Flickr group to upload visualizations
ttp://www.flickr.com/groups/culture_viz/
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VIS 242| Winter 2008: Theories of Media and New Media
Visual Arts Department
| UCSD
TIme: Wed. 9a-11:50a
Location: MAN 212-Seminar Room
The syllabus for this class is online at www.manovich.net/
As the course progresses, the additional materials will be added to the course web site.
instructor: Dr. Lev Manovich
office: Visual Arts Facility (VAF) 553
office hours: after this class (i.e., from 3pm onward on Wednesdays, by appointment
email: manovich@ucsd.edu
Readings:
All readings for this class will be available online at no charge.
TOPIC FOR WINTER 2009:
Information Visualization, Social Media, Cultural Analysis
Class background:
White paper and Keynote presentation which describes in detail the ideas leading to this class.
Examples of cultural analytics work done by Software Studies Initiative.
Resources: culturevis.com
Course description:
In this class we will explore some of the key trends and concepts in contemporary culture, media, and technology which all emerge (or become visible) since the late 1990s. These trends can be divided into 3 clusters (see the list below). In parallel, we will conduct original cultural research using some of the same tools and techniques which we will discussing theoretically. (The methodology for this research called Cultural Analytics is being currently developed by Software Studies Initiative UCSD - see "Practical work: background" section below.)
The concepts and trends to be discussed in class (divided into 3 clusters):
cluster 1:
data mining
information growth
the new scale of cultural production (pro and pro-ams)
web 2.0
semantic web
social media
long tail
user-generated content
folksonomy
crowd sourcing
cluster 2:
scientific visualization
visual analytics
information visualization
information design
image processing / computer vision
computational photography
new design disciplines emerging in the second part of the 1990s
critical design
motion graphics
cluster 3:
digital humanities
traditional methods of cultural criticism vs. quantitative cultural analysis
software studies
cultural analytics
Practical work: background:
In 2007 Lev Manovich (Visual Arts, UCSD) and Noah Wardrip-Fruin (Communication, UCSD) have set up Software Studies Initiative at University of California, San Diego (UCSD) and California Institute for Telecommunications and Information (2007). Together with the researchers and students working in our lab, we have been developing a new paradigm for the study, teaching and public presentation of cultural artifacts, dynamics, and flows. We call this paradigm Cultural Analytics.
Today sciences, business, governments and other agencies rely on computer-based analysis and visualization of large data sets and data flows. They employ statistical data analysis, data mining, information visualization, scientific visualization, visual analytics, and simulation. We proposes to begin systematically applying these techniques to contemporary cultural data. The large data sets are already here – the result of the digitization efforts by museums, libraries, and companies over the last ten years (for instance, Google Books, www.artstor.org and archive.org) and the explosive growth of newly available cultural content on the web. (For instance, as of November 2008, Flickr had 3 billions of images – together with tags created by users and other metadata automatically logged by Flickr servers).
We believe that a systematic use of large-scale analysis and interactive visualization of cultural data will become a major trend in humanities research in the coming decades. The same can be argued for the analysis and visualization of the social processes that underpin cultural production. What will happen when humanists start using interactive visualizations as a standard tool in their work, the way many scientists do already? If slides made possible art history, and if the movie projector and video recorder enabled film studies, what new cultural disciplines may emerge out of the use of interactive visualization and data analysis?
In April 2008, exactly one year later we founded Software Studies Initiative, NEH (National Endowment for Humanities, the main federal agency in the U.S. which provides grants for humanities research) announced a new “Humanities High-Performance Computing” (HHPC) initiative that is based on the similar insight:
“Just as the sciences have, over time, begun to tap the enormous potential of High-Performance Computing, the humanities are beginning to as well. Humanities scholars often deal with large sets of unstructured data. This might take the form of historical newspapers, books, election data, archaeological fragments, audio or video contents, or a host of others. HHPC offers the humanist opportunities to sort through, mine, and better better understand and visualize this data."
In December 2007 NEH awarded us Humanities High Performance Award to use Department of Energy (DOE) Supercomputers to analyze and visualize patterns in large sets of visual media.
Practical work: goals and tools:
Based on the already completed case studies done in our lab, in this class we will continue developing analytical and visualization techniques appropriate for working with stilt and time-based visual media such as visual art, photography, fashion/street styles, feature films, animation, motion graphics, use-generated video, videos of game play. The work in this class will allow us to process massive amounts of such material on DOE supercomputers - something which was never done before. We will also have access to state of the art supervisualization system at Calit2 (HIPerSpace) to display class projects.
