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Dr. Lev Manovich Director, Software Studies Initiative, Calit2 UCSD Professor, Visual Arts Department


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Title: Dr. Lev Manovich Director, Software Studies Initiative, Calit2 UCSD Professor, Visual Arts Department

CULTURAL ANALYTICSvisualizing cultural patterns
  • Dr. Lev ManovichDirector, Software Studies
    Initiative, Calit2 UCSD Professor, Visual Arts
  • email manovich_at_ucsd.edupersonal web site
    www.manovich.net personal blog
  • Software Studies Initiative softwarestudies.com
  • You can also contact me on Facebook, Myspace,
    Flickr, and Yourtube.
  • You can follow the development of Cultural
    Analytics athttp//lab.softwarestudies.com/2008/0

BACKGROUNDLets extrapolate and connect some of
the most important technological and cultural
developments of the last 10 years CULTURAL
ANALYTICS is the logical outcome.
1 data revolution.Exponential explosion in
the amounts of data we generate, capture, and
store over last 10 years.
By 2011, the digital universe will be 10 times
the size it was in 2006.This is a compound
annual growth rate of 60.---------------------
------------------IDC (International Data
Corporation). The Diverse and Exploding
Information Universe. 2008.
2 the rise of interactive visualization
1988-To deal with information growth and take
advantage of news ways to create and capture
information, sciences, business, and various
social institutions increasingly turned to
computer-based analysis and visualization of
large data sets and data flows. This approach
has already yielded significant advances in many
scientific fields such as astronomy, geology,
genetics, linguistics, environmental science,
live sciences, computer science,
--------------------------------------1 While
computers were used for visualization already in
the 1960s, the field started to develop rapidly
after National Science Foundation (NSF) 1988
report Visualization in Scientific Computing.
Example researchers in the Consortium for
Estimating the Circulation and Climate of the
Ocean are merging sparse observations of the
Southern Ocean with a state-of-the-art ocean
circulation model (MITgcm) running on SDSCs
DataStar supercomputer to produce estimates of
ocean conditions of greatly increased accuracy.
The map shows the speed of the clockwise
Antarctic Circumpolar current on May 12, 2006.
3 data mining society appr. 2000-
"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.The Automated Learning Group,
National Center for Supercomputing Applications
(NCSA) at The University of Illinois.
background beginning to map global culture using
digital traces. Google Trends.
background beginning to map new global culture
using digital traces. Blogpulse.
Computerworld, May 1, 2006Q. Which areas in CS
will show the most important and interesting
advancements in the next few years?A. Randal E.
Bryant, dean of the school of computer science,
Carnegie Mellon UniversityA recent big growth
area in computing has been in using statistical
methods to process vast quantities of data.
Google is a prime example of that They can
return a query to you in a few seconds based on
the contents of the entire Web. How do they do
it? By maintaining massive data repositories that
allow thousands of processors to operate on
terabytes of data. This data-centric style of
computing will drive many future efforts in
natural-language translation and understanding,
astronomy and even epidemiology. For example, we
have a project that provides early detection of
public health concerns by monitoring the sales of
cough and cold remedies at regional pharmacies --
giving a heads-up before doctors start seeing
disease trends among their patients.
Statistical analysis of large data sets has
become central to many industries, government,
and NGOs.Examples- business intelligence-
new drugs research- medical fraud and credit
card fraud detection- anti-terrorism efforts-
customer profiling- marketing research.The
trend in business intelligence moving from the
analysis of historical data to real-time data
analysis. HP research topic 18 (2008)
Real-time Business Intelligence
InfrastructureFor example, an on-line retailer
would like to analyze a users real-time click
stream data and up-to-the-minute inventory to
offer dynamically-priced product bundles. A
bank would like to detect and react in real-time
to fraudulent transactions. A logistics
provider would like to dynamically reconfigure
shipping routes in response to weather
While large-scale information visualizations as
used in science are still not very common in
business, government, and NGOs, they increasingly
use other interactive visual tools such as GIS
(Geographical Information Systems), Information
Dashboards, Perceptual Mapping, etc.
