Introduction to data-handling
tools
In data
sonification, while the input data can be
thought of as eventually controlling the sound rendering, the
transformations it has to undergo in the interim can be quite
considerable. Such data processing can reasonably include
multidimensional scaling, filtering and statistical analysis, which
itself may become the subject of sonification.
Each input dataset
can have potentially unique
structural characteristics. Some common characteristics are multiple
channels with various (and variable) amounts of noise and offset
biases, massively paralleled, metadata-embedded and multiplexed
arriving in real-time. Difficulties in displaying such datasets are
compounded when they need to be buffered and streamed in non-real-time
as is the case of multiple overlays of time sequences of different
temporal compressions.
High-level tools
for processing such data complexities
are rarely, if ever, found in computer music environments, and even
less likely if the input data is spatial rather than temporal. In fact,
it was the need for sophisticated data-handling tools that didn't have
to be written for specific composition tools, and then
maintained
across various hardware platforms and their operating system upgrades,
that led to the idea of the SoniPy Project.
SoniPy divides
tools for data-handling tasks into the
following categories:
- data acquisition
- data analysis
and generation
- data persistence
- data transfer
Modules for each category are discussed on separate pages. Use the menu
links, above, to access them.
The
visual display (plotting/graphing) of data
is covered under USER
INTERFACES .
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