Graphics Reference
In-Depth Information
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Studying and measuring the impact of vi-
sualization, especially in emerging forms
of collaborative interactions, including
visual groupware, group support systems,
and social media;
outlines the shapes and fills them in with a sample
picture allowing the computer to send only an
outline and a picture to a destination.
See Table 12 for Your Reaction and Visual
Answer.
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The diffusion of input devices such as
(multi-) touch screens that provides fluid
forms of interaction;
3. TOOLS AND TECHNIQUES USED
IN VISUALIZATION
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Testing knowledge visualization in new
domains such as intercultural communica-
tion that can be useful to overcome linguis-
tic and cultural barriers.
The pace of growing the number, range, and
quality of tools and techniques used in visualiza-
tion quickens because of advances in technology.
Below, data mining, concept maps, knowledge
maps, open source intelligence, visual analyt-
ics, tag clouds, network visualization, network
visualization, web search result visualization,
visualization of the semantic web, and tag cloud
visualization will be mentioned briefly.
Martin Eppler (2011) reviews seminal concepts
related to knowledge visualization coming from
different domains, and then compiles a list of the
requirements of effective knowledge visualization,
showing the theoretical and practical implications
derived from five principles:
3.1. Data Mining
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Visual Variety:
Visual vocabulary to ex-
press ideas through various ways;
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Visual Unfreezing:
Re-elaborating the
captured and frozen visuals to be changed
again;
Data mining is a search for new, implicit, non-
trivial, previously unknown, and potentially useful
information within data. A data set with M items
has 2
M
subsets, any one of which may be the one
we really want. Our fantastic pattern recognition
ability can cut swaths and also extract insights
from the visual patterns (Inselberg, 2009). Spatial
data mining discovers patterns from large data
that may be spatial (such as location, shape, geo-
metric and topological properties) or non-spatial
(human age or activity). It allows for analysis
of large quantities of data such as stock market,
telecommunication, or scientific data in order to
discover meaningful patterns and search for new
information. It applies visualization techniques for
discovery and the transfer of knowledge from a
database and often includes interactive techniques
and the use of graphical tools.
Data mining allows making inferences, predic-
tions, and decisions made on the basis of reason-
ing about the data. Data mining, as the process
of selecting, preprocessing, and mapping the
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Visual Discovery:
Connecting elements in
new ways and detecting new patterns;
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Visual Playfulness:
Inviting to change
perspectives, assume new roles, immerse
in the collaborative effort, and reframe is-
sues creatively;
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Visual Guidance:
Providing a clear 'road-
map' of how it should be iteratively popu-
lated or completed.
George P. Lakoff, a cognitive linguistics pro-
fessor, says that conceptual metaphors address
cognitive abilities to abstract the essence of the
idea as they allow understanding an abstract or
unfamiliar domain in terms of another, more
concrete and familiar domain (Lakoff, 1990).
Abstracting would mean removing non-crucial
information, in a similar way as in an optimized
file or in a compressed video where the computer
