Mdst3703 visualization-2012-10-23

Visualization and the New Epistemology

Prof. AlvaradoMDST 3703/770323 October 2012

Business

• Midterms graded• Office hours– Tomorrow 11:00AM—3:00PM– Friday 1:00PM—3:00PM

• Project homework– Mark-up text for paragraphs and quotes– Quotes are SPAN elements with CLASS attributes

of either ‘quote’ or ‘extract’– Make sure file and directories are named properly

Review

• Web 2.0– Post-Google era of the web– Massive participation in social media– Social production of knowledge– New models of how knowledge is produced,

maintained, organized• Tags– One example of this shift– A new kind of knowledge “product”

A Delicio.us “folksonomy” visualized

A Flickr “folksonomy” visualized

Eric Fischer creates maps that merge geographic locations with geotagged photos from Flickr and tweets from Twitter. Red dots pinpoint the locations of Flickr pictures, blue dots show tweets, white dots mark places that have been posted to both. This map of Washington, D.C., shows messages concentrating around the national landmarks and power corridors of the city’s federal zone.

http://anthonyflo.tumblr.com/post/7590868323/photographer-and-self-described-geek-of-maps

An algorithm generates a virtual Rome in 3D from 150,000 Flickr Users' Photos

http://www.popsci.com/gear-amp-gadgets/article/2009-09/building-virtual-cities-automatically-150000-flickr-photos

Flickr Photos Yield Tourist Trails. An algorithm uses images from millions of tourists to suggest ways for visitors to spend their time.

http://www.technologyreview.com/computing/25549/page1/

Trends Map for #OWS

http://trendsmap.com

These visualizations are created out of “Big Data”

What is Big Data? What are some examples?

What is distinctive about the form of this kind of knowledge generated by Big Data?

Organic

Rhizomic

Socially generated

Transductive

What about the content of this kind of knowledge?

What does it tell us about what?

?

A new epistemology?

An new science?

(media determinism again)

Franic Bacon in 1620 described a new kind of knowledge based on observation and induction (empiricism). This view can be partly traced to the successes of exploration and instruments in learning about the world.

Anderson argues that a similar shift is happening now

With the era of the “cloud” and massive data

the Petabyte Age

comes a new kind of knowledge

The database is not just a symbolic form

It is the pervasive and standard form in which our knowledge is organized

Anderson

• The end of theory– Positivism (see definition)– It’s algorithms all the way down

• No need for models and causality– Correlation is enough

• More is different– The “Petabyte Age”– The sheer amount of data makes it valuable– Quality does not matter

Some Definitions

• Petabyte (PB) = 250

1,125,899,906,842,624 bytes1,024 terabytes

• Positivism (my definition)– A theory of knowledge that views physical laws and

models as more or less stable patterns– Regards statistics and pattern recognition as more

authentic forms of knowledge than laws– Radically empiricism (nothing “behind” the

observed)

Google does not care about what is on a page, it just cares about this

The Page Rank algorithm visualized

Same approach to advertising

“AdWords analyzes every Google search to determine which advertisers get each of up to 11 ‘sponsored links’ on every results page. It’s the world’s biggest, fastest auction, a never-ending, automated, self-service version of Tokyo’s boisterous Tsukiji fish market, and it takes place, Varian says, ‘every time you search.’ ”

http://www.wired.com/culture/culturereviews/magazine/17-06/nep_googlenomics

Steven Levy, “Secret of Googlenomics: Data-Fueled Recipe Brews Profitability,” WIRED 17.06.

It’s all about the algorithm

There is no real theory behind the formula

It just happens to work

Sometimes this approach is called “the physics of clicks”

Manovich’s experimentsexplore this concept

(examples from Mapping Time Exhibit)

http://www.flickr.com/photos/culturevis/sets/72157624959121129/detail/

Time Magazine 1923—2009

Science and Popular Science Magazines

1872-1922

Anna Karenina

This visualization of Anna Karenina is inspired by a common reading practice of underlining important lines and passages in a text using magic markers. To create this visualization we designed a program that reads the text from a file and renders it in a series of columns running from top to bottom and from left to right as a single image it also checks whether text lines contain particular words (this version checks for the word Anna) and highlights the found matches.

Manga Style SpaceEN

TRO

PY

VARIATION

MONDRIAN ROTHKO

13 years of data for eachX: BrightnessY: Saturation

ImagePlot of Vertov’s film, The Elevent Hour

BRIGHTNESS

NU

M S

HAP

ES

Visualization

Algorithm

Big Data

Visualizing Text

Co-presence of characters in Les Miserables

Same data, different display algorithm