Example of Perceptual Mapping. Consumer
perceptions of various automobiles on the two
dimensions of sporty/conservative and
distinctive/affordable. Source
4 massive digitization of existing cultural
assetsExamples - Artstor 7800,000
high-quality digital images in art and
architecture - Google Books digitizing
approximately 3000 books a day - partners include
20 leading university libraries- millions of
hours of video in the BBC motion gallery
However, our interfaces to vast media collections
are still based on 19th century models a grid of
images, a slide show, a timeline, a photo album.
Above Andre Malraux (future French minister of
culture) in the 1920 with his museum without
5 2005- The Rise of User-Generated
Contentsocial media sites software consumer
electronics social media cultural objects
produced by non-professional users
conversations around and through these
Lev Manovich The Practice of Everyday (Media)
Life. 2008. Forthcoming in Critical Inquiry.
examples of the growth of user-generated content
Flickr July 2007 600 million images.Flickr
February 2008 1.2 billion images (100 milion /
month).Facebook 14,000,000 photo uploads
daily.MySpace 300,000,000 users. Cyworld, a
Korean site similar to MySpace 90 percent of
South Koreans in their 20s, or 25 percent of the
total population of South Korea. Hi4, a leading
social media site Central America 100,000,000
users.The number of new videos uploaded to
YouTube every 24 hours (as of July 2006)
The number of images uploaded to Flickr every
week is likely to be larger than all objects
contained in all art museums in the world.
User-generated content is one of the fastest
growing part of the expanding information
universe. Fast-growing corners of the digital
universe include those related to digital TV,
surveillance cameras, Internet access in emerging
countries, sensor-based applications, datacenters
supporting cloud computing, and social
networks. Approximately 70 of the digital
universe is created by individuals.
--------------------------------------- IDC
(International Data Corporation). The Diverse and
Exploding Information Universe. 2008.
6 parallel expansion of professional cultural
universe agencies (educational institutions,
companies, museums), actors (professional
cultural producers, students), publishing (books,
catalogs, web sites, blogs), cultural objects.
The rapid growth of professional educational and
cultural institutions in many newly globalized
countries along with the instant availability of
cultural news over the web has also dramatically
increased the number of "culture professionals"
who participate in global cultural production and
discussions. Hundreds of thousands of students,
artists, designers have now access to the same
ideas, information and tools. It is no longer
possible to talk about centers and provinces.
In fact, the students, culture professionals,
and governments in newly globalized countries are
often more ready to embrace latest ideas than
their equivalents in "old centers" of world
If you want to see this in action, visit the
following web sites and note the range of
countries from which the authors come
fromstudent projects on archinect.com/gallery
design portfolios at coroflot.commotion
graphics at xplsv.tv
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growth of a global culture space after 1990.
Example Fashion Weeks, 2005.
growth of a global culture space after 1990.
Example architecture. left Danish Pavillion by
MA architects (Beijing), 2006. right kbh
kunsthal in Copenhagen - by MA architects
(Beijing), proposal, 2007.
Acceleration of changes in consumer behavior.
Screenshot from trendwatching.com
Before, cultural theorists and historians could
generate theories and histories based on small
data sets (for instance, "classical Hollywood
cinema," "Italian Renaissance," etc.) But how
can we track "global digital culture(s), with
its billions of cultural objects, and hundreds of
millions of contributors? Before you could
write about professional culture by following
what was going on in a small number of world
capitals and schools. But how can we follow the
developments in tens of thousands of cities and
educational institutions?
