© 2001-2005 Franz J. Kurfess Knowledge Presentation 1 CPE/CSC 580: Knowledge Management Dr. Franz...

© 2001-2005 Franz J. Kurfess Knowledge Presentation 1

CPE/CSC 580: Knowledge Management

CPE/CSC 580: Knowledge Management

Dr. Franz J. Kurfess

Computer Science Department

Cal Poly


Course OverviewCourse Overview Introduction Knowledge Processing

Knowledge Acquisition, Representation and Manipulation

Knowledge Organization Classification, Categorization Ontologies, Taxonomies, Thesauri

Knowledge Retrieval Information Retrieval Knowledge Navigation

Knowledge Presentation Knowledge Visualization

Knowledge Exchange Knowledge Capture, Transfer,

and Distribution Usage of Knowledge

Access Patterns, User Feedback

Knowledge Management Techniques Topic Maps, Agents

Knowledge Management Tools

Knowledge Management in Organizations


Overview Knowledge PresentationOverview Knowledge Presentation

Motivation Objectives Evaluation Criteria Chapter Introduction

Cognition and Perception

Visualization Data Visualization Information Visualization Knowledge Visualization

Alternatives to Visualization Sound Tactile Presentation

Virtual Reality Immersion

Important Concepts and Terms

Chapter Summary


LogisticsLogistics Introductions Course Materials

textbook handouts Web page CourseInfo/Blackboard System and Alternatives

Term Project Lab and Homework Assignments Exams Grading


Stories, not Bories!Stories,

not Bories! lengthy explanations

endless bulleted lists allows the discussion of more

or less relevant issues at arbitrary levels of detail

important stuff in unreadably small font sizes

speaker reads from the display reinforces knowledge transfer

by exploiting multiple modalities

audience enjoys a nice nap no nasty/embarrassing

questions refreshed after the talk

[Clemens 1998, http://www.idiagram.com]


MotivationMotivation

reduce the user’s overhead for locating and interpreting knowledge indicate attributes of concepts show relationships between items display results of a search

visual computing utilize the features of computer displays

instead of “paper replication”

make technology conform to people instead of forcing people to adapt to technology


ObjectivesObjectives

be aware of perceptual and cognitive aspects of human information processing main emphasis on visual input

understand presentation methods and techniques for data, information, and knowledge

evaluate the use of visualization techniques for knowledge management purposes


CognitionCognition

cognitive engineering design principles for presentation techniques based on cognitive processes in humans

information processing, attention, memory

main emphasis on the visual system mental depiction can be as important as mental description

[Kowalski 1997]


PerceptionPerception

interface between our mind and the worldsensory information translates physical aspects of

the world into neural encodings in our brain visual and auditory systems are most relevant for

knowledge-related perception many lower-level processing steps are encoded in

“wetware” and happen sub-consciously

[Kowalski 1997]


Information VisualizationInformation Visualization

utilizes the visual system to indicate important aspects of data and information absence/presence quantity features

basis for writing, drawing, art long-distance communication long-term preservation of knowledge

graphical displays offer a much richer visual experience than text-based terminals flexibility, resolution, color

[Kowalski 1997]


Cognitive Aspects of VisionCognitive Aspects of Visionproximity

nearby items are grouped together

similarity similar items are grouped together

continuity smooth continuous patterns vs. separate items

closure automatic filling of gaps in a figure

connectedness interpretation of related items as single units

many of these aspects are performed at low levels of perception

[Kowalski 1997]


Visualization PrimitivesVisualization Primitivesbuilt-in, low level functions of our visual systemorientation of shapes

easy detection of groupings

color preference for primary colors

depth cues to size, distance of objects

arrangement of objects deviation from regular arrangements are easily detected

spatial frequency construction of a coherent visual image is attempted

[Kowalski 1997]


Technology: Visual ComputingTechnology: Visual Computing

computer presentation technology has some advantages over other media modify representations of data and information

e.g. change color, scale

show changes in space and time through animation use interaction with the user to optimize presentation

according to the user’s preferences

show relationships between items e.g. through hyperlinks


Visual Presentation TechniquesVisual Presentation Techniques

text mostly sequential good for details, explanations

diagrams two-dimensional good for structural aspects, relations between items, properties

images two-dimensional (partial) reproduction of real-world objects creation of imaginary objects

e.g. art


Visual Presentation MethodsVisual Presentation Methods

hierarchical structures (trees) appropriate for items with relations such as

is-a, part-of, parent-child, dependencies, etc.

