„We are drowning in information,
but starving for knowledge. “
(John Naisbitt, *1929)
Mental Representations and Visualization
Processes in Organizational Memories
Stefan Smolnik – Ludwig Nastansky – Torsten Knieps
University of Paderborn, Germany
7th International Conference
Information Visualisation (IV03-KDViz)
London, England, July, 16 – 18, 2003
Overview
Motivation
From perception to information
Mental representations
Visualization processes
Small case: GCC K-Pool
Conclusions and future areas of research
Motivation
Groupware-based knowledge management system as a
point of reference
Theory/literature study as a basis for the
evaluation/enhancement of visualization prototypes
Infoglut:
From perception to information
Prerequisite for processing information: the perception
of an information-transmitting stimulus
Eye fixation: Gathering and processing of information
Fixation points: groups of words or known patterns in
images
Perception of motion:
Translation
Rotation
Change of an object’s shape
Visualizations support human apprehension by reducing
presented information through abstraction.
Mental representations
How are information and knowledge represented in
mind?
Semantic network model
Information is filed into a hierarchical classification model
Schema
Newly acquired knowledge is filed with regard to already filed
knowledge
Propositional representations and mental models
Mental symbols describing the represented subject in a mental
language + mental scenes spatially represent personally experienced
or adapted situations and facts
Connectionism based representation
Representation of information and knowledge is describable as a
certain wiring diagram and the resulting state of a neuronal network
Visualization processes
The encoding of information into visualizations passes
through several stages.
Visualization process following Chi:
Visualization processes
Filtering: data transformation
Interpolation, reduction, or filter techniques
Diminution to a presentable complexity or the interpolation of
insufficient data
Visualization processes
Mapping: visualization transformation
Data is translated into abstract geometrical objects
Translation from n dimensions into geometrical and topological
qualities of visual objects like color, form, and texture
Visualization processes
Rendering: viewing transformation
Translation of the resulting geometrical abstraction into a two
dimensional visual form of representation
Projection onto a display
Small case: GCC K-Pool
Versatile knowledge management system
Integrated and open environment for information
gathering, contextualization, communication,
collaboration, and information dissemination
Modules:
Document and content management
Workflow processing
Granular access structure from intranet to internet
Rich and flexible taxonomy
Variety of surfaces/viewers supporting ‘intelligent’
working by visualization of content semantics
Small case: GCC K-Pool
Alphabetical navigation about
authors and themes
Full text search
Categorizations with categories for
information object types, keywords,
and user-defined categories
Small case: GCC K-Pool
HyperbolicModeler
1. Visualize and modify categories, i.e. the hierarchical
structure
Focus + Context
Supporting mechanisms: cut and paste, drag and drop,
search for text in category structures, and thumbnails
2. Visualize the K-Pool topic map
Smolnik/Erdmann “Visual Navigation of Distributed
Knowledge Structures in Groupware-based
Organizational Memories” in the proceedings of the
IV02-KDViz
HyperbolicModeler
Filtering: manual by authors
Mapping: hyperbolic geometry
algorithms
Rendering: StarTree engine
K-Viewer
Graphs and graph-based resp. visual languages
Java class library yFiles: algorithms and components for
analyzing, viewing, and layouting graphs, diagrams, and
networks
Topic map as the underlying data structure
Supporting mechanisms: different layout styles,
zooming, search for requested information objects,
hierarchical tree view, graph overview, and thumbnails
K-Viewer – organic
Filtering: configuration/maintenance
of the topic map
Mapping: graphic engine; document
authors (thumbnails)
Rendering: graphic engine
K-Viewer – circular
K-Viewer
Sky Surfer
Web-based application using the Virtual Reality
Modeling Language (VRML), now X3D
Information comprehended in the underlying data
structure (again a topic map) is identified, analyzed, and
finally clustered to semantic fragments.
Semantic fragments represented by graph-based threedimensional visualizations
Supporting mechanisms (provided by a Java applet):
search for requested information objects, zooming,
rotating, ‘flying and walking’, and thumbnails
Sky Surfer
Demo
Filtering: configuration/maintenance
of the topic map
Mapping: Sky Surfer backend;
document authors (thumbnails)
Rendering: VRML engine/plug-in
Conclusions and future work
All three visualization tools provide capabilities to
support structure recognition and therefore, to enhance
human apprehension.
K-Viewer: different implemented layout styles increase
the quality of visual information gathering
Sky Surfer: support of motion perception
Topic maps: support the basic way of thinking
(associations)
Continuous improvements of the prototypes
Empirical evaluation: usability tests
Questions & discussion
K-Discovery @Web: http://gtm.upb.de
University of Paderborn
Business Computing 2 – Information Management & Office Systems
Faculty of Business Administration, Business Computing & Economics
Phone: +49--5251--60-3375
Email: [email protected]
GCC @Web: http://gcc.upb.de