7 visualization emerges as a new area of
culture 1998-2007
Visualization in public spaces 2005- In the
last two years visualization has been integrated
in some of the most prestigious new buildings
Seattle Public Library (architect Rem
Koolhaus)The New York Times Building in NYC
MOMA IAC Building in NYC - lobby (architect
Frank Gerhy), Wolkvagen Autostadt,
GermanyArticles about visualization designers
and artists - Lisa Strausfeld, Martin Wattenberg,
Jonathan Harris - in mainstream press (i.e.,
Business Week).MOMA show Design and Elastic
Mind (Spring 2008) features visualization
Visualization of books flow in Seattle Public
Library. Artist George Legrady, UCSB
IAC Building, NYC outside view the lobby with
the visualization showing global users accessing
web properties owned by IAC. Dynamic
visualization as a new logo of a
company/institution -- representation of dynamic
process rather than static identity.
IAC Building, NYC lobby with the screen.
New York Times building
Wolksvagen Autostad
a growing number of artistic visualization
projects 2005-
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8 the rise of culture visualization graphing
cultural patterns culturevis.com - a web site
developed by Software Studies Initiative (7/2008
- ) to collect best projects and provide
resources for help promote this work.
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History Flow visualization
History Flow visualization
Graphs of statistical data are beginning to be
integrated in consumer software and webware.
Example statistics for activity on individual
user account on Flickr.
Can we create quantitative measures of cultural
innovation? Can we have a real-time detailed
interactive maps of global cultural production,
consumption, remixing, and collobarations? 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?Can we use interactive
visualization to research existing cultural
trends and patterns and predict their future
The joint availability of large cultural data
sets (through the exponential growth of user
generated content, digitization efforts by
museums and libraries, and digital traces),
cultural information (web presence of all
professional cultural agents) and the tools
already employed in the sciences to analyze big
data makes feasible a new methodology for the
study of cultural processes and artifacts -
including contemporary cultural production and
consumption. We can create interactive
visualizations and dynamic maps of large cultural
data sets to discover patterns that have not been
visible previously.
It is time to start thinking of culture as data
(including media content and peoples creative
and social activities around this content i.e.
social media) that can be mined and visualized.
If data analysis, data mining, and visualization
have been adopted by scientists, businesses, and
social agencies as a new way to generate
knowledge, let us apply the same approach to
understanding cultural flows and dynamics.
Who would use Cultural Analytics? - cultural
creators in all fields who want to better
understand how their work fits within a larger
global context - students in digital media, art
history, media studies, cultural history,
communication studies, ethnography, HCI, etc. -
social scientists, historians, anthropologists,
humanities scholars who professionally study
culture- any researchers who deal with multiple
sources of information to study human activity
(i.e, video, records of screen activity,
movements in space, conversation) - museums
and other cultural spaces.- trend forecasting
and cool hunting agencies - marketing and
advertising departments of media companies
(including social media)I anticipate that
Cultural Analytics systems may eventually be
adopted as standard tools in all areas of
creative industries similar to how today most
business executives use information dashboards.
Cultural Analytics developed bySoftware
Studies Initiative - funded by Calit2-San Diego
California Institute for Information and
Telecommunication) and CRCA (Center for Research
in Computing and the Arts, UCSD)Lev Manovich
Jeremy Douglass (post-doctoral researcher)grad
and undergrad students in Visual Art Department,
UCSD Visualizing Cultural Patterns - 3 year
grant from UCSD Chancellors Interdisciplinary
Collaboratories program Lev Manovich, (Calit2-
San Diego Visual Arts Department)Noah
Wardrip-Fruin (Calit2-San Diego Communication
Department)James Hollan (Calit2 - San Diego
Cognitive Science)Falko Kuester (Calit2 - San
Diego Department of Structural
IMAGINE a real-time traffic display (a la car
navigation systems) except that the display is
wall-size, and the traffic shown is not cars on
highways, but some of the real-time cultural
traffic around the world. IMAGINE the same
wall-sized display divided into multiple windows,
each showing different data about cultural,
social, and economic news and trends thus
providing a situational awareness for cultural
IMAGINE a wall-sized interactive visualization
showing the long tail of cultural production that
allows you to zoom to see each individual product
together with rich data about it (à la real
estate map on zillow.com) while the graph is
constantly updated in real-time by pulling data
from the web.
