Seek and You Shall Find Visualization Tools Professor Elaine Ferneley

Seek and You Shall Find

Visualization Tools

Professor Elaine Ferneley

Prof Elaine Ferneley

What is Visualization?What is Visualization?

Defn: (vb) ‘to form a mental image or vision of ….. to imagine or remember as if actually seeing’

Graphic representations of data can be used to make the information contained more accessible. The graphical form is easier to investigate than tables of

data. It helps the user to search for items of interest and to

detect patterns. Examples include graphs and bar charts.

Cognitive activity – it goes on in the mind, creation of an internal model or cognitive map; Internal to the individual human being – provides insight

and understanding; Individuals will interpret visualizations in different ways


Visualization MetaphorsVisualization Metaphors

All attempts to create a representational picture from some information are visualization. Sometimes the representation will explain a physical fact e.g.

a bar chart for the heights of all the children in a class. Sometimes the representation will explain conceptual facts

e.g. business processes

Information visualization is different because the mapping is not based on the physicality of the data. All data has a physical form – words in a book, documents

stored on a hard disk but in order to graphically display the meaning behind the data a new physicality has to be created.

This new physical model creates a metaphor to help the user navigate the information that is presented to them. In Microsoft Windows, a desktop metaphor supports access to computer files.


A Classic VisualizationA Classic Visualization

Individuals all have a unique understanding &

perspective

May focus on planned journey – colour,

direction, interchangestations

Relevant portion isvisualised & resultant

model accessedduring journey

Unique internal model= your cognitive

map


Minard’s Map of Napoleon’s March on Moscow Minard’s Map of Napoleon’s March on Moscow – – Originally created in 1812Originally created in 1812

Depicts several variables in a small space:•the size of the French army depicted by the width of the bands; •its location on a two-dimensional surface; •the direction of the movement of the advance (pink upper band) and retreat (black lower band); •the temperature on certain dates during the retreat.

422,000 soldiersSet out, 10,000

returned

Deaths - soldiersfell through theiced over river

Deaths – as aresult of drop in

temperature


Florence Nightingale’s Coxcombs –Florence Nightingale’s Coxcombs – to highlight needless to highlight needless

deaths during the Crimea War (1854-56)deaths during the Crimea War (1854-56)

• Blue – deaths from preventable disease (cholera & typhoid);

• Red – deaths from wounds• Grey – deaths from other causes

• Mortality peaked in January 1855 - 2761 died of contagious diseases, 83 of wounds, 324 of other causes. • Based on the army's average strength of 32393, Nightingale computed an annual mortality rate of 1174 per 1000.


Key Visualisation IssuesKey Visualisation Issues

Selection: should all data be

represented; can selection take place

automatically; Is it useful to suppress

information. Presentation:

How do you lay the data out e.g. Harry Beck’s distortion of the tube network to make the best use of space and make it more memorable;

New issues of how to present on mobile devices.

Representation: Colours, lines, slopes, graphs,

pie charts etc; Can attributes be combined; How do you represent many

attributes (>20 ?). Scale:

How to cope with vast quantities of data – abstraction.

Rearrangement, interaction and exploration: Can the user view be

changed; Is it possible to explore the

underlying datasets.


Rearrangement –the key to insightRearrangement –the key to insight

Simple example for illustration: 10 crops e.g. rice,

cereal, barley, corn etc.;

7 treatments e.g. fertiliser, insecticide, pruning etc.;

Result of treatment noted:Purple =

improvement;White = degradation.

A B C D E F G

12345678910

10 c

rops

, ric

e, b

arle

y, c

orn

…

7 treatments: fertiliser, insecticide, pruning …


A B C D E F G

12345678910


A B C D E F G

13826104795

A B C D E F G

10 c

rops

, ric

e, b

arle

y, c

orn

…



13826104795

A B C D E F G


13826104795

A D C E G B F

Can now clearly see that certain groups of treatments are appropriate for certain types of crops

10 c

rops

, ric

e, b

arle

y, c

orn

…



Left and Right Brain ActivityLeft and Right Brain Activity

The need to produce visualisations of data can be seen as the need to incorporate left and right brain activity. Current search engines are seen as analytical, methodical,

serial technologies suited to the activities of the left hemisphere of the human brain.

