms, think instrument fingerboards, keyboards, their roadmaps, exercises, chords, rhythm and musical application of colour.

Anywhere data patterns can be found, data visualisation can be applied.

As it happens, the tree structures we associate with instrument and other musical data is an excellent match with established visualisation (and storage) technologies.
Music Instrument Classification System Hornbostel Sachs Aerophones Chordophones  Electrophones Idiophones Membranophones. #VisualFutureOfMusic #WorldMusicInstrumentsAndTheory
Instrument Classifications, with Top Level of Hornbostel-Sachs

Regardless of platform, a user's musical preferences will dictate the specific visualisations with which they choose to populate their immediate environment.

This is as true for scores as for instrument models, theory tools, genres, scores, bands or any of a host of other fields of interest.
Instrument Classification. Family Subtree (a Selection). #VisualFutureOfMusic #WorldMusicInstrumentsAndTheory

Population with User Preferences

Given the ease with which hierarchical data can be transformed into one or more graphical representations, it makes sense to use our base data directly to populate the GUI - perhaps even allowing visual selection from a data tree to replace traditional text search.

When populating menus, for example, we would be free to select not just individual end points ('leaves" of the tree), but entire twigs or branches.

Safeguards against GUI over-population aside, this would be accurate, flexible, and provide immediate visual feedback.

A further benefit is that of code reuse. With all data sharing the same basic tree structure, code used to manipulate it can be reused across all data sources.

In our case, then, we are likely to end up with two levels of data population: the first populating a given user's menus, the second a working selection from these menus to populate the current animation, panel for actual use.

Potential Crowdfunder?

Flamenco genre classifications in world music context. #VisualFutureOfMusic #WorldMusicInstrumentsAndTheory
User Selection from Flamenco Genres to Populate Own Preferences

This approach to preferences and population unleashes a monumental flood of visualisation possibilities. To build on an earlier diagram (here just a foretaste!):

Some Examples of Music Visualisation Opportunities. #VisualFutureOfMusic #WorldMusicInstrumentsAndTheory
Examples of Music Visualisation Opportunities
This also gives us some idea of the potential for the creation of -for example- individual exercises (notation) touching on every aspect of music theory, but integrated across the entire instrument and theory tool spectrum.

Population with User Preferences

Assuming a live video chat session, sharing one's environment with others will, we envisage, be as simple as dragging individual menu items (or indeed entire menus) over a new learner's avatar. This simply mirrors the way menus are populated in the first place: only the source is different.


online music learning,
online music lessons
distance music learning,
distance music lessons
remote music lessons,
remote music learning
p2p music lessons,
p2p music learning
music visualisation
music visualization
musical instrument models
interactive music instrument models
music theory tools
musical theory
p2p music interworking
p2p musical interworking
comparative musicology
world music
international music
folk music
traditional music
P2P musical interworking,
Peer-to-peer musical interworking
WebGL, Web3D,
WebVR, WebAR
Virtual Reality,
Augmented or Mixed Reality
Artificial Intelligence,
Machine Learning
Scalar Vector Graphics,
3D Cascading Style Sheets,

Comments, questions and (especially) critique welcome.