Graphics Reference
In-Depth Information
and Cairns (2005, pp. 110-118), Mantra serves as
a methodological guidance to practitioners who
seek to design novel systems and many authors
reference to Mantra as a holistic approach to
visualization design. It offers many implementa-
tions, such as information visualization systems,
document analysis visualization tools, software
visualization tools, or design implementations,
methodologies, evaluations, and taxonomies In-
formation visualization application should support
seven high level tasks: overview, zoom, filter,
detail-on-demand, relate, history, and extract;
they were later elaborated in prescriptive way by
Craft and Cairns (2005, pp. 110-118):
cognition. The dynamic filters allow users
quickly see how the changed variable af-
fects the data representation;
•
Details-on-Demand on a Selected Item,
with the Level-of-Detail Design:
'Details-
on-demand' (a simple action such as a
mouse-over or selection) can limit visual
complexity without requiring a change of
view or the data context, on a point-by-
point basis. Data items can number from
dozens to millions. Specific data elements
can be identified amongst many or relating
attributes of some data points;
•
Relate:
Viewing relationships between the
data items with hierarchical parent-child
relationships of data, so the user can sepa-
rate nodes from leaves, and make compari-
sons among the characteristics of different
data objects in the display;
•
History of Actions:
To support undo, re-
play, and progressive refinement, to allow
the user to delete, create, and move files
and directories. 'History' means an ability
to return to a previous state, recover from a
mistake, and replay a sequence of changes
in refining the data;
•
Overview of the Entire Collection:
For
the file system - the size of files, for the
newspaper - the number and size of ar-
ticles. 'Overview' can provide assistance
in understanding the information that is
encoded, a picture of a whole dataset and
data relationships, so the user can filter the
extraneous information and exclude unim-
portant aspects of the representation;
•
Zoom on Items of Interest:
'Zooming and
filtering' involve reducing the complexity
of the data representation. Zooming is of-
ten used as an expression of scalar changes
of space, i.e., vantage points rather than
changes of discrete screen objects such as
text or icons. Zooming involves two cog-
nitive tasks. Zooming-in enlarges smaller
data elements of interest, and removes from
the visual field or reduces the size of larger
data that are not of interest. Zooming-out
reveals hidden, often contextual informa-
tion and integrates the close inspection into
a larger understanding;
•
Extract Sub-Collections and Query
Parameters:
To save the current state
of visualization. 'Extraction' provides a
means of selecting and applying important
findings for use in other computing sys-
tems and saving work exploration when the
use of the information visualization tools
involves lengthy and complex operations
(Craft and Cairns, 2005).
According to Ward, Grinstein, & Keim (2010,
p. 25), the process of visualization involves map-
ping from the data to the display. The entered,
presented, monitored, analyzed, and computed
data are thus translated into more visual and intui-
tive formats for users For this reason data values
and their attributes are used to define graphical
objects. With user interaction and collaboration,
•
Filter Out Uninteresting Items:
Filtering
diminishes complexity in the display but
it disturbs the general context. The adjust-
ment of widgets in the interface allows for
control of which data points are visible, so
that information can be simplified to aid
