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Visualizing Data (Kape + Teknolohiya Version)

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This version I gave during a January 2009 Kape + Teknolohiya at the TechnoHub-AyalaTBI, is taken from the original lecture I gave at UP Open University: http://www.slideshare.net/diegomaranan/20080718mms100lecturecolloquiumpresentation
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Visualizing Data: Making Sense of an Information-Rich World Diego Maranan [email protected] Faculty of Information and Communication Studies UP Open University Visualization of del.icio.us tags is courtesy of kaeru on Flickr.com and is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.0 Generic license. I assert that any use of copyrighted images in this presentation constitutes acceptable use because they are low-resolution copies, do not limit in any way the copyright owners to sell the images or products they represent, are identified and referenced clearly, and are used only to illustrate arguments central to this presentation. Non-copyrighted portions of this presentation are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Philippines License.
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Page 1: Visualizing Data (Kape + Teknolohiya Version)

Visualizing Data: Making Sense of an Information-Rich World

Diego [email protected] Faculty of Information and Communication Studies UP Open University

Visualization of del.icio.us tags is courtesy of kaeru on Flickr.com and is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.0 Generic license. I assert that any use of copyrighted images in this presentation constitutes acceptable use because they are low-resolution copies, do not limit in any way the copyright owners to sell the images or products they

represent, are identified and referenced clearly, and are used only to illustrate arguments central to this presentation.Non-copyrighted portions of this presentation are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Philippines License.

Page 2: Visualizing Data (Kape + Teknolohiya Version)

Visualizing Data: Making Sense of an Information-Rich World

Diego [email protected] Faculty of Information and Communication Studies UP Open University

Visualization of del.icio.us tags is courtesy of kaeru on Flickr.com and is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.0 Generic license. I assert that any use of copyrighted images in this presentation constitutes acceptable use because they are low-resolution copies, do not limit in any way the copyright owners to sell the images or products they

represent, are identified and referenced clearly, and are used only to illustrate arguments central to this presentation.Non-copyrighted portions of this presentation are licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Philippines License.

Biomodd [LBA2]Ecology + Gaming + Installation Art + Community

Interested?

www.biomodd.net

`

THIS IS AN ADVERTISEM ENT

Page 3: Visualizing Data (Kape + Teknolohiya Version)

A quick backgrounder on meGrowing up, I wanted either to compose film music or study the cosmos. In college, I

became a computer geek who studied contemporary dance.

Art, science, and positive social change have always been important to me.www.diegomaranan.com/CV

Page 4: Visualizing Data (Kape + Teknolohiya Version)

IN TER R UP T T HI S

TA L KAT

A N Y T IM E

(I don't mind)

Page 5: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 6: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 7: Visualizing Data (Kape + Teknolohiya Version)

data visualization isa particular way of doing

information design

Page 8: Visualizing Data (Kape + Teknolohiya Version)

“ Information design tells a story with pictures.

It can tell “how many?” “when?” or “where?”

It can show trends over time, compare elements or reveal hidden patterns.

It brings form and structure to information.

It is not the same as graphic design, nor is it only about making something aesthetically pleasing.

It is not about branding, style, making a glossy product or something that looks “corporate.”

From John Emerson. (2008, January). Visualizing Information for Advocacy: An Introduction to Information Design. Tactical Technology Collective. Retrieved June 6, 2008, from http://www.tacticaltech.org/infodesign Visualizing Information for Advocacy: An Introduction to Information Design is licensed under a Commons Attribution-Share Alike 3.0 License.

Page 9: Visualizing Data (Kape + Teknolohiya Version)

From John Emerson. (2008, January). Visualizing Information for Advocacy: An Introduction to Information Design. Tactical Technology Collective. Retrieved June 6, 2008, from http://www.tacticaltech.org/infodesign Visualizing Information for Advocacy: An Introduction to Information Design is licensed under a Commons Attribution-Share Alike 3.0 License.