IMAGINE the same wall-sized display playing an
animation of what looks like an earthquake
simulation produced on a super-computer except
in this case the earthquake is the release of a
new version of a popular software or an important
consumer electronics product, the release of a
new major video game, or the announcement of an
important architectural project. What we are
seeing are the effects of such cultural
earthquake over time and space.
We are building an open Cultural Analytics
research environment an interactive system for
the mapping, analysis and visualization of large
sets of cultural data and information.
cultural data- photos, art, music, design,
architecture, films, motion graphics, games, web
sites, interactive environments, spaces - i.e.
actual cultural artifacts/experiences.cultural
information - cultural news published on the
web (web sites, blogs) - both professional and
user-generated content- conversations around
cultural content. Data sets can be comparable
in size to largest data sets used in the
Cultural Analytics research environment will run
on HIPerSpace OptIPortal, currently (11/2008) the
highest-resolution displays in the world -
developed _at_GRAVITY (Graphics, Visualization and
Virtual Reality Laboratory, Calit2-San
Diego.)Calit2 San Diego - HIPerSpace - current
configurationresolution 287 megapixels (35,640
by 8,000 pixels).physical dimensions 9.7
metres x 2.3 metres (31.8 feet wide and 7.5
feet).hardware 18 Dell XPS710 with nVIDIA
Quadro FX5600s 72 Dell 30 Displays.Calit2
Irvine - HIPerWall - current configuration50
Apple 30-inch Cinema Displays driven by 25 Power
Mac G5. The software would run both on a
HIPerSpace and on PCs/MACs - although
HIPerSpace-type displays offer the ability to see
much more detail and also would allow for new
modes of interaction with the information (such
as group multi-touch).
Platform for Cultural Analytics research
environment HIperSpace (287 megapixels).
What kind of interface do we need to create
situational awareness for cultural analysts?
The interfaces used today whenever a
person/group monitors a performance of
system/machine/process, makes decisions and
controls (i.e., a human-machine system) all
share the common principle - multiple displays
which present information about a system/process
using diff. visual techniques. Examples vehicle
interfaces, patient monitoring in a hospital,
control room of a plant, information dashboards,
financial news.Culture is a complex system /
process / environment - therefore we should use
similar interface design for studying and
monitoring it.----------------------------------
----------------------For a historical analysis
of a concept of a human-machine system, see
Manovich, Engineering of Vision (PhD
dissertation, 1993) Manovich and Kratky, Soft
Cinema Navigating the Database (MIT Press,
Example of an existing interface Barcos iCommand
Example of an existing interface ATT control
center (2001).
Cultural Analytics research environment
interface mockup. Focus geo map.
IDEOLOGY OF DIGITAL TRACES. Not all cultural and
social activities leave digital traces on the
web. A significant part of todays global culture
is digitally invisible. Therefore, we cant
only do projects which rely on web data or
existing databases - we also need to take on
digitally invisible cultural activities using
available and original etnographic research.
Example envisioned analysis of the development
of shanty towns in Mexico city (using research
of the local architects working with these
Cultural Analytics research environment
interface mockup. Focus long tail.
Map of Science visualization
Cultural Analytics research environment
interface mockup. Focus relationships map.