becomes difficult to use for large structuresmap

arranges items according to spatial proximity useful for properties that map into space

with zooming, it can be used for large sets of itemsgrid

visualization of tabular data requires strong regularities in the overall information space

[Kowalski 1997]


Visual Presentation Methods cont.Visual Presentation Methods cont.

network (graph) items are represented as nodes, and relationships as arcs

clusters related items are grouped together

bar chart indicates values of properties

histogram shows the distribution of items

perspective wall main focus on the centerpiece (front), with less relevant items

arranged on the side panels

[Kowalski 1997]


Auditory Presentation TechniquesAuditory Presentation Techniques

language sequential similar to text

sound (partial) reproduction of real-world events creation of new events

e.g. music


Relevance of Knowledge Presentation

Relevance of Knowledge Presentation

better user experience shorter time to locate and identify relevant knowledge knowledge is easier to comprehend and utilize

improved understanding critical examination of existing bodies of knowledge exploration and validation of relationships suitable presentation of abstract concepts

creation of new knowledge integration of existing diverse bodies of knowledge addition of relationships between knowledge items


Data VisualizationData Visualization

visual display of data values

0

5

10

15

20

253-D Column 13-D Column 2050545862667074788286903-D Column 15


Information VisualizationInformation Visualization display of relationships for structured data

e.g. entity-relationship diagrams

document clustering present the user with a visual representation of the document space

constrained by the search criteria group related documents together

requires a similarity measure

search formulation analysis display the relationships between various aspects of the search terms

and the retrieved results effects of expansion, relevance feedback, etc.

used to help the user formulate a better query


Knowledge VisualizationKnowledge Visualization

link display indicates relationships between items color, patterns, thickness, arrows, labels, etc. can be used

to differentiate types of relationships

link analysis correlates multiple documents that share certain aspects helps with the identification of dependencies, trends, etc.


Alternatives to VisualizationAlternatives to Visualization

utilization of other senses for the presentation of knowledge auditory

speech signals

beeps

tactile virtual reality

taste smell


SoundSound

speech somewhat limited due to the sequential nature helpful as alternative or additional method

sounds sometimes used for alerts, or to augment aspects of visual

display

music primarily used for entertainment purposes may be used to evoke emotional responses


Tactile PresentationTactile Presentation

Braille as alternative to text input for visually impaired people

virtual reality mainly augmentation of visual input

special-purpose devices feedback mouse

special mouse/mouse pad combination that delivers some tactile feedback to the user

feedback joysticks, haptic gloves force feedback used for tele-manipulation, VR


Virtual RealityVirtual Reality

tries to provide a computer-based model of an environment

relies mainly on 3D visual inputfeedback between user and system is critical

direct manipulation of virtual objects

mostly used for modeling purposes, not so much for knowledge presentation


ImmersionImmersion

similar to VR, tele-presencethe user has the impression of being in another

environment


Inxight TreeInxight Tree tree displays the

hierarchical structure of a Web site

overview of available contents

quick navigation no details

[Inxight 2001]


Lexis-Nexis TreeLexis-Nexis Tree built with Inxight

Tree Studio


Understanding USA: EnvironmentUnderstanding USA: Environment

[Understanding USA]


ClearForest ClearSight ViewerClearForest ClearSight Viewer

[ClearForest 2001]


OutlineOutline

DefinitionsConstant Information DensityVISAGEBig Issues

[Woodruff 1998]


DefinitionsDefinitions

Scientific visualization Information visualizationDatabase visualization

[Woodruff 1998]


DefinitionsDefinitions

Scientific visualization Physical data, physical processes

Information visualization Abstract representations

Database visualization Mapping data in database

to graphical display

[Woodruff 1998]


OutlineOutline


[Woodruff 1998]


MotivationMotivation

Clutter can have negative effects Decreased user performance Diminished visual appeal …

VIDEO

[Woodruff 1998]


Comments?Comments?

Do people buy the concept of Constant Information Density?

What tasks might it be appropriate for?Will a new type of graphic replace existing

paradigms? Playfair...

