+ All Categories
Home > Documents > MDST 3705 2012-03-05 Databases to Visualization

MDST 3705 2012-03-05 Databases to Visualization

Date post: 21-Nov-2014
Category:
Upload: rafael-alvarado
View: 2,444 times
Download: 1 times
Share this document with a friend
Description:
 
Popular Tags:
73
From Database to Visualization Prof Alvarado MDST 3705 5 March 2013
Transcript
Page 1: MDST 3705 2012-03-05 Databases to Visualization

From Database to Visualization

Prof AlvaradoMDST 3705 5 March 2013

Page 2: MDST 3705 2012-03-05 Databases to Visualization

Business

• Quiz 2 to be posted this evening– Covers everything between the last quiz and

last week– Database theory and practice

Page 3: MDST 3705 2012-03-05 Databases to Visualization

Review

• Last week, we explored the idea of the database as a “symbolic form” and “genre”– The Database is a mode of representation

comparable to such things a linear perspective in painting and the novel in writing

• The Database has certain representational qualities– Everything is a list (like an array)– Order does not matter– No inherent beginning or end– Endlessly reconfigurable (SELECT, JOIN, etc.)

Page 4: MDST 3705 2012-03-05 Databases to Visualization

Review

• The Database stands in contrast to narrative– Traditional narrative is sequential and fixed– Endings matter; novels have an arc.

• The Database reverses the relationship between paradigm and syntagm– Traditional works are final products of a

process that is hidden and forgotten– The products of a database are ephemeral

and contingent – the database itself is the thing

Page 5: MDST 3705 2012-03-05 Databases to Visualization

Review

• Databases have a logic that is used in the arts– Stories in which the order of events or

perspectives are mixed up. Manovich calls the ‘database logic’

– An example is the film, Man with a Movie Camera

• Databases can be more effective than books in organizing works of art and literature– E.g. The Whitman Project

Page 6: MDST 3705 2012-03-05 Databases to Visualization

Vertov's film shows the relationship between Database and Montage

Just as we saw that Linear Perspective and the Novel

go together

Page 7: MDST 3705 2012-03-05 Databases to Visualization

Data(bases) can be visualized

More than that, they lend themselves to visualization

Let’s look at a couple of examples …

Page 8: MDST 3705 2012-03-05 Databases to Visualization

A radial network graph from data scraped from Pandora, beginning with the Beatles

Page 9: MDST 3705 2012-03-05 Databases to Visualization

A force directed network graph of data scraped from Pandora, beginning with Elvis Costello

Page 10: MDST 3705 2012-03-05 Databases to Visualization

These network visualizations show the database as a genre – a way of

representing information

Compare them to a catalog of musical artists in a book (itself a kind of

database)

Page 11: MDST 3705 2012-03-05 Databases to Visualization

A database record depicted as a kind of text

Page 12: MDST 3705 2012-03-05 Databases to Visualization

The examples also show the database as a way to understand genre

Page 13: MDST 3705 2012-03-05 Databases to Visualization

What is visualization?

Page 14: MDST 3705 2012-03-05 Databases to Visualization

“a mapping between discrete data and a visual representation”

(Manovich)

or

a mapping of information in logical form to visual form

Page 15: MDST 3705 2012-03-05 Databases to Visualization

Manovich defines two types:

Information Visualization

Media Visualization

Page 16: MDST 3705 2012-03-05 Databases to Visualization

Statistics and information visualization were invented in the 18th century. This was linked to the rise of nation states and bureaucracy

William Playfair

Page 17: MDST 3705 2012-03-05 Databases to Visualization

The result of nations becoming aware of data ...

Page 18: MDST 3705 2012-03-05 Databases to Visualization

According to Manovich, the salient features of information visualization are

(1) The reduction of data items to points, lines, etc.

and

(2) the use of space (size, shape, etc.) as the primary vehicle of representation

Color is used, but as an embellishment

Page 19: MDST 3705 2012-03-05 Databases to Visualization

Here are some examples …

Page 20: MDST 3705 2012-03-05 Databases to Visualization

http://www.visionlearning.com/library/large_images/image_4108.png

William Playfair (1786) The Commercial and Political Atlas: Representing, by Means of Stained Copper-Plate Charts, the Progress of the Commerce, Revenues, Expenditure and Debts of England during the Whole of the Eighteenth Century.

