Geography Reference
In-Depth Information
Table 1 Sound variables and
their suitability for
representing data at different
scales (“
Suitability depending on data scale
Nominal
Sound variable
Ordinal
Cardinal
Location
”: not suited;
“
”: poorly suited; “+”:
suited with limitations; “++”:
suited)
Loudness
++
+
Pitch
++
++
Register
+
Timbre
++
Duration
Rate of change
+
Order
Attack/decay
Number
+
+
Summarizing this analytical review we can modify and expand the aforemen-
tioned list of Krygier (
1994
) by assessing the suitability of sound variables also for
the representation of data at a cardinal scale (Table
1
). In particular, it considers
differences between data at ordinal and cardinal scales according to the above made
statements.
Acoustic Coding of Quantitative Data for Time Series
For depicting time series (i.e. describing more than one point of time) diagrams are
the standard choice in cartography. Turning over to an acoustic representation, we
can of course transfer the aforementioned statements (second section). However,
there are further acoustic variable combinations and design options which should be
taken into consideration.
For the representation of a
bi-temporal change
the following options are feasible
(Fig.
1
).
• the attack or decay (crescendo/de-crescendo) of a sound can represent an
increase or a decrease, resp.;
• two different pitches are used to encode increase or decrease, resp. (a third pitch
might be used for the case “no change”);
• each of the three change cases are represented by a series of two tones (for
example, a second higher, a second lower, same tone).
Also for
multi-temporal series
of data values only little implementations and
studies have been published so far. One exception is the work done by Mezrich
et al. (
1984
) who propose the display of multivariate time series in a dynamic
manner with support of audio.
More conceptually, we can encode multi-temporal series of data again through
pitch (Fig.
2
) which can be changed
