ICAM130/VIS149 spring 2008: Contemporary Computer Topics
Visual Arts Department | UCSD

The syllabus for this class is online at www.manovich.net/
As the class progresses, the additional materials will be added to the class web site.

instructor: Dr. Lev Manovich
office: Visual Arts Facility (VAF) 553
office hours: by appointment
email: manovich@ucsd.edu


Readings:
All readings for this class will be available online at no charge.

Topic: Visualizing Cultural Patterns


Class Description:

Can we create quantitative measures of cultural innovation? Can we have a
real-time detailed map of global cultural production and consumption? Can we
visualize flows of cultural ideas, images, and trends? Can we visually represent
how cultural and lifestyle preferences – whether for ideas, music, forms, designs, or
products – gradually change over time?

In this decade we see a growing body of projects which visualize cultural content,
cultural flows, and social networks. People who create such visualizations come
form many fields: design (for instance, Media Lab’s alumni Ben Fry), media
design (Imaginary Forces’s visualization of the paintings in MOMA collection
commissioned by MOMA for its lobby), media and software art (for instance,
George Legrady’s visualization of books’ flow in Seattle Public Library
commissioned by the library; Listening Post installation by Mark Hansen and Ben
Rubin), computer graphics, and computer and information science.

These visualizations share certain limitations, which we will try to overcome in our class.
They typically rely on existing meta-data, and do not look “inside the
data.” We will attempt to visualize sets of cultural data based on the descriptions of the content and form (which can be combined with existing metadata).
The descriptions can be generated either manually or by software via automatic analysis.

In order to generate the descriptions of formal properties of cultural objects, we need to first figure out what they are.
In the 1920s Bauhaus and other centers for modern art and design have developed analysis of formal resources
and grammars of visual and spatial compositions;
and, throughout the twentieth century, filmmakers, architects, and later academics working in
film theory / architecture theory have provided similar analysis for cinema, architecture, literature, and other areas of culture.
However, since the adaptation of software in all creative fields in the 1990s, a multitude of new
visual, spatial, and material forms have emerged. Their development was so fast that theory has often lagged behind.
And while it is possible to find descriptions of formal resources in some new areas if we look at professional publications (textbooks, catalogs of best works)
these publications are usually not consulted by cultural critics.

Consequently, before we can analyze and visualize patterns in many contemporary cultural areas, we need to develop theoretical understanding
of their new means of expression. This will be the second goal of our class: developing vocabularies of the visual/spatial dimensions in new cultural areas
(such as motion graphics).

Note that this theoretical task and the building practical visualizations go hand in hand.
We can test our hypothesis about relevant dimensions by visualizing their use in a particular data set -
which then can lead us in turn to look at the data set again and to think about other dimensions which may be more relevant.
In a similar fashion, we can overlay other data on our visualizations (social, technological, economic, historical)
and test which data is relevant.

Requirements:

1.Consistent class attendance. Class attendance will be taken every class - at different times. You are allowed to miss one class meeting without an excuse. Missing any additional classes without proper excuse (doctor's notice) will lower your final grade half a letter grade for each class missed. Chronic lateness counts as absence. Forgetting to sign the attendance sheet or leaving early counts as absence.

2. Reading the assigned materials before each class meeting. If any additional online resources are assigned, you should go though them them before the lecture as well.

3. Timely completion of the assignments.

4. Individual practical project(s) which needs to be completed on time - will be judged on:
(1) is it visually compelling?
(2) does it fit with the class goals, i.e. does it reveal something new about culture which is not already obvious or known (as opposed to just being a cool visualization)?
(3) is is technically competent?