Page 21: MDST 3705 2012-03-05 Databases to Visualization

http://dougmccune.com/blog/wp-content/uploads/2010/01/playfair_north_america_trade2.jpg

Page 22: MDST 3705 2012-03-05 Databases to Visualization

http://www.economist.com/images/20071222/5107CR1B.jpg

Page 23: MDST 3705 2012-03-05 Databases to Visualization

http://www.math.yorku.ca/SCS/Gallery/images/priestley.gif

Joseph Priestley's life-time graph of the lifespans of famous people. One of the first graphical time lines. Joseph Priestly, A Chart of Biography, 1765.

Page 24: MDST 3705 2012-03-05 Databases to Visualization

http://cartographia.files.wordpress.com/2008/05/minard_napoleon.png

Minard’s map

Page 25: MDST 3705 2012-03-05 Databases to Visualization

http://cartographia.files.wordpress.com/2008/05/minard-full.jpg

Page 26: MDST 3705 2012-03-05 Databases to Visualization

http://commons.wikimedia.org/wiki/File:Minard-carte-viande-1858.png

Page 27: MDST 3705 2012-03-05 Databases to Visualization

The difference is that information

visualizations reveal patterns in the data,

whereas info graphics use patterns to present a point or to present an

idea

Page 28: MDST 3705 2012-03-05 Databases to Visualization

Media Visualizations are not essentially reductive, and they use

color as much as space

Page 29: MDST 3705 2012-03-05 Databases to Visualization
Page 30: MDST 3705 2012-03-05 Databases to Visualization
Page 31: MDST 3705 2012-03-05 Databases to Visualization

Time Magazine covers between 1923 and 2009

Data points are the objects themselves

Color emerges as a key dimension

Sequencing -- "cultural time series"

Page 32: MDST 3705 2012-03-05 Databases to Visualization

What can you learn from this visualization?

Page 33: MDST 3705 2012-03-05 Databases to Visualization
Page 34: MDST 3705 2012-03-05 Databases to Visualization
Page 35: MDST 3705 2012-03-05 Databases to Visualization
Page 36: MDST 3705 2012-03-05 Databases to Visualization
Page 37: MDST 3705 2012-03-05 Databases to Visualization
Page 38: MDST 3705 2012-03-05 Databases to Visualization

A million manga pages

Page 39: MDST 3705 2012-03-05 Databases to Visualization
Page 40: MDST 3705 2012-03-05 Databases to Visualization
Page 41: MDST 3705 2012-03-05 Databases to Visualization

Rothko and Mondrian

Page 42: MDST 3705 2012-03-05 Databases to Visualization

Not all visualizations are information

visualizations in Manovich's sense ...

The following are “info graphics”

Page 43: MDST 3705 2012-03-05 Databases to Visualization
Page 44: MDST 3705 2012-03-05 Databases to Visualization

The Odyssey

Page 45: MDST 3705 2012-03-05 Databases to Visualization

The History of Science Fiction

Page 46: MDST 3705 2012-03-05 Databases to Visualization

Rebecca Black's "Friday"

Page 47: MDST 3705 2012-03-05 Databases to Visualization

What’s the big difference?

Page 48: MDST 3705 2012-03-05 Databases to Visualization

Information and media visualizations are generated algorithmically

Info graphics tend to be hand made creations (although they may

emulate algorithms)

The former exemplify Manovich’s principle that databases generate works – in this case, visualizations

Page 49: MDST 3705 2012-03-05 Databases to Visualization

Are information and media visualizations more truthful than

information graphics?

Page 50: MDST 3705 2012-03-05 Databases to Visualization

graphesis

Page 51: MDST 3705 2012-03-05 Databases to Visualization

graphesisInformation embodied in material form

Page 52: MDST 3705 2012-03-05 Databases to Visualization

graphesisOpposite of mathesis –Science, math as universal language

Page 53: MDST 3705 2012-03-05 Databases to Visualization

Think of the relationship between geometry and algebra

Database: Visualization :: Algebra : Geometry

Which is more real? Which depends on the other?

Page 54: MDST 3705 2012-03-05 Databases to Visualization

Can we imagine what a point is without visualizing it?

Is information separable from matter?