The tools used in the class include ImageJ open-source image processing software, Google Docs, Excel, and other applications.
One of the goals of this class is to explore how the community-assigned semantic descriptions of media artifacts can be combined with automatic computer analysis of their visual structure.
Therefore, some of our practical work will involve discussing the ways of assigning these descriptions and then working collaboratively to describe sets of cultural artifacts.
Class structure includes a few different formats: individual assignments, working in groups, and work with all other students in class in a coordinated fashion.
Students will be evaluated both on their individual work and on their contribution to group projects.
Practical work: timeline:
In the first part of the course we will be all working together on the same cultural material. Our goals are 1) to get comfortable with the tools and methods for quantitative analysis and visualization; 2) to push Cultural Analytics further by combining our collective insights and expertise.
In the second part of the class the students will have a choice: they can continue working on the same cultural material, or they can form groups which will use the tools and methods the students learned so far to analyze different types of cultural artifacts.
This class is a research seminar where the students will be involved in the original research program which was never undertaken before.
Therefore, I am not providing a detailed week-by-week schedule of the practical work in this class: what we will do next will be determined by our progress up to that point.
Practical work: credit system:
This class will follow the approach and the credit system which is more close to the science than the traditional humanities. Instead of writing individual course papers (which are usually never published and therefore do not end on students' CVs), we will engage in collaborative research projects which will lead to publications.
Similar to the sciences, we will also use a systematic approach to giving the students credit for their participation:
1.The students will be credited in any publications and public/web presentations which result from the work conducted in this class.
2. Consequently, students can also list all publications which use the research which was conducted in this class (in which a student was directly involved in)on her/his CV.
3. The work done in this class can also potentially lead to joint publications between the instructor and the students with student's listed as co-authors on the papers.
Requirements:
1.Consistent class attendance.
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.
2. Reading the assigned materials before each class meeting. If any additional online resources are assigned, you should go through them before the class meeting as well.
3. Timely completion of the individual assignments.
No late assignments will be accepted.
4. Timely completion of the group assignments.
No late assignments will be accepted.
If the group does not complete its assigned work on time, all group participants will be penalized equally.
5. Participation in a group project. The project will be judged using the following criteria:
(1) is it visually compelling?
(2) is it meaningful and original, i.e. does it reveal new cultural patterns which are not not already obvious or known?
(3) is is technically competent?
More detailed information and requirements for the group projects will be provided later in the quarter.
Grading:
Each component of the class (1-5) is equally important and will be counted equally in determining the final grade.
TOPICS AND READINGS:
(Yes, of course, it is likely to change. I will fill in readings as the quarter progresses):
1/ January 8
class introduction:
data mining / the new scale of cultural production / cultural analytics
2/ January 15
social media / metadata, humanities vs. science - research and publication cultures /
traditional cultural criticism vs. qualitative cultural analysis / basic research methods in humanities
3/ January 22
selecting - describing - measuring /
describng cultural artifacts: experts, athuors, users, computers /
traditional cultural criticism vs. qualitative cultural analysis /
taxonomy, folksonomy, user-generated tags, and other classification concepts /
image processing: history, applications, use in cultural analysis
read carefully (you can skip more technical parts):
metadata
folksonomy
Folksonomies and Tags
taxonomy
Clay Shirky: Ontology is Overrated. 2005.
browse:
visualization
wikipedia: controlled vocabulary
Steve.museum
knowledge management
knowledge representation
John Unsworth. Scholarly Primitives: what methods do humanities researchers have in common, and how might our tools reflect this? (2000)
4/ January 29
social media / user-generated content / long tail: concepts, tools, applications
this just in:
Where Computer Science and Cultural Studies Collide. The Chronicle of Higher Education. January 23, 2009.
browse: a syllabus for a class similar to spirit to ours:
Alan Lu. Literature+ | UCSB | 2008
read carefully (you can skip more technical parts):
Social Media: Paradigm Shift?
Mass_collaboration
The Long Tail
Perceptual mapping
view: all projects/resources - listed under
visualizing social media
tracking popularity
browse:
Metadata? Thesauri? Taxonomies? Topic Maps! - Making sense of it all
Digital_repository
social network
data mining
web mining
Companies that Measure Social Media, Influence, and Brand
Open Directory Project (the largest directory of websites put together by human editors - an interesting example of a contemporary taxonomy)
optional:
Wikipedia
Cris Anderson, The Long Tail (the original 2004 Wired article)
5/ February 5
software and contemporary design + media /
analysis of new software-based cultural forms
required: read carefully:
tacit knowlege
John Whitney. Computational Periodics. 1975.