“ Clear

It makes complex information easier to understand.

Compelling

Visuals grab people’s attention.

Convincing

People who might not be persuaded by raw numbers or statistics may be more likely to understand and believe what they see in a chart or graphic.

Page 10: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 11: Visualizing Data (Kape + Teknolohiya Version)

The US news media dedicates a disproportionate amount of attention to

stories about the US and Iraq.

Alisa Miller. (2007). Why we* know less than ever about the world, TED2008. Monterey, California. Retrieved July 11, 2008, from www.ted.com/index.php/talks/alisa_miller_shares_the_news_about_the_news.html. * “we” = “Americans”, of course.

The world map redrawn according to the number of seconds US network and cable news organizations devoted to news items for each country in February 2007.

Page 12: Visualizing Data (Kape + Teknolohiya Version)

In 2006, only the US, the UK, and Israel did not support “an immediate cessation of hostilities in the Middle East.”

Belfast Telegraph (2006, July), reproduced by John Emerson in Visualizing Information for Advocacy: An Introduction to Information Design. (2008, January). Tactical Technology Collective.

Page 13: Visualizing Data (Kape + Teknolohiya Version)

Between August and September 2007, over 60 demonstrations were staged

across Myanmar in response to oppressive state policies.

Alternative ASEAN Network on Burma. Map of demonstrations August-September 2007 - ALTSEAN Burma. ALTSEAN-BURMA. Retrieved July 15, 2008, from http://www.altsean.org/Photogalleries/ProtestsMap.php.

Details of each demonstration are filed on Google Maps.

Page 14: Visualizing Data (Kape + Teknolohiya Version)

The US is the leading an economic superpower.

Froz Gobo. (2007, June 27). Much Better. apostropher.

Retrieved July 14, 2008, from http://www.apostropher.com/blog/archives/003827.html. See also http://strangemaps.wordpress.com/2007/06/10/131-us-states-renamed-for-countries-with-similar-gdps/

The names of US states have been replaced with countries that have similar GDPs.

Page 15: Visualizing Data (Kape + Teknolohiya Version)

The Israel-Palestine conflict is long and complex. It is made up of countless individuals who

each have a story to tell.

Just Vision. Timeline. Just Vision. Retrieved July 15, 2008, from http://justvision.org/en/timeline.

An interactive and “subjective history of the Israeli-Palestinian conflict composed of historical and personal events” as recounted by participants of the project.

Page 16: Visualizing Data (Kape + Teknolohiya Version)

Every community defines a concept in its own way.

UP Open University. "What is Multimedia?" MMS100: Introduction to Multimedia Studies (1st Semester, 2008). Retrieved July 14, 2008, from http://sites.google.com/a/upou.edu.ph/mms100/course-outline/sfg987srtew4rtf/whatismultimediaresults.

Page 17: Visualizing Data (Kape + Teknolohiya Version)

There's a lot of heartache out there.Golan Levin, Kamal Nigam, & Jonathan Feinberg. (2006, February 14). The Dumpster. Retrieved May 3,

2008, from http://www.tate.org.uk/netart/bvs/thedumpster.htm.

`

When it happened

Someone blogging

about getting dumped

How they felt about it

(Generally, not good)

whoa

Page 18: Visualizing Data (Kape + Teknolohiya Version)

Powerful interests are connected through complex networks of influence that significantly affect US public policy

around climate change.

Users can construct their own maps by placing, removing, and rearranging institutions and individuals associated with claims that anthropogenic climate change is not a cause for concern. The interface allows users to explore for themselves relationships between the petroleum industry, various think tanks, and the US government.

Greenpeace. Exxon Secrets. Exxonsecrets.org. Retrieved July 14, 2008, from http://www.exxonsecrets.org/maps.php.

Page 19: Visualizing Data (Kape + Teknolohiya Version)

The world is increasingly connected.

Walter Rafelsberger. (2008). Twitter Conversations Map. visualcomplexity.com. Retrieved July 15, 2008, from http://www.visualcomplexity.com/vc/project_details.cfm?id=600&index=600&domain=.