Cultural Analytics research environment
interface mockup running on HIPerWall
Cultural Analytics research environment
interface mockup running on HIPerWall
Cultural Analytics research environment
interface mockup running on HIPerWall
Example of a use researchers working with AMVs
(Anime Music Video). Data source there are a
few hundred thousands AMVs available on YouTube
and other web sites dedicated to AMVs). First,
the software would analyze all videos extracting
various features. This metadata will be added to
previously available metadata descriptions and
rating by authors and fans, place of origin,
video length, year, etc.The interactive system
would allow us to see each video in the context
of the overall set identify "statistically
improbable" videos add/edit our own metadata,
descriptions, markers, etc. We can also
simultaneously display the remix videos and all
the sources they use and analyze the
relationships. We would also be able to compare
the analytical languages by authors, fans, and
professional researchers (if we collect the
appropriate data first).
Why Cultural Analytics?existing
termsknowledge discoveryfrom data to
knowledgeweb analyticsbusiness
analyticsvisual analytics the science of
analytical reasoning facilitated by interactive
visual interfaces
On April 22, 2008, National Endowment for
Humanities Office of Digital Humanities announced
Humanities High Performance Computing
initiativeHumanities High-Performance
Computing (HHPC) refers to the use of
high-performance machines for humanities and
social science projects. Currently, only a small
number of humanities scholars are taking
advantage of high-performance computing. But just
as the sciences have, over time, begun to tap the
enormous potential of HPC, 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 understand and
visualize this data.NEH wants humanists to get
trained to use TeraGrid network and the National
Energy Research Scientific Computing Center
(NERSC) at the Lawrence Berkeley National
Laboratory. Currently, TeraGrid resources include
more than 750 teraflops of computing capability
and more than 30 petabytes of online and archival
data storage.
November 20, 2008 Software Studies Initiative is
awarded Humanities High Performance Computing
initiative grant. The grant will be used to
analyze and visualize large visual media data
sets (photographs, video, films, videos of
gameplay, etc.)
While Humanities High-performance Computing
initiative (HHPC) so far has been only announced
in the USA, we can expect that the idea of data
mining and visualizing large humanities and
social science data sets will soon be taken in
other countries. Our goal is to create a
general-purpose Cultural Analytics research
environment which could be used by not only us
but also all other researchers working with large
cultural data sets.At the same time, while we
also want to data-mine cultural data from the
past, the goal of Software Studies Initiative is
to work on analyzing and mapping contemporary
global cultural production, consumption,
remixing, collaboration, preferences, dynamics,
flows, and patterns.
Cultural Analytics in the classroom Cultural
Analytics is very suitable for undergraduate
teaching. Because data gathering, data analysis,
and visualization can be treated as separate
projects, the work can be continued across the
semester boundaries.For instance, students in
one class can work on visualizing data sets
created by students in a previous class. (I have
already been using this approach in my classes
using ManyEyes.)Cultural Analytics Research
Environment can also act as a global educational
platform. We envision students from around the
world contributing data sets, maps and
visualizations, analyzing each other data,
Example of a student project done at UCSD (winter
2008) a visualization of the connections between
subcultures. source sharedeggg.blogspot.com
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Key differences between existing work in culture
visualization and our approach1. The projects
created so far are driven by the available data
rather than by theories of cultural and social
processes. We believe that significant results
will only be achieved in the context of
theoretical research questions from the
humanities, social sciences and culture
industries combined with the advances in
information visualization and interaction
design.2. Existing cultural visualizations
typically use relatively small data sets. We want
to develop new visualizations and interaction
techniques appropriate for much larger data sets.
The limitations of existing visualizations are,
in part, an outgrowth of the fact that many are
designed for the web, limiting how much
information they can show legibly. We will use
new wall-size displays with a resolution in
hundreds of megapixels to display more
information and also to enable new modes of
interaction (such as HiperWall and HiperSpace
created at Calit2). This will also allow us to
address the challenge of analyzing and
visualizing data-intensive types of cultural
media that so far have not been approached -
specifically, feature films, video, computer
games, and architecture.