[Woodruff 1998]


View from a high elevationView from a high elevation

At the user’s current elevation, only the state outline layer is visible

- This visualization has three layers.- At the user’s current elevation, shown by the horizontal line, only the state outline layer is visible. We can see the objects associated with this layer in the canvas on the left.

- This visualization has three layers.- At the user’s current elevation, shown by the horizontal line, only the state outline layer is visible. We can see the objects associated with this layer in the canvas on the left.

[Woodruff 1998]


View from an intermediate elevationView from an intermediate elevation

The cities circles layer becomes visible when the user zooms

States are still visible and a new layer is visible

States are still visible and a new layer is visible

[Woodruff 1998]


View from a low elevationView from a low elevation

The graph layer replaces the circles layer

At this elevation, a new layer is visible, and the circles layer is no longer visible, so a graph of transportation data for each city replaces the circle for each city

At this elevation, a new layer is visible, and the circles layer is no longer visible, so a graph of transportation data for each city replaces the circle for each city

[Woodruff 1998]


Width bars in our exampleWidth bars in our exampleA couple of slides ago we saw a cluttered visualization. This picture shows VIDA’s density feedback on that same visualization, using # objects as the density function.

A couple of slides ago we saw a cluttered visualization. This picture shows VIDA’s density feedback on that same visualization, using # objects as the density function.

We can see that at this particular elevation, this layer on the far right is causing us the trouble. We can also see that other elevations will be cluttered.

We can see that at this particular elevation, this layer on the far right is causing us the trouble. We can also see that other elevations will be cluttered.

The two layers on the left contain political boundaries. The four layers on the right contain cities of different sizes. We can see that there are different numbers of cities in each of these layers.

The two layers on the left contain political boundaries. The four layers on the right contain cities of different sizes. We can see that there are different numbers of cities in each of these layers.

[Woodruff 1998]


After the user has made adjustmentsAfter the user has made adjustments

User can make all the necessary adjustments without zooming back and forth to check each change

User can make all the necessary adjustments without zooming back and forth to check each change

[Woodruff 1998]


Housing cost/Income visualizationHousing cost/Income visualization

Before

After

- This is a visualization of housing cost (shown on the x axis) versus income (shown on the y axis).- States can be represented as either a dot or a state outline.

- This is a visualization of housing cost (shown on the x axis) versus income (shown on the y axis).- States can be represented as either a dot or a state outline.

VIDA chooses between these two representations based on density as measured by the # vertices - in the denser regions, dots are drawn. In less dense regions, the state outlines are drawn. Essentially, the user is shown more detail about outliers.

VIDA chooses between these two representations based on density as measured by the # vertices - in the denser regions, dots are drawn. In less dense regions, the state outlines are drawn. Essentially, the user is shown more detail about outliers.

[Woodruff 1998]


Fortune 500 visualizationFortune 500 visualization Displayed using VIDA’s

technique for non-uniform data Outliers have more detailed

representation

% profit

# em

ploy

ees

I’ve extended VIDA to support this functionality as I’ll illustrate in this example of Fortune 500 data

I’ve extended VIDA to support this functionality as I’ll illustrate in this example of Fortune 500 data

[Woodruff 1998]


Population visualizationPopulation visualization

Before After

Once the user has expressed their constraints, VIDA can choose different combinations of layers to show in different parts of the visualization

Once the user has expressed their constraints, VIDA can choose different combinations of layers to show in different parts of the visualization

Smaller cities are omitted in the more populous areas in which larger cities are drawn. In the less populous areas where no larger cities exist, the smaller cities are drawn.

Smaller cities are omitted in the more populous areas in which larger cities are drawn. In the less populous areas where no larger cities exist, the smaller cities are drawn.

[Woodruff 1998]


Operations to decrease densityOperations to decrease density

Change shape

Reduce size

Remove attribute association

Change color

Original

Select

Aggregate

Reclassify

Comprehensive list of actions that can be performed on the contents of a single layer to decrease data density

Comprehensive list of actions that can be performed on the contents of a single layer to decrease data density

Zoomed-in view of circles showing populations of cities; these are Baltimore and Washington, D.C.

Zoomed-in view of circles showing populations of cities; these are Baltimore and Washington, D.C.

