1. No category

IST 511 Information Management: Information and
Technology
Introduction to IST 511
Dr. C. Lee Giles
David Reese Professor, College of Information Sciences
and Technology
Professor of Computer Science and Engineering
Professor of Supply Chain and Information Systems
The Pennsylvania State University, University Park, PA,
USA
giles@ist.psu.edu
http://clgiles.ist.psu.edu
What is IST 511?
• Introduction to algorithmic/computational parts of IST
– There will be some maths
• Guide to research
– In information and related sciences
– In IST
– Illustrate the intellectual diversity of IST
• Methodology
– Read, view, discuss and write about ideas and papers in the
field
• When possible, use examples of IST 511 research from IST grad students
– Write a research proposal paper and give a professional
presentation
• Focus on methodologies discussed here
IST 511
• Nearly all course material is at:
http://clgiles.ist.psu.edu/IST511
Lose this address, put IST511 into Google or Bing
Read this page and links very carefully at least once a week
• Angel is used so far only for student submissions.
• Important notices will be sent by email with the subject:
IST511
Today
• What is information
– Things - artifacts
– Use
• Personal, social,etc.
– Foundations and representation
– Information vs knowledge
• Information science vs informatics vs
information theory
Tomorrow
Topics considered and used in IST (will consider
some, not all)
•
•
•
•
•
•
•
•
•
•
•
Complexity
Representation
AI
Machine learning
Information retrieval and search
Text
Encryption
Social networks
Probabilistic reasoning
Digital libraries
Others?
Theories in Information Sciences
• Enumerate some of these theories in this course.
• Issues:
– Unified theory?
– Domain of applicability
– Conflicts
• Theories here are mostly algorithmic
– Automated vs manual
– Scalable features
• Google vs iPhone
• Quality of theories
– Occam’s razor
– Subsumption of other theories
Past & Recent Headlines
• A Minnesota hacker was sentenced to 18 years in prison on Tuesday for
using his neighbors’ wireless network without permission and then
framing them for child pornography distribution and email threats
against Vice President Joe Biden and other officials.
• “Latest Genealogy Tools Create a Need to Know”
• “Bots Hammer Estonia In Cyber Vendetta”
• “UPS slashed the time it takes to determine the least-expensive route
from months and wants to make that information available in real time”
• “Sophisticated internet users continue to fall for spam”
• “Google makes us stupid”
• “Google makes us smarter”
• “IT doesn’t matter”
• “Microsoft and Yahoo unite against Google Book Search”
What is Information?
•
There are several ways to define
“information”
–
–
Subjective: People develop models of their
environment. Information created by people
makes those models more accurate.
Thing/artifact: Information is what’s
captured in a book, web page, or other
resource.
•
More information is digital
Information - wikipedia
• Information as a concept has a diversity of meanings, from everyday
usage to technical settings. Generally speaking, the concept of
information is closely related to notions of constraint, communication,
control, data, form, instruction, knowledge, meaning, mental stimulus,
pattern, perception, and representation.
• Many people speak about the Information Age as the advent of the
Knowledge Age or knowledge society, the information society, the
Information revolution, and information technologies, and even though
informatics, information science and computer science are often in the
spotlight, the word "information" is often used without careful
consideration of the various meanings it has acquired.
How much information is
there in the world
Informetrics - the measurement of
information
• Stored
–
–
–
What can we store
What do we intend to store.
What is stored.
• How do we use it
–
Decision making
Information Age
• We have entered the information age
–
What is the information age?
• When do we leave it and where do we
go next?
–
–
David Weinberger’s Too Big to Know
What information was
Digitization of Everything: the Zettabytes are coming
•
•
•
•
•
Soon most everything
will be recorded and
indexed
Much will remain local
Most bytes will never
be seen by humans.
Search, data
summarization, trend
detection, information
and knowledge
extraction and
discovery are key
technologies
So will be
infrastructure to
manage this.
Digital Information
Created, Captured, Replicated Worldwide
Exabytes
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0
10-fold
Growth in 5
Years!