5. Participation in a group project which will be judged using the same criteria as individual projects.

6. Active participation in the discussions and critiques.

grading:
1. The assignments: %25
2. Individual project(s): %25
3. Group project: %50

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PROJECTS DONE LAST QUARTER IN THIS CLASS:

individual projects done in ManyEyes

group projects:

sNews
lyirical language:

offline vs. online
sharedegg

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SOFTWARE:

We will use ManyEyes and/or Google Spreadsheet charts/gadgets webware for individual projects.
You can also use this webware for you group project if you like.


examples of Google docs charts

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SELECTED RESOURCES

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SCHEDULE:


1. April 1.
Class introduction.

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2. April 8.
Artistic work in info visualization.

Conceptual background for Cultural Analytics.


Reading assignments:

If you are new to info vis:
Wikipedia "visualization" article

visit as many projects as you can linked at:
VisualComplexity
Infoaesthetics


for everybody:

read (and check out linked projects):
Andrew Vande Moere, Infosthetics: the beauty of data visualization

Fernanda B. Viégas and Martin Wattenberg: Artistic Data Visualization: Beyond Visual Analytics


Watch Hans Rosling TED Talk (all) and play with Gapminder software and data


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3. April 14.
Discussion of the completed individual projects and strategies for group projects.

Cultural Analytics: study and visualization of cultural patterns using large data sets.
Example of the recently emerged cultural area which has not been much discussed or analyzed: motion graphics.


Ongoing assingment:
while you have specific assingments for each class (see below), you are also expected to go through and visit all recources collected in my selected online resources page. The faster you do it, the more efficient will be your work in this course!

Viewing assingment:
browse through as many projects as you can on Infoaesthetics

Reading assinments:

wikipedia: Theories of Post-industrial society
wikipedia: design - specifically, look at the list of "Design disciplines" and click on the links for all disciplines you dont know about.
wikipedia: critical design

Manovich: Cultural Analytics proposal (2007). Please visit all projects linked in the text.
Manovich: Understanding Hybrid Media (2007)
.


Individual Project 1:

select (or generate) a cultural data set and create one (or more) visualizations of it using ManyEyes.
Please add your projects in icam130_spring_2008 topic hub.
Name your data set as follows: lastname_dataset_1.
Name your visualization as follows: lastname_project_1.
Label your axies appropriately so somebody can understand your visualization without you being there to explain.

As a minimum, your visualizaton should be meaningful - i.e., it should show trends in your data set which we can't see by looking at data directly.
Ideally, your visualization should reveal something new about culture (past or present) which is not already obvious or known.

Note: the key to creating succesful visualization is to carefully read "data requiremens" for your selected visualization type.

 

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4. April 28.
Quantitative and graphical analysis of cultural data: examples from the humanities.
Contemporary approaches for the analysis of large data (text): data mining / web and social media mining.


Ongoing assingment:
while you have specific assingments for each class (see below), you are also expected to go through and visit all recources collected in my selected online resources page. The faster you do it, the more efficient will be your work in this course!

Reading assingments:

Warren Buckland: statistical style analysis
(look around cinemetrics site and check out all other papers.)


Judith Donath: designing sociable media (spring 2008 class syllabi)

(also look at MIT social media group stuff)


Action assingments:

If you use Last.fm - plot your your musical listening history @ LastGraph

play with Google trends and blogscope

Cloudalicious: enter diffirent URLs to see how they were tagged on del.icio.us over time.
(optional for technically-minded students: read Tagclouds and cultural changes - analyis of results which can be obtained with Cloudalicious.)

Blogpulse: play with all publically available tools (Trend Search, Featured Trends, Conversation Tracker, BlogPulse Profiles)

Play with like.com


Viewing assingments:


use of visualization in Obama compaign: www.barackobama.com/resultscenter/

example of the use of animated chart in Google Docs spreadsheet (yes, you can also use it for your projects)

Nielson BuzzMetrics (look at Solutions and Approach)

MIT Reality mining (note: currently N. Eagle is directing a new similar project in India which involves tracking 100,000 people.)
(optional: read
Nathan Eagle and Alex (Sandy) Pentland: Reality Mining: Sensing Complex Social Systems, 2007.)