Notice how visually different all these options are

Notice how visually different all these options are

For example, Decreases # objects

For example, Decreases # objects

Aggregate cities by state; Chesapeake Bay; Decreases # objects

Aggregate cities by state; Chesapeake Bay; Decreases # objects

Have only two sizes of cities;Decreases # sizes

Have only two sizes of cities;Decreases # sizes

Decreases amount of ink




Decreases data density

Decreases data density

Decreases # colors once we take other layers into account

Decreases # colors once we take other layers into account

Not every action affects every density functionActions may affect several density functions

Not every action affects every density functionActions may affect several density functions

<<Data operations>><<Data operations>>

<<graphical operations>><<graphical operations>>

[Woodruff 1998]


The transformation canvasThe transformation canvas Transformations presented

to user in a “transformation” canvas Each transformation appears

as a portal

When the user zooms, the visualizations all change

How should user navigate the transformation space?

-- VIDA should give transformations like the one the user selected- After user enters the portal for a transformation, they can edit it- VIDA could then show them transformations that incorporated their changes

-- VIDA should give transformations like the one the user selected- After user enters the portal for a transformation, they can edit it- VIDA could then show them transformations that incorporated their changes

<<This visualization in the upper-right is particularly interesting. The association between city circle size and population has been removed, and an association between state color and population has been added.>>

<<This visualization in the upper-right is particularly interesting. The association between city circle size and population has been removed, and an association between state color and population has been added.>>

Portals’ contents change dynamically

Portals’ contents change dynamically

- Portals are a natural mechanism for presenting a number of visualizations to the user.

- Portals are a natural mechanism for presenting a number of visualizations to the user.

[Woodruff 1998]


OutlineOutline


[Woodruff 1998]


IssuesIssues

What are some of the good techniques?What are some of the problems with VISAGE from

the user’s perspective?

[Woodruff 1998]


OutlineOutline


[Woodruff 1998]


Interesting things to visualizeInteresting things to visualize

Graphs The Web!!!

Networks Network administration

Financial data Data mining (very little visual data mining work to date)

etc...

[Woodruff 1998]


Open problems in visualizationOpen problems in visualization

What are the limits of visualization?Multi-dimensional analysisContext, context, context

Users get lost while navigating Users lose linkages in multiple views Users get confused composing Magic Lenses

Creation End-user programming, automated creation

Misrepresentation

[Woodruff 1998]


Knowledge TrailsKnowledge Trails



Knowledge Levels in OrganizationsKnowledge Levels in Organizations



Knowledge LandscapesKnowledge Landscapes



Visualization at NorthernLightVisualization at NorthernLight


Scatter PlotsScatter Plots

[Cook 1999]


Pie and Bar ChartsPie and Bar Charts

[Cook 1999]


Turkey Box PlotTurkey Box Plot

[Cook 1999]


Multidimensional DataMultidimensional Data

[Cook 1999]


DBMinerDBMiner

[Cook 1999]


DBMiner 2DBMiner 2

[Cook 1999]


Daisy ChartDaisy Chart

[Cook 1999]


ClementineClementine

[Cook 1999]


Decision Tree Visualization 1Decision Tree Visualization 1

[Cook 1999]



[Cook 1999]


Scientific VisualizationScientific Visualization

[Cook 1999]


Human EffectivenessHuman Effectiveness

[http://www.idiagram.com/]


Semiotic ModelSemiotic Model



Semiotic TriangleSemiotic Triangle



Knowledge VisualizationKnowledge Visualization

[Clemens 1998, http://www.idiagram.com/kv_venn.html]


Characteristics of Complex SystemsCharacteristics of Complex Systems



System RepresentationSystem Representation



System DynamicsSystem Dynamics



System HierarchiesSystem Hierarchies



Complex Adaptive Systems ModelComplex Adaptive Systems Model



Evolutionary System ModelEvolutionary System Model



Visualizing Complex SystemsVisualizing Complex Systems



Important Concepts and TermsImportant Concepts and Terms visual display cognitive science

knowledge presentation


Summary Knowledge PresentationSummary Knowledge Presentation

© 2001-2005 Franz J. Kurfess Knowledge Presentation 1 CPE/CSC 580: Knowledge Management Dr. Franz...

Documents

Transcript of © 2001-2005 Franz J. Kurfess Knowledge Presentation 1 CPE/CSC 580: Knowledge Management Dr. Franz...