“This visualization [...] using Processing shows the conversations of about 1500 users from the microblogging service Twitter. The arcs [...] link the locations of users who talk to each other. The geocoding was done filtering location info from the users profile pages and looking it up with Geonames.”

Page 20: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 21: Visualizing Data (Kape + Teknolohiya Version)

`

Interactive

PERMITS GRADUAL DISCLOSUREGOOD FOR UNCOVERING COMPLEXITYUSERS ARE IN CONTROL OF THEIR LEARNINGDESIGN SHOULD IMPLY PROMISE OF NEW DISCOVERIESGENERALLY REQUIRES MORE SOPHISTICATED AUTHORING

TOOLSGENERALLY MORE DIFFICULT TO MAKE

Non-interactive

INSTANTANEOUS LEARNING GRATIFICATIONSUITABLE FOR SIMPLIFYINGDESIGNER CONTROLS DISCLOSURE OF INFORMATIONMORE CONVENTIONAL AUTHORING TOOLS ARE USUALLY

SUFFICIENTGENERALLY EASIER TO MAKE

USER INTERACTIVITY

Page 22: Visualizing Data (Kape + Teknolohiya Version)

`

Very large or very small values

Unexpected relationships

Unusual statistical distributions

WHAT THEY REVEAL

Page 23: Visualizing Data (Kape + Teknolohiya Version)

`

Data changes over time USER-GENERATED CONTENTSYSTEMS THAT CONTINUOUSLY AND AUTOMATICALLY GENERATE DATA

Data remains fixed

DATA SOURCES

Page 24: Visualizing Data (Kape + Teknolohiya Version)

`

Desktop publishing programsMS WORD, MS EXCEL, OPEN OFFICE

Image editing and layout softwareADOBE PHOTOSHOP, ADOBE INDESIGN, COREL

Web 2.0 tools aimed for “average” web userGOOGLE MAPS, MANY EYES

Specialized design tools FLASH, COURSELAB, SOCIAL ACTION

Highly specialized, highly flexible visualization authoring toolsPROCESSING, VVVV, VTK

TOOLS USED TO AUTHOR THEM

Page 25: Visualizing Data (Kape + Teknolohiya Version)

Can represent data that changes over time

Draws reader in through the power of design: “It must be

important”

Interactivity supports user-centered learning

Mapping Glovalization Projecthttp://qed.princeton.edu/main/MG

Page 26: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 27: Visualizing Data (Kape + Teknolohiya Version)

The Internet on Jan 16, 2005www.opte.org

Page 28: Visualizing Data (Kape + Teknolohiya Version)

Social Networks (1)

Social networking

My facebook networkgenerated using http://nexus.ludios.net

Page 29: Visualizing Data (Kape + Teknolohiya Version)

Social Networks: Linking Subgroups in my network

Page 30: Visualizing Data (Kape + Teknolohiya Version)

orphaned nodes and subgroups

nodes connecting subgroups

Page 31: Visualizing Data (Kape + Teknolohiya Version)

Developed at the Human-Computer Interaction Lab at University of Maryland

Simultaneously presents statisical analysis alongside social network analysis graph1

SNAs can be used to examine power relations2

Screenshot from http://www.cs.umd.edu/hcil/socialaction [1] Adam Perer, & Ben Shneiderman. (2008). Integrating Statistics and Visualization: Case Studies of Gaining Clarity during Exploratory Data Analysis. In Proceedings of the ACM Conference on Human Factors in Computing Systems. Florence, Italy. [2] e.g., Padgett, J. F., & Ansell, C. K. (1993). Robust Action and the Rise of the Medici, 1400-1434. American Journal of Sociology, 98(6), 1259.

Social network analysis

Page 32: Visualizing Data (Kape + Teknolohiya Version)

(SocialAction... in action.)