Examples of research labs working on data mining/ social media analysis:

data mining (the Automated Learning Group)
HP Social Computing Lab
also take a look at the list of all HP labs
Nielsen BuzzMetrics white papers

Microsoft Social Computing Group

quote: "The next decade will produce a revolution in the use of archived, simulation, and near real-time data to guide future decisions and research directions."


Examples of research publications and conferences in these areas:

Akshay Java , UMBC

International Conference on Weblogs and Social Media 2008: papers / program
Mapping the Blogosphere
Data Mining: Text Mining, Visualization and Social Media (blog)


For technically minded: A recent book on design of Web 2.0 applications - look at the TOC

NOTES FOR GROUP PROJECTS

In deciding if your idea for a group project is valid or if you need to rethink it, my main criteria are "will you project tell us something new and interesting about contemporary culture which we don't know?" and "what is research question which your project is designed to answer"?

Remember that the title of the class is "Visualizing Cultural Patterns" - so this is what your project should be doing.

If your project deals with the actual cultural objects (paintings, photography, films, computer games, videos, interiors, products, buildings, etc.), your methodology has to include some analysis of the content of cultural objects - as opposed to only using existing metadata. (The examples of such projects are 1, 2 and 3 below).

Your project should start with an in testing research question - rather than on available data. Below are examples of such research questions. (You will find more examples in my Cultural Analytics proposal, so you may want to look at it again.)


Examples of projects which analyze the contents of a set of cultural products:

(1) "are there any differences today between portfolios of designers (in a particular field) from different countries? If so, how significant are these differences? How did this changed over last 10 years?" (These examples refers to portfolios on coroflot.com. You can ask these questions in relation to any other area of culture production or discussion - student blogs of architectural schools collected at archinect.com, short films on vimeo, etc.)

(2) "if we describe contemporary motion graphics (or any other art/design field) works using a number of attributes, what patterns can we observe if we sample a large number of works? Do some attributes tend to occur together? Are there any significant differences between the works in different areas as they are specified on xplsv.tv - commercial, experimental, VJ live, etc?". (These questions can be also asked in relation to any other art/design field).

(3) "if we graph the gradual simplification of forms in European art of the end of the nineteenth and early twentieth century which eventually lead to pure abstraction, what patterns can be observe? Will we see a linear development (i.e. a strait line) or will we see some jumps, accelerations, etc.? Will these patterns be different for different arts and media (i.e., painting, furniture, decorative arts, architecture)? (This question can be also asked in relation to any other cultural development in media and arts - for instance, development of contemporary styles of music, etc.)


Examples of projects which look at patterns in the development of cultural institutions, cultural preferences, and ideas:

(4) "what geopolitical patterns would we see if we map the growth of art museums (or: art biennials, design biennials, fashion works, film festivals, design schools, university programs in media, university majors for new subjects, publications in art history, articles on media art, etc.) around the world over last 5 (7, 10, etc.) years?"


(5) "If we look at new cultural concepts (or selected set of concepts) which emerged in this decade, how much attention and "mindshare" these concepts have captured relative to each other? To answer this question we will analyze Wikipedia pages for these concepts. We will use the dates when the pages were established and also compare how much and how frequently people contributed to each page.


 

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4. May 6.
Culture Visualization: emerging genres.
We will continue looking at different examples of projects in culture visualization linked under "selected visualizations of cultural processes" in resources page.

Ongoing assingment:
while you have specific assingments for each class (see below), you are also expected to go through and visit all recources collected in my selected online resources page. The faster you do it, the more efficient will be your work in this course!

Viewing / Reading assingments:
Ben Rubin and Mark hansen: Listening Post / video of the installation (look also at other videos of this installation at youtube.com) / moveable typ installation
Lev Manovich: Data Visualisation as New Abstraction and Anti-Sublime, 2002

Golan Levin: Dumpster - project (2006)
Lev Manovich: Social Data Browsing - text about the project (2006)


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INSTRUCTOR's NOTES