Shapes and patterns have been ignored by the text based approach and would tap in to right hemisphere activity.

Bad displays of data obviously make perception much more difficult for people. The layout of the voting cards in some US states was seen

as the main reason why the whole 2000 election was thrown into turmoil because the poor representation of information actually hampered people’s decision making capabilities.


US Voting 2000 – Why we have Bush??US Voting 2000 – Why we have Bush??


US Voting – Why we have Bush??US Voting – Why we have Bush??


US VotingUS Voting

Errors associated with the design of the Palm Beach County ballot were primarily due to poor ballot layout, resulting in problematic spatial mappings.

The two-page format of the ballot violated the expectations of voters. People reading English text read from left to right and will read a left-hand page from top to bottom before reading a right-hand page. Thus, the natural behaviour for voters was to start at the top of

the left-hand page and read down. However, holes on the ballot book corresponded in

alternating fashion to candidates on the left and right pages. Some voters claimed to be confused and said that they wanted

to vote for the second candidate from the top left (Gore) but punched the second hole, which actually corresponded to Buchanan, who was listed on the right-hand page


Is this Possible???Is this Possible???


Focus on the dot in the centre and move your Focus on the dot in the centre and move your head backwards and forwardshead backwards and forwards


Are the purple lines straight or bent??Are the purple lines straight or bent??


Do you see grey areas in between the squares? Do you see grey areas in between the squares? Where did they come from?Where did they come from?


You should see a man’s face and a wordYou should see a man’s face and a word


This is not animated!This is not animated!


1. Relax and concentrate on the 4 small dots in the middle of the picture for 40 secs

2. Then, take a look at a wall near you (any smooth, single coloured surface)

3. You will see a circle of light developing

4. Start blinking your eyes a couple of times and you will see a figure.

Who do you see??Who do you see??


Rudolph Arnheim – the Power of the CenterRudolph Arnheim – the Power of the Center


When things come out of a centre or, the reverse, bear in When things come out of a centre or, the reverse, bear in on a centre, a dynamic is created. Our eye is drawn to or on a centre, a dynamic is created. Our eye is drawn to or away from the centreaway from the centre


When things come out of a centre or, the reverse, When things come out of a centre or, the reverse, bear in on a centre, a dynamic is created. Our eye is bear in on a centre, a dynamic is created. Our eye is drawn to or away from the centredrawn to or away from the centre


DaVinci’s The Last SupperDaVinci’s The Last Supper


What do You Feel?What do You Feel?








Visualization and Large DatasetsVisualization and Large Datasets

It is hoped that the previous experience of the user will help them with the new, abstract information. Investigating the semantics of data means creating links and

classifications regardless of physical boundaries and it is these semantic connections that can be given a graphical representation.

The aim of information visualisation is to provide a computer-based, interactive graphic of abstract data which improves cognition

As an alternative to a search on the internet returning a text list, a graphical representation can show the links between sets of concepts. The aims are to allow the user to find what they need faster

and to identify previously unrecognized relationships.


Problem of Information Retrieval from Problem of Information Retrieval from intranets/the internetintranets/the internet

External factors: Limited time, exponential growth of

content increase in naïve users, few new tools

Query factors: Encourage fast wandering, bibbling,

collaboration Support for fuzzy query formulation – do

you know what you want to know ???


Mapping Cyberspace using Geographic Mapping Cyberspace using Geographic MetaphorsMetaphors

IP access across USA Different colours

represent time & routing

Not accessible IP address

access from Stamford University


Statistical Maps of Cyberspace - Size of Statistical Maps of Cyberspace - Size of country represents internet usagecountry represents internet usage

A "census" of Internet connectivity by countries has been developed at Computer Science Department, University of Wisconsin - Madison, USA.

The map opposite shows the differential levels of network connectivity

http://www.cybergeography.org/atlas/internet_users_cartogram_large.png


The Art of AskingThe Art of Asking

Volvo intranet study 58% single keyword searches, 34% single phrase

searches, 8% > one word or phrase

Why are sophisticated questions not asked Users do not have mathematical or logic training –

Boolean expressions inappropriate “((nivana OR grunge) AND seattle) AND NOT hinduism” Semantic gulf – only 15% of users use the same

expression to search for a specific topic We’re lazy ! – usually only submit one word

My index is bigger than yours ! – approach of most search engine suppliers


Internet usage in EuropeInternet usage in Europe

Produced by Eric Guichard, at the Ecole Normale Superieure, Paris.