DVD
RFID
Digital TV
MP3 players
Digital cameras
Camera phones, VoIP
Medical imaging, Laptops,
Data center applications, Games
Satellite images, GPS, ATMs, Scanners
Sensors, Digital radio, DLP theaters, Telematics
Peer-to-peer, Email, Instant messaging, Videoconferencing,
CAD/CAM, Toys, Industrial machines, Security systems, Appliances
2006
Source: IDC, 2008
2007
2008
2009
2010
2011
Scale of things to come
• Information growth:
– In 2002, recorded media and electronic information flows generated
about 22 exabytes EB (1018) of information
– In 2006, the amount of digital information created, captured, and
replicated was 161 EB
– In 2010, the amount of information added annually to the digital
universe was about 988 EB (almost 1 ZB)
• How much of this is information, data or knowledge?
Digital Universe Environmental Footprint
•
•
In our physical universe, 98.5% of the
known mass is invisible, composed of
interstellar dust or what scientists call
“dark matter.” In the digital universe,
we have our own form of dark matter
— the tiny signals from sensors and
RFID tags and the voice packets that
make up less than 6% of the digital
universe by gigabyte, but account for
more than 99% of the “units,”
information “containers,” or “files” in
it.
Tenfold growth of the digital
universe in five years will have a
measurable impact on the environment,
in terms of both power consumed and
electronic waste.
How much information is there?
Yotta
• Soon most everything will be
recorded and indexed
• Most bytes will never be seen
by humans.
• Data summarization,
trend detection
anomaly detection
are key technologies
See Mike Lesk:
How much information is there:
http://www.lesk.com/mlesk/ksg97/ksg.html
See Lyman & Varian:
How much information
Everything
!
Recorded
All Books
MultiMedia
Exa
Peta
All books
(words)
.Movi
e
A Photo
http://www.sims.berkeley.edu/research/projects/how-much-info/
A Book
24 Yecto, 21 zepto, 18 atto, 15 femto, 12 pico, 9 nano, 6 micro, 3 milli
Zetta
Tera
Giga
Mega
Kilo
Information Facts
Print, film, magnetic, and optical storage media produced about 5 exabytes of new
information in 2002. Ninety-two percent of the new information was stored on
magnetic media, mostly in hard disks.
•
•
•
•
How big is five exabytes? If digitized with full formatting, the seventeen million
books in the Library of Congress contain about 136 terabytes of information;
five exabytes of information is equivalent in size to the information contained in
37,000 new libraries the size of the Library of Congress book collections.
Hard disks store most new information. Ninety-two percent of new information
is stored on magnetic media, primarily hard disks. Film represents 7% of the
total, paper 0.01%, and optical media 0.002%.
The United States produces about 40% of the world's new stored information,
including 33% of the world's new printed information, 30% of the world's new
film titles, 40% of the world's information stored on optical media, and about
50% of the information stored on magnetic media.
How much new information per person? According to the Population Reference
Bureau, the world population is 6.3 billion, thus almost 800 MB of recorded
information is produced per person each year. It would take about 30 feet of
books to store the equivalent of 800 MB of information on paper.
Information Census
Lesk
Varian & Lyman
EB
PB
•
•
•
•
~10 Exabytes
~90% digital
TB
> 55% personal
Print: .003% of bytes
5TB/y, but text has lowest entropy
• Email is
4PB/y and is 20% text
• WWW is ~50TB
deep web ~50 PB
• Growth: 50%/y
(10 Bmpd)
Media
(estimate by Gray)
Growth
Rate, %
TB/y
optical
50
70
paper
100
2
100,000
4
magnetic
1,000,000
55
total
1,100,150
50
film
First Disk 1956
• IBM 305 RAMAC
• 4 MB
• 50x24” disks
• 1200 rpm
• 100 ms access
• 35k$/y rent
• Included computer &
accounting software
(tubes not transistors)
1.6 meters
10 years later
30 MB
Now - Terabytes on your desk
Terabyte external
drive for
$200 - 20 cents a
gigabyte.
In 5 years, 1
cent/gigabyte, $10
for a terabyte?
Now - Terabytes on your desk
Terabyte external drive for
$200 - 6 cents a gigabyte.
In 5 years, 1 cent/gigabyte, $10 for a
terabyte?