Manovich. Design workflow and Contemporary Aesthetics. 2005.
references for the article:
Graphic Design For The 21st Century: 100 Of The Worlds Best Graphic Designers (Paperback) by Charlotte Fiell (Editor), Peter Fiell (Editor).
some images from the book
1920s normal (not avant-garde) graphic design
what is graphic design?
Manovich. Understanding Hybrid Media. 2008.
links to videos and images discussed in the article:
MK12: Common music video
(MK12 site is in Flash, so I can't provide you with the direct URL to the video.
After you get to MK12 site, navigate to
work>motion>client>
The video you are looking for is titled "Common" -
2nd column, 2nd row)
Ann Lislegard: Crystal World
(download the file "Crystal_world_small.mov" - in <Infoaesthetics> folder
Jeremy Blake | Sodium Fox | Mod Lang
required: watch:
Hans Richter - Rhytmus 21 (1921) | info | movie
Saul Bass title sequences:
Vertigo (1958)
Psycho (1960)
Kyle Cooper: titles for Se7en (1995)
required: visit these sites:
http://xplsv.tv/movies.php
http://www.motionographer.com/
optional or required - depending on your existing knowledge:
If you are new to graphics software, read the following:
motion graphics
graphics program
common media types used today:
Raster_graphics
Vector_graphics
3D model
If you are not familiar with 3D software,
watch the the following Maya videos:
Overview of Maya
Geometry Types
If you are not familiar with Adobe After Effects, watch this video:
Overview of Adobe After Effects CS4
(note: this web page takes a whle to load) )
recommended - watch:
Fundamentals of Motion Graphics
Kyle Cooper documentary
6/ February 12
tutorials on imageJ - Jeremy Douglass
7/ February 19
presentation and discussion of project protypes
cultural infovis - start
8/ February 26
scientific visualization, information visualization, visual analytics,
information design, information architecture
visual interfaces for navigating cultural databases
required:
To further facilitate group collaboration - and also to provide some variety - I am structuring the usual reading assingment in a dffirent way this time. Since you are already working in groups, I am going to ask to resarch a number of terms as a group - and prepare to present and defend your definitions of these terms in class (with examples):
Each group should prepare to define and discuss the following terms: scientific visualization, information visualization, visual analytics, information design, information architecture. Since some of these terms cover similar concepts - and their available definitions also often incosistent - you should be able to provide reasons for your particular definitions. Please also prepare links of projects which exemplify these terms which you can refer in your discussion.
required:
visit all projects/sites linked on genres pages of culturevis.org
required:
go to www.visualcomplexity.com;
check out as minimum 3 projects from every subject category (list on the right: art, biology, etc).
9/ March 4
artistic infovis, cultural infovis, infovis and histories and future of representation / media / visual culture
required:
prepare to discuss the following vis projects:
Fernanda Viegas and Martin Wittenberg: history flow
Stefanie Posavec: writing without words
Brendan Dawes: cinema redux
Alex Dragulescu: spam architecture
required:
Fernanda B. Viégas and Martin Wattenberg. Artistic Data Visualization: Beyond Visual Analytics.
Fernanda B. Viégas, Martin Wattenberg. Tag Clouds and the Case for Vernacular Visualization
recommended:
projects: Jonathan Harris and Sep Kamvar: we feel fine
readings: theory articles about artistic and cultural visualization section of culturevis.com
10/ March 11
digital humanities, qualitative cultural analysis, theories and research on social media, collective intelligence
view:
steve.museum
Project Muse
MIT OpenCourseware
List of academic databases and search engines
read:
qualitative cultural analysis:
Franco Moretti: Graphs, Maps, Trees: Abstract Models for a Literary History
browse the texts in bibliography in Digging Into Data grant web site
academic research on social media:
Introduction and Creative Production
recommended:
museums and the web 2009: nominations for best sites
Collaborative_filtering
Collective_intelligence
Danah m. Boyd and Nicole B. Ellison: Social Network Sites: Definition, History, and Scholarship
academic social media researchers:
Mimi Ito
Danah Boyd
Henri Jenkins
Creative Professional
Rise of the Creative Economy
Creative Industry