Page 33: Visualizing Data (Kape + Teknolohiya Version)

Open Source Dancehttp://www.slideshare.net/diegomaranan/open-source-dance-presentation/

Building dance communities through sharing Creative Commons-licensed choreography and tracking the flow of choreographic ideas across dance communities

Page 34: Visualizing Data (Kape + Teknolohiya Version)

Visualizing Philippine Cinemahttp://www.slideshare.net/diegomaranan/proposal-for-a-portal-to-philippine-cinema-using-data-visualization-

techniques-presentation/

Facilitating insights into independent cinemas in the Philippines (but can be extended easily to cover global cinemas) using data publicly available on the web and data visualization techniques

Page 35: Visualizing Data (Kape + Teknolohiya Version)

The Apology Projecthttp://sites.google.com/site/diegomarananprojects/todo/on-hold/The-Apology-Project

A Web 2.0 platform for public apologies

Page 36: Visualizing Data (Kape + Teknolohiya Version)

Open Source DanceThe Apology Project

Visualizing Philippine Cinema

ANOTHERADVERTISEM ENT

Web developers needed!

Page 37: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 38: Visualizing Data (Kape + Teknolohiya Version)

Visualizing data is not an unproblematic activity.

Page 39: Visualizing Data (Kape + Teknolohiya Version)

Methods used

IN GENERATING AND COLLECTING DATA,

IN CHOOSING APPROPRIATE VISUAL ELEMENTS,

OR IN DISSEMINATING A VISUALIZATION

can be subject to debate.

Page 40: Visualizing Data (Kape + Teknolohiya Version)

● Data visualization assumes the presence of data● Broad strokes might miss important details (which

is why interactivity is important)● All the visual cleverness might eventually become

tiring. (“I'm skeptical of shapes.”)

Page 41: Visualizing Data (Kape + Teknolohiya Version)

But work in data visualization can be an interdisciplinary activity, where experts

IN DESIGN,

IN EDUCATION,

IN SOCIAL SCIENCE,

AND IN TECHNOLOGY

contribute best practices in the spirit of free inquiry, openness, and trust.

Page 42: Visualizing Data (Kape + Teknolohiya Version)

Visualizing data is not an unproblematic activity.

But that's OK.

Page 43: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 44: Visualizing Data (Kape + Teknolohiya Version)

Tons of examples on www.visualcomplexity.com and processing.org/exhibition

Page 45: Visualizing Data (Kape + Teknolohiya Version)

● Collaboration and Productivity, Onboarding, Training● Archiving● Basic Education● Raising the cool factor of your web presence● Maximing your investment on the web presence by

understanding user behavior on your website● Grassroots advocacy, activism, information

campaigns● Personal use: Coping with information overload● ++

Page 46: Visualizing Data (Kape + Teknolohiya Version)

When you want to say something radically different, or when you uncover information that is potentially dangerous to the status quo,

say what you want to say in the most aesthetically stunning, quantitatively sound way possible.

Page 47: Visualizing Data (Kape + Teknolohiya Version)

What data visualization isExamples: 1

General FeaturesExamples: 2

CaveatsExamples: 3Now what?

some older examplesso we can make sense of it allnetworks

what's in it for you

Page 48: Visualizing Data (Kape + Teknolohiya Version)

1) Join the Information Design for Social Change email list.groups.google.com/group/disenyo

2) Try it yourself. Graph your social network on Facebook on www.nexus.ludios.net. Or try out Many Eyes: www.manyeyes.alphaworks.ibm.com/manyeyes

3) Read up more about it on the Web: www.delicious.com/dmaranan/visualization

4) Read books and journal articles about data visualization:wednesdaysmnlove.blogspot.com/2008/10/list-of-readings.html

5) Go to a school that teaches you more about it.Look for buzzwords like Aesthetic Technologies, Computational Aesthetics, Computational Design, Information Design

Page 49: Visualizing Data (Kape + Teknolohiya Version)

“Good art renders the invisible, visible.”


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