kirti trivedi presentation

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Self-Generated Data Patterns

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Page 1: Kirti Trivedi Presentation

Self-Generated Data Patterns

Page 2: Kirti Trivedi Presentation

Recurring events leave their mark to create visible data patterns

Page 3: Kirti Trivedi Presentation

Footprints on a jogging track

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Fingers on a keyboard

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Riverwater flow on stones

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Such patterns are

Self-Evident

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What is Self-Evident ?

That, which does not need to be

verbally explained by language or

labels, and can be directly grasped

visually by everyone.

Capable of universal understanding.

Page 8: Kirti Trivedi Presentation

Smile, hair, broken teeth, glasses

Page 9: Kirti Trivedi Presentation

Mountain profile, cloud pattern, radiating glow

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Vigorous river water flow, battered stones

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Whole data pattern visible at a glance.

Great density of detail as contributed

by various parameters which create the

event.

Page 12: Kirti Trivedi Presentation

Visual Information Diagrams: Typical Process

Data Collection

Analysis and Processing of data to reveal the

desired Data Pattern

Creating Visual Representation of Data Pattern by

assigning meanings to visual forms and labeling them

Final Data Diagram

Page 13: Kirti Trivedi Presentation

Though the aim is to make visual diagrams,

the interpretation and understanding usually

is dependent on verbal labeling of the data

pattern.

Data DistancingThe distance created by the extent of labeling

which must be read before data can be understood.

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Generic quantitative variables need data labeling

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Understanding totally dependent on verbal information

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Many visual diagrams

exist just as

visual fillers on a page

or illustrations

without any significant

information function

Page 18: Kirti Trivedi Presentation

Some seem to exist because the intended audience is not capable of mentally visualizing the magnitude difference between 525 and 13

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Piling Up the Electoral Votes

REAGAN: 525 MONDALE: 13Republican Democrat

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Isolating data bits and presenting them as

single parameter patterns destroys the

Context of the Data, as well as the Density of Detail.

Both the Context and the Detail can be very useful in

understanding the data. Eliminating them may lead

to data loss and partial understanding.

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Data pattern created with dots

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Replacing dots with foot-marks

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Adding colour to suggest jogging track

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Actual track image not only shows data, but also whole context, detail, and relationships.

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The Whole Pattern, as well as magnifiable detail showing further patterns at smaller levels

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Data as it is.Watering as a parameter, contributing to grass density on the track

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A Virgin Computer Keyboard.

Unused and without use data pattern.

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Typing as creator of use data pattern

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Frequency, stroke strength and location, touching pattern for left and right hand fingers: recorded automatically by use.

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Co-existence of many different data types

including lack of proper housekeeping

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Use frequency map of Keys

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Strength and location of finger stroke on individual keys

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Possibility of composite mapping through multi-sampling

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Data about fingering pattern on a particular key from a sample of users

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Use data pattern on an old elevator control panelin an Office Building

Door Close button used much more than Door Open button

Maximum visitors for First Floor

Least visitors to 30th floor

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Dynamic data patterns on a beach

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Wave force, slope, sand particles distribution

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Wavelet sub-events

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multi-level, multi-variable data patterns

constantly changing

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endlessly generating themselves

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recording unfolding eventsin real time, as high resolution 3-D renderings

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variety and beautywith great clarity

naturally and effortlessly

Page 43: Kirti Trivedi Presentation

Individually and Collectively.

Visually, Completely, and Honestly.

Showing their story to whoever will see.