3. Most existing work in visualization of media
data relies exclusively on existing metadata
(such as Flickr community-contributed tags). In
contrast, our methodology calls for the
computational content analysis to generate new
metadata - in particular, image processing and
computer vision.4. The existing culture vis
projects typically show the abstract graphs - but
not the original data. Cultural Analytics
research environment which will allow the user to
work both with the original data and its multiple
visualizations at the same time. When a user
makes a selection in one display, all displas are
automatically updated. The interface also allows
the user to move between the overall view of the
whole data set and the individual cultural
artifacts. 5. Cultural Analytics research
environment will be an open social knowledge
production platform. Users will be able to add
new analytical and visualization modules. We can
also use collaborative knowledge production /
social media paradigm users can add their own
data, analysis of data, visualizations,
interpretation of the results created by others,
vote for most interesting results, etc. Study of
culture moves from being the domain of small
groups of experts to being open to all. We can
also tap into the knowledge of millions of fans
and passionate users - they can annotate cultural
objects they are knowledgible about, judge if
visualizations and analysis make sense to them,
6. Existing culture vis projects usually show
only a few or a single dimensions of a data set.
Our methodology is to visualize separately each
of the dimensions of a data set (and some of
their combinations if appropriate) and to combine
these visualizations into a single intergrated
interactive interface.--------------------------
------------------------------------ a
dimension a records field in a cultural
database, i.e. authors name, project date,
shape, distribution of colors, etc.
Examples of projects we want to do within
Cultural Analytics paradigm Projects which
analyze the contents of a set of cultural
products (each questions below can be also asked
in relation to any other art/design field) in
order to visualize historical development,
influences, differences, etc.(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?" (Examples
of data sets design portfolios on coroflot.com
student blogs of architectural schools _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 today between the works
in different genres - commercial, experimental,
VJ live, etc?"
More examples of visualization projects showing
cultural dynamics - the patterns in how cultures
change(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)? We can also do this project
in relation to the characteristics of video
games, movies, blogs, or any other currently
popular cultural form over periods of time. (4)
the story of how the world has moved from a old
world paradigm to a flat world (2000) to an
inverted world (2005) in which newly developed
countries have become leaders in cultural
innovaton and experimentation?(5) Cultural
evolution - the ways in which a set of cultural
forms gives rize to more forms - for instance, a
visualization showing the proliferation of styles
in popular and dance music over the last few
decades and their adoption around the world 6)
Mapping cultural and social phenomena which do
not leave easily accessible digital traces on
the web - for instance, a time-space interface
showing the growth of shanty towns in Mexico
city (small towns developed by people themselves
from scratch over a few decades - DIY
Examples of projects which look at the patterns
in the development of cultural institutions,
ideas, and cultural perceptions(7) How do
designers in different parts of Asia incorporate
the concept of Asia in their designs? Do these
different Asia concepts work in distinct ways
in different media? What are the cultural DNA
which make Asia in design, and how they are
distributed across different regions, media,
markets?(8) 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 decade?
What patterns would we see if we analyze the
titles and descriptions of all the exhibitions
they have put on?(9) 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 can
analyze Wikipedia pages for these concepts. We
can use the dates when the pages were established
and also compare how much and how frequently
people contributed to each page." (I.e., doing
History Flow type of analysis - but on a large
set of wikipedia pages.)
Examples of a projects which analyze cultural
flows - the ways in which cultural atoms
(elements, memes) and cultural DNAs
(techniques) travel in time, space and from one
context to another 10) How does a new cultural
atom travels in space, time, and gets adopted by
other subcultures/authors? For instance, what
patterns would we see if we map and analyze how
the elements of the new popular video gets
remixed by other users in their videos?11) Can
we map the relationships between AMVs produced by
fans and all original sources they use (anime,
music videos, computer games)?12) Since the
history of human cultures is that of
cross-cultural exchange, adoptation, and
intergration of foreign elements into the
existing culture - can we create detailed
visualizations of such flows based on the content
analysis of large number of artifacts? Example
development of modern art in diff. Asian
countries in the 20th century - attempts to
integrate Western ideas with the local
traditions. Example a study of material
artifacts from a number of ancient cultures which
were in contact. Example beginning with the
artifacts in a culture in a particular place and
time period, we crawl (a la web search engine)
to all other cultures which these artifacts
historically are connected with (came from).