Page 55: MDST 3705 2012-03-05 Databases to Visualization

graphesisthe basis of mathesis

Page 56: MDST 3705 2012-03-05 Databases to Visualization

Media are always embedded in culture. Science was made possible by exact copy printing, a visual language (Ivins 1953)http://21st.century.phil-inst.hu/2002_konf/Nyiri/web_ivins.JPG

Page 57: MDST 3705 2012-03-05 Databases to Visualization

These images are both beautiful and effective

As digital scholars, our job is to learn how to read, review, and produce them

Page 58: MDST 3705 2012-03-05 Databases to Visualization

The theory of graphesis teaches us that images have an epistemology, or “cognitive style”

Page 59: MDST 3705 2012-03-05 Databases to Visualization

Paradoxes

• Computers are based on mathesis, or logico-mathematical thinking

• And visualization is based on computing• Ergo, mathesis precedes graphesis• But, mathesis rests on graphesis

– The iconography of mathematical symbols– The products of mathesis must always be

visualized with forms that have a rhetoric

Page 60: MDST 3705 2012-03-05 Databases to Visualization

http://oneparticularwave.files.wordpress.com/2006/11/escher.gif

Page 61: MDST 3705 2012-03-05 Databases to Visualization

All visualization involves transformation

Raw Data Data Models Queries Arrays Visual

Arrangements

Page 62: MDST 3705 2012-03-05 Databases to Visualization

The “final” transformation

• The visual product encodes a series of transformations from raw data to visual design

• A key element of this design is the use of space

• Space is complex—it involves the concepts of dimension, location, distance, and shape

• Each visualization uses these elements differently

Page 63: MDST 3705 2012-03-05 Databases to Visualization

What is transformation?

Review Examples

Page 64: MDST 3705 2012-03-05 Databases to Visualization

Patterns of Transformation (i)

• Image Grids (aka Image Graphs)– Purpose: Creates 2D qualitative space

• Space is uniform, Cartesian• “Points” are actually not atomic, but contain

content• Designed to show “hot spots”

– Method:• Identify X and Y in which to plot objects of type A• Create query to generate A, X and Y columns• Convert query data into 3D array $DATA[$X][$Y] =

$A• Convert array into HTML

Page 65: MDST 3705 2012-03-05 Databases to Visualization

htt

p:/

/stu

dio

1.s

han

ti.v

irgin

ia.e

du/~

rca2

t/data

est

heti

cs/0

3-2

9/v

4.p

hp

Page 66: MDST 3705 2012-03-05 Databases to Visualization

Patterns of Transformation (ii)

• Network Graphs– Purpose: Creates a network of relationships

• Space not uniform—distance and location of nodes require interpretation

– Method:• Identify nodes and principle of relationship (e.g.

container)• Create query to generate nodes and principle• Convert query into NODE and EDGE arrays• Convert arrays data into Cartesian Product for

each principle• Convert array into PNG, SVG, etc.

Page 67: MDST 3705 2012-03-05 Databases to Visualization

http://studio1.shanti.virginia.edu/~rca2t/dataesthetics/04-26/graph-main.php

Page 68: MDST 3705 2012-03-05 Databases to Visualization

Patterns of Transformation (iii)

• Adjacency Matrix – Purpose: Creates a 2D space

• But X and Y are “self similar”

– Method:• Identify X and Y• Create query to generate X and Y columns• Convert query data into 2D array• Convert array into HTML

Page 69: MDST 3705 2012-03-05 Databases to Visualization

htt

p:/

/stu

dio

1.s

hanti

.vir

gin

ia.e

du/~

rca2t/

data

est

heti

cs/0

4-2

1/e

x-0

4-p

viz

-matr

ix.p

hp

Page 70: MDST 3705 2012-03-05 Databases to Visualization

Patterns of Transformation (iv)

• Arcs and Circles– Purpose: Creates a 2D dimensions, with 1

dimension metric, the other not• Only an X axis with connections in qualitative

space

– Method:• Same as network graphs• Visualize using Protovis library

Page 71: MDST 3705 2012-03-05 Databases to Visualization

http://studio1.shanti.virginia.edu/~rca2t/dataesthetics/04-21/ex-04-pviz-arc.php

Page 72: MDST 3705 2012-03-05 Databases to Visualization
Page 73: MDST 3705 2012-03-05 Databases to Visualization

Patterns of Transformation (v)

• Hand-made– Purpose: Creates a free-form qualitative

space– Method:

• Draw!


Recommended