Countries are colour-coded according to hosts per capita and the green circles show domains per capita.

Blue diamonds show the national population.

http://www.cybergeography.org/atlas/guichard2_large.gif


Tile Based MapsTile Based Maps

"ET-Map" - a multi-level category map of the information space of over 100,000 entertainment related Web pages listed by Yahoo!.

Developed by by Hsinchun Chen, at the University of Arizona, USA


Virtual World RepresentationsVirtual World Representations

The 3D cityscape view of the Web generated by Map.Net.

You fly-through the world, with individual websites represented by different buildings.

The large skyscrapers are the most popular and important site on the Web.

http://www.map.net/


Themescape – very advanced but can not Themescape – very advanced but can not be reconfigured by interrogation be reconfigured by interrogation

a visual landscape of hundreds or thousands of web pages;

Peaks - represent concentrations of documents about a similar topic.

more documents create higher peaks;

valleys between peaks contain fewer documents but with more unique content;

Documents in common mountain ranges or valleys are related.

Topic Labels - reflect the major two or three topics represented in a given area of the map,

quick indication of what the documents are about;

additional labels often appear when you zoom into the map for greater detail.


Hyperbolic Trees Hyperbolic Trees – www.webbrain.com– www.webbrain.com

Ideal for hierarchical data Search engine

results File directories

Data, information and certainly knowledge is not hierarchical

Extension of the hyperbolic tree should consider cross branch associations.


Example 2: Spectacle from aidministrator.comExample 2: Spectacle from aidministrator.com

Data represented as a system of text labels & spheres connected by straight lines: Each label represents a class

(category) of pages, e.g. sports; Each sphere is an instance of a

class (every page belonging to that category).

The lines indicate that an instance is a member of a class or that a class is a subclass of another one (e.g. football is a member of sports and sports could be a subclass of entertainment).


How to Read a Spectacle GraphicHow to Read a Spectacle Graphic

All elements are located in space through a system of attraction and repulsion between the objects (as if you had springs inside the lines) objects that are semantically close appear

spatially close; objects that are semantically far away appear in

distant locations; In this context "semantically close" means that

two classes share many instances or that two instances belong to the same class.


How to Read a Spectacle Graphic Cont.How to Read a Spectacle Graphic Cont.

Example depicts the contents of recruitment agency database: Jobs classified economic sector:

recreation, finance, education The size & intersections of the

classes stands out immediately due to the clustering of spheres quite a few of the jobs are

classified under several classes; e.g. one of them "hangs" from finance, management & secretarial.

Classes placed on opposite sides of the diagram don't have any member in common (government & security vs., healthcare & sports).


Support MechanismsSupport Mechanisms

Natural language interfaces (AskJeeves – www.ask.com) “show me info on Nivana or other grunge bands from

Seattle but nothing on Hinduism” Query expansion

Query is automatically augmented with synonym keywords from a thesaurus

Tends to increase the amount of data brought back Domain pruning

Predefined categories e.g. Yahoo! Intelligent agents

Learn about the user Support user collaboration


Exploration - Exploration - Understand/identify the reasons behind a Understand/identify the reasons behind a rearrangementrearrangement

Must be interactive: Reconfigurable interfaces; Multiple views/perspectives;

Must be capable of interrogation: Embedded query manipulation languages;

Current limitations on recreation of graphical interfaces quickly Key questions:

Is the interface intuitive; Can the interface be reconfigured to give a user specific view; Can multiple concurrent views be displayed – essential for

knowledge sharing; Can the underlying data be queried; Can alternative views be generated within an acceptable time

period.


Finally, not All Visualizations have to be Finally, not All Visualizations have to be Serious!Serious!


Visualisation techniques are useful for KM activityhowever we are still at the R&D stage with little

commercial uptake – significantly more work needs to beundertaken to commercialise the idea.

SummarySummary

Key issues: Selection,

Presentation, Representation,

Rearrangement, Interaction and Interrogation.

Visualisation is not a new discipline