fMRI of a global cultural braintoday
neuroscience combines single neuron recodings,
tracking activities of neural networks (1mm) and
neural maps (1cm), fMRI of the neural activity of
the whole brain, and other methods.Usual
analysis of culture can be compared to recording
and analyzing activity of a single cell or a
small cell population.We need to start tracking,
analyzing and visualizing larger cultural
structures - (including their connectivity and
dynamics over space and time) - equivalents of
neural networks, maps, cortical columns, and the
whole brain.Applying other techniques from
neuroscience such as staining cells. (UCSD
other research labs nearby - the leading area in
the world for neuroscience research). Applying
the basic method of contemporary neuroscience
combining results from different research methods
(MRI, PET, staining cells, genomics, etc.)
P.S. Our long-term research plansfrom
visualization of cultural patterns to modeling
and simulation.
Studying cultural processes from taxonomy to
evolutionary biology We usually think of
culture in terms of taxonomies - styles, genres,
market segments - equivalent of the biology in
the 18th century. The exponential increases in
the number of cultural objects (lifestyle
products, films, photographs, songs, graphic
designs, etc.) created by both professional
producers and non-professionals - and the similar
increase in the number of producers - create a
new cultural universe. The sheer size of the
new cultural universe, and its much higher
connectivity1 makes appropriate to apply
scientific paradigms and methods (including
mathematical models and computational modeling)
used in evolutionary biology, environmental
biology, genomics, bioinformatics, and other live
sciences to study large-scale biological
phenomena. 2----------------------------------
-----2 Future collaboration with Calit2 Center
for Algorithmic and Systems Biology (CASB)
----------------------------------1 Higher
cultural connectivityglobalization access to
the same ideas and tools more people using
English as a global cultural platformlarge-scale
globally distributed production in games
industry, film industry, etc.social media
software which encourages remix and media
mobilitydesktop software production
environment which similarly makes it very easy to
borrow elements from other cultural
productsincrease in travel access to cultural
objects produced by everybody else (Youtube,
Flickr, portfolio web sites of professional
designers, etc.) Lev Manovich, Remixability
and Modularity, 2005.
Mathematical simulations of global cultural flows
based on the existing data?Blue Brain project
_at_Henry Markram's Brain and Mind Institute at the
École Polytechnique (EPFL) in Lausanne Henry
Markram anticipates that a simulation of a
complete human brain down to the molecular level
(based on all existing experimental neuroscience
data) will be available before 2020.
--------------- An interdisciplinary team of 35
researchers has cast the reverse-engineering of
the biological pieces and the forward
construction of detailed mathematical models in
an iterative process that allows continuous
refinement. Particular efforts go into the
preparation of 10,000 unique morphologically-comp
lex electrical models representing all
morpho-electrical classes as well as
establishing their structural and functional
connectivity. Once a multi-compartmental
description for each neuron is generated and the
exact locations of the synapses (30 million)
are determined, the simulation is supposed to
reproduce emergent properties found in slice
experiments. The refinement is directed by a
bottom-up calibration that aligns the model
across all levels - from the ion channels to the
emergent network phenomena - with the
experimental data. In order to put the expert in
the loop, extensive use of visualization and
interactive analysis is made, which is powered
by another dedicated supercomputer in order to
realize short turn-around times.
If we do simulation-based research into global
cultural flows, what kinds of models would we
need? More complex than for brain simulation?
More simple?If simulation-based research is now
being applied to new scientific areas, let us use
it to study global culture. What new analytical
categories can we develop if we aim for an
equivalent of a Blue Brain project - simulating
all of contemporary global cultural developments
and relationships using all available data?
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