Information Science Zadar - School of Communication and
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Information Science:
Where does it come from
and where is it going?
Tefko Saracevic, PhD
School of Communication, Information and
Library Studies
Rutgers University
New Brunswick, New Jersey USA
http://www.scils.rutgers.edu/~tefko
Gutenberg
1397-1468
© Tefko Saracevic
1
Information science:
a short definition
“the collection, classification,
storage, retrieval, and
dissemination of recorded knowledge
treated both as a pure and as an
applied science”
Merriam-Webster
© Tefko Saracevic
2
Organization of presentation
1.
2.
3.
4.
5.
6.
7.
8.
9.
Big picture – problems, solutions, social place
Structure – main areas in research & practice
Technology – information retrieval – largest part
Information – representation; bibliometrics
People – users, use, seeking, context
Paradigm split – distancing of areas
Relations – librarianship, computer science
Digital libraries – whose are they anyhow?
Conclusions – big questions for the future
© Tefko Saracevic
3
Part 1. The big picture
Problems addressed
Bit of history: Vannevar Bush
(1945):
Defined problem as “... the massive
task of making more accessible of a
bewildering store of knowledge.”
Problem still with us & growing
1890-1974
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… solution
Bush suggested a machine:
“Memex ... association of ideas ...
duplicate mental processes
artificially.”
Technological fix to problem
Still with us:
technological determinant
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At the base of information science:
Problem
Trying to control content in
Information explosion
exponential growth of information
artifacts, if not of information itself
PLUS today
Communication explosion
exponential growth of means and ways by
which information is communicated,
transmitted, accesses, used
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6
technological solution, BUT …
applying technology
to solving
problems of
effective use of
information
BUT:
from a
HUMAN & SOCIAL
and not only
TECHNOLOGICAL
perspective
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or a symbolic model
People
Information
Technology
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8
Problems & solutions:
SOCIAL CONTEXT
Professional practice AND scientific
inquiry related to:
Effective communication of knowledge
records - ‘literature’ - among humans in
the context of social, organizational, &
individual need for and use of
information
Taking advantage of modern
information technology
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or as White & McCaine
(1998)
put it:
“modeling the
world of
publications
with a practical
goal of being
able to deliver
their content to
inquirers
[users] on
demand.”
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10
General characteristics
Interdisciplinarity - relations
with a number of fields, some more
or less predominant
Technological imperative - driving
force, as in many modern fields
Information society - social
context and role in evolution shared with many fields
Table of content
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11
Part 2. Structure
Composition of the field
As many fields, information science
has different areas of
concentration & specialization
They change, evolve over time
grow closer, grow apart
ignore each other, less or more
sometimes fight
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most importantly different areas…
receive more or less in funding &
emphasis
producing great imbalances in work &
progress
attracting different audiences & fields
this includes
vastly different levels of support for
research and
huge commercial investments &
applications
© Tefko Saracevic
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How to view structure?
by decomposing areas & efforts in
research & practice emphasizing
Technology
or
Informatio
n
© Tefko Saracevic
People
or
Table of content
14
Part 3.
Technology
Identified with information
retrieval (IR)
by far biggest effort and investment
international & global
commercial interest large & growing
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Information Retrieval –
definition & objective
“ IR: ... intellectual aspects of
description of information, ... search,
... & systems, machines...”
Calvin Mooers, 1951
How to provide users with relevant
information effectively?
For that objective:
1. How to organize information
intellectually?
2. How to specify the search &
interaction intellectually?
3. What techniques & systems
to use effectively?
1919-1994
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Streams in IR Res. & Dev.
1.
Information science:
Services, users, use;
Human-computer interaction;
Cognitive aspects
2.
Computer science:
Algorithms, techniques
Systems aspects; evaluation
3.
Information industry:
Products, services, Web
search engines – BIG!