Moore's Law
• Defined by Dr. Gordon Moore during the
sixties.
• Predicts an exponential increase in
component density over time, with a
doubling time of 18 months.
• Applicable to microprocessors, DRAMs ,
DSPs and other microelectronics.
• Monotonic increase in density observed
since the 1960s.
Moore’s Law - Density
Disk TB Shipped per Year
1E+7
Storage capacity
beating Moore’s law
• Improvements:
Capacity
60%/y
Bandwidth 40%/y
Access time
16%/y
• 1000 $/TB
today
• 100 $/TB in 2007
Moores law
58.70% /year
TB growth
112.30% /year since 1993
Price decline 50.70% /year since 1993
Most (80%) data is personal (not enterprise)
This will likely remain true.
1998 Disk Trend (Jim Porter)
http://www.disktrend.com/pdf/portrpkg.pdf.
ExaByte
1E+6
1E+5
disk TB
growth:
112%/y
Moore's Law:
58.7%/y
1E+4
1E+3
1988
1991
1994
1997
2000
Digital Immortality
Bell, Gray, CACM, ‘01
Requirements for storing various media for a single
person’s lifetime at modest fidelity
What is Digital Immortality?
• Preservation and interaction of digitized
experiences for individuals and/or groups
– Preservation and access
– Active interaction with archives through
queries and/or an avatar (agents)
– Avatar interactions for group experiences
• Issues:
–
–
–
–
Archiving
Indexing
Veracity
Access
New Information Flows
• Telephone increase is significant
Internet
All the world’s libraries on
your iPod! iPhone
NY Times Magazine
And you thought finding that
song was hard.
•Storage is practically free
•Much is mobile
•Access is crucial
•Moore’s law keeps on trucking
Low rent
min $/byte
Shrinks time
now or later
Shrinks space
here or there
Automate processing
knowbots
Immediate OR Time Delayed
Why Put Everything in Cyberspace?
Point-to-Point
OR
Broadcast
Locate
Process
Analyze
Summarize
Memex
As We May Think, Vannevar Bush, 1945
“A memex is a device in which an individual
stores all his books, records, and
communications, and which is mechanized so
that it may be consulted with exceeding speed
and flexibility”
“yet if the user inserted 5000 pages of material a
day it would take him hundreds of years to fill
the repository, so that he can be profligate and
enter material freely”
Trying to fill a terabyte in a year
Item
Items/TB
Items/day
300 KB JPEG
3M
9,800
1 MB Doc
1M
2,900
1 hour 256 kb/s
MP3 audio
1 hour 1.5 Mbp/s
MPEG video
9K
26
290
0.8
Progress of Science Paradigms
• Thousand years ago:
science was empirical
describing natural phenomena
• Last few hundred years:
theoretical branch
using models, generalizations
• Last few decades:
a computational branch
2
.
a
4G
c2
 a   3  2
a
 
 
simulating complex phenomena
• Today:
data and information exploration (eScience)
unify theory, experiment, and simulation - information driven
– Data captured by sensors, instruments
or generated by simulator
– Processed by software
– Information/Knowledge stored in computer
– Scientist analyzes database / files
using data management and statistics
– Network Science
– Cyberinfrastructure
Information Systems
•
An Information System is the system of persons, data records and
activities that process the data and information in a given
organization, including manual processes or automated processes.
–
–
•
Usually the term is used erroneously as a synonymous for computerbased information systems, which is only the Information
technologies component of an Information System.
The computer-based information systems are the field of study for
Information technologies (IT); however these should hardly be
treated apart from the bigger Information System that is always
involved in.
The actual system such as a search engine, etc.
The
Information
Funnel
Information is nearly always developed to facilitate human needs!
•
•
Complexity of the World
Capture
Representation
Apply
Representation as Information:
What Makes a Good Representation?
•
• A straight
line can be a good representation
for describing some data.
• For other data, a curved (quadratic) line is
better.
Types of Representations
•
•
•
•
•
•
Categories
Equations
Language
Logic statements
Images
Mental models
Models(information) of Processes
•
Square-wave
process
Modeled by
sine wave
Information Processing
•
There are many ways to apply the information stored in
representations.
• Retrieval
– Finding useful information
• Recognition
– Identifying an instance
• Inference
– Extend stored information to a new situation
Context
• One of the hardest problems for
information processing is determining the
context in which the information is
applied.
• This may lead to incorrect inferences.
• Some say information is data in context.
People and Information
• People process information based on their
experience and context.
• Human information processing is affected
by emotions and needs.
• Your data may be my information
What is an information system?
• Processes information
• Requires knowledge of what information is
• How much information is available
– Static vs dynamic
– Explict vs implicit
• How it is used and structured
– information management
• How it’s managed
• Incorporated into personal or social use.
Information Characteristics
• Structural / Ontological / context
– State based
•
•
•
•
•
Representations / rules
Functional / active
Language / communication
Personal
Social
What is knowledge?
• Data - Facts, observations, or perceptions.
• Information - Subset of data, only including those
data that possess context, relevance, and purpose.
• Knowledge -
A more simplistic view considers
knowledge as being at the highest level in a hierarchy
with data (at the lowest level) and information (at the
middle level).
•Data refers to bare facts void of context.
–A telephone number.
•Information is data in context.
–A phone book.
•Knowledge is information that facilitates action.
–Recognizing that a phone number belongs to a good client,
who needs to be called once per week to get his orders.
From Facts to Wisdom
(Haeckel & Nolan, 1993)
one example of the hierarchy
Volume
Completeness
Objectivity
Less is
Value
More
Structure
Wisdom
Knowledge
Intelligence
Information
Facts
Subjectivity
What is knowledge?
• Knowledge - A more complex view considers
knowledge as intrinsically different from
information. Instead of considering knowledge as
richer or more detailed set of facts, we define
knowledge in an area as justified beliefs about
relationships among concepts relevant to that
particular area.
Is Information
• An aspect of intelligence?
– Derivative to its use
• An aspect of life?
• Innate to physical reality?
– Innate code, ex DNA, etc.
Characteristics of Information
–
–
–
–
–
–
–
–
–
Invariant
Dynamic
Personal
Situational
Cultural
An act versus a fact
Additive
Symbolic
Others?
Information Theory
• Information theory is a discipline in applied
mathematics involving the quantification of data
with the goal of enabling as much data as possible
to be reliably stored on a medium or
communicated over a channel.
• The measure of information, known as
information entropy, is usually expressed by the
average number of bits needed for storage or
communication.
– The more common the event, the higher the entropy
http://en.wikipedia.org/wiki/Information_theory
Claude Shannon
• Claude Shannon is the creator
of “information theory”
• The definition was not a broad
definition of “information”
nor it was others were
referring to information at that
time and even now.
• However, the definition can
be quite useful
Models of Information
• Common model: a representation of data
– When possible formalize the information process
– Interoperability
– Standards
• What is formalization?
– Logical or mathematical representation
• Natural language definitions are becoming formal
– Why formal definitions of information?
– Examples?
Formalization/automation/digitization
of Information
Advantages:
• Costs
• Reproducibility
• Scalability
• Automation
• Interpretation
• Others?
Consequences of Information
• Information can lead to
–
–
–
–
–
Decisions
Actions
Contemplation
Laws
More information
Models of Information Use
• Personal models
– Cognitive
• Social models
–
–
–
–
–
Institutions
Groups
Nations
Commerce
Etc.
What is Information?
• There is no standard definition
• Context is important; maybe vital
– "Information is produced when data are processed so
that they are placed within some context in order to
convey meaning to a recipient."
• Information causes things to happen
– Permits decisions, actions, predictions, etc.
• An innate aspect of intelligence/universe?
The Philosophy of Information: A Definition
What is the Philosophy of Information?
a new philosophical discipline, concerned with
a) the critical investigation of the conceptual nature and basic
principles of information, including its dynamics (especially
computation and flow), utilisation and sciences; and
b) the elaboration and application of information-theoretic and
computational methodologies to philosophical problems.
L. Floridi
What is the Philosophy of Information? (2002)
Open Problems in the Philosophy of Information © L. Floridi
P.3 The GUTI Challenge
Is a grand unified theory of information possible?
The word “information” has been given different
meanings by various writers in the general field of
information theory. It is likely that at least a number of
these will prove sufficiently useful in certain applications
to deserve further study and permanent recognition. It is
hardly to be expected that a single concept of
information would satisfactorily account for the
numerous possible applications of this general field.
(Shannon 1993, 180)
Reductionism: we can extract what is essential to understanding
the concept of information and its dynamics from the wide variety
of models, theories and explanations proposed.
Non-Reductionism: we are dealing with a network of logically
interdependent but mutually irreducible concepts.
Open Problems in the Philosophy of Information © L. Floridi
What is information science?
wikipedia
Not to be confused with informatics or information theory
• Information science is an interdisciplinary science primarily
concerned with the collection, classification, manipulation, storage,
retrieval and dissemination of information. Practitioners within the
field study the application and usage of knowledge in organizations,
along with the interaction between people, organizations and any
existing information systems, with the aim of creating, replacing or
improving information systems. Information science is often
(mistakenly) considered a branch of computer science. However, it
is actually a broad, interdisciplinary field, incorporating not only
aspects of computer science, but often diverse fields such as
mathematics, business, library science, cognitive science, and the
social sciences.
information science vs informatics
wikipedia
• Informatics is the science of information, the practice of
information processing, and the engineering of
information systems. Informatics studies the structure,
algorithms, behavior, and interactions of natural and
artificial systems that store, process, access and
communicate information.
• It also develops its own conceptual and theoretical
foundations and utilizes foundations developed in other
fields. Since the advent of computers, individuals and
organizations increasingly process information digitally.
• This has led to the study of informatics that has
computational, cognitive and social aspects, including
study of the social impact of information technologies.
• Many subfields: X-informatics
Great Predictions
•
•
•
•
•
•
"Computers in the future may weigh no more than 1.5 tons.” Popular
Mechanics, forecasting the relentless march of science, 1949
"I think there is a world market for maybe five computers.” Thomas Watson,
chairman of IBM, 1943
"Heavier-than-air flying machines are impossible.” Lord Kelvin, president,
Royal Society, 1895.
"Man will never reach the moon regardless of all future scientific
advances."Dr. Lee De Forest, inventor of the vacuum tube and father of
television.
"Everything that can be invented has been invented.” Charles H. Duell,
Commissioner, U.S. Office of Patents, 1899.
“Nobody would ever need more than 640 kilobytes of memory on their
personal computer,” 1981, Bill Gates.
– Other predictions of Bill Gates?
Great Predictions
RIGHT!
•
Artificial Intelligence:
– speech recognition
– Some reasoning; computer beats man in
chess
– Privacy and security problems
– Computers can be a pain in the butt
WRONG!
•
Missed Moore’s law and ubiquity of
computers
Predicting the future
– “The future ain’t what it used to be” Yogi Berra
• Can we really predict the future?
• Who predicted the implications of the web and
search engines?
• Social networking?
• Can we understand power laws and their
implications?
– We have no examples of exponential growth in our
evolution except plagues.
• Can we understand the pervasiveness of
computers?
Everything Gets Bigger
“Screens” are larger
• Flat screen television
• Wall televisions
“Screens” are everywhere
• Every room of the house
• Waiting rooms
• Stores
• Cars
• Phones
“ The return of large data centers”
Everything Gets Smaller
• Phones
• Watches / instruments
• Computers
– embedded
• Glasses
• Projectors
Everything Gets Cheaper
• World wide cell phone penetration
– 5 Billion
• Some places 100% penetration
– 1 Billion smart phones
Everything gets smarter
• Mobile phones - the new computer
• The PDA that is really an assistant
• Digital immortality
Discussion Questions
• Is more and more information being digitized?
• Which definition of information do you prefer? Can
information be inaccurate? Can you measure it?
• Information is the message
• How is information accessed?
• Is entertainment information? Are music and games
information resources?
• What is a “fact”? Can it exist without a context? What is
objectivity?
• Can information be both explicit and implicit?
• What does the growth of information mean?
• What about Moore’s law?
Thanks to:
• Jim Gray, Microsoft
• L. Floridi, Hertfordshire
• Robert Allen, Drexel
• Wikipedia