Market aspects
Problem:
relative isolation – discussed later
© Tefko Saracevic
17
IR research
Started in the US
through government
support & in
information science
Now mostly done
within computer
science
e.g Special Interest
Group on IR,
Association for
Computing Machinery
(SIGIR,ACM)
© Tefko Saracevic
Gerard Salton
1927-1995
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Contemporary IR research
Spread globally
e.g. major IR research communities
emerged in China, Korea, Singapore
Branched outside of information
science - “everybody does information
retrieval”
search engines, data mining, natural
language processing, artificial
intelligence, computer graphics …
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Testing in IR
Major component of
IR made it strong &
affected innovation
Long history –
started with
Cranfield tests in
late 1950’s
Measures –
precision & recall
based on relevance
Cyril Cleverdon
1914-1997
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Text REtrieval Conference (TREC)
Major research, laboratory effort
Started in 1992,
“support research within the IR community by
providing the infrastructure necessary for largescale evaluation”
Methods
provides large test beds, queries, relevance
judgments, comparative analyses
essentially using Cranfield 1960’s methodology
organized around tracks
various topics – changing over years
© Tefko Saracevic
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TREC impact
International – big impact on creating
research communities
Annual conferences
reports, exchange results, foster cooperation
Results
mostly in reports, available at
http://trec.nist.gov/pubs.html
overviews provided as well
but, only a fraction published in journals
Book (2005):
TREC: Experiment and Evaluation in Information
Retrieval
Edited by Ellen M. Voorhees and Donna K. Harman
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TREC tracks
116 groups from 20 countries
Genomics
Spam
Blog
Question answering
Enterprise
Million query (new)
Legal
© Tefko Saracevic
Previous tracks:
ad-hoc (1992-1999)
routing (92–97)
interactive (94-02)
filtering (95-02)
cross language (97-02)
speech (97-00)
Spanish (94-96)
video (00-01)
Chinese (96-97)
query (98-00)
and a few more run for
two years only
23
Broadening of IR – sample
ever changing, ever new areas added
Cross language IR (CLIR)
Natural language processing (NLP IR)
Music IR (MIR)
Image, video, multimedia retrieval
Spoken language retrieval
IR for bioinformatics and genomics
Summarization; text extraction
Question answering
Many human-computer interactions
XML IR
Web IR; Web search engines
IR in context – big area for major
search engines & newer research
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Commercial IR
Search engines based on IR
But added many elaborations &
significant innovations
dealing with HUGE number of pages fast
countering spamming & page rank games –
adversarial IR - combat of algorithms
adding context for searching
Spread & impact worldwide
about 2000 engines in over 160 countries
English was dominant, but not any more
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Commercial IR: brave new world
Large investments & economic sector
hope for big profits, as yet questionable
Leading to proprietary, secret IR
also aggressive hiring of best talent
new commercial research centers in
different countries (e.g. MS in China)
Academic research funding is changing
brain drain from academe
Commercial search engines facing many
challenges – hiring best talent
and providing brain-drain for academics
© Tefko Saracevic
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IR successfully effected:
Emergence & growth of the INFORMATION
INDUSTRY
Evolution of IS as a PROFESSION &
SCIENCE
Many APPLICATIONS in many fields
including on the Web – search engines
Improvements in HUMAN - COMPUTER
INTERACTION
Evolution of INTEDISCIPLINARITY
IR has a long, proud history
© Tefko Saracevic
Table of content
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Part 4.
Information
Several areas of investigation;
as basic phenomenon – not much progress
measures as Shannon's not successful
concentrated on manifestations and effects
no recent progress in this basic research
information representation
large area connected with IR, librarianship
metadata
bibliometrics
structures of literature
© Tefko Saracevic
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What is information?
Intuitively well understood, but
formally not well stated
Several viewpoints, models emerged
Shannon: source-channel-destination
signals not content – not really
applicable, despite many tries
Cognitive: changes in cognitive
structures
content processing & effects
Social: context, situation
information seeking, tasks
© Tefko Saracevic
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Information in information science:
Three senses
(from narrowest to broadest)
1. Information in terms of decision involving
little or no cognitive processing
signals, bits, straightforward data - e.g.. inf.
theory (Shanon), economics,
2. Information involving cognitive processing
& understanding
understanding, matching texts, Brookes
3. Information also as related to context,
situation, problem-at-hand
USERS, USE,TASK
For information science
(including information retrieval):
third, broadest interpretation necessary
© Tefko Saracevic
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Bibliometrics
“… the quantitative treatment of the properties of
recorded discourse and behavior pertaining to it.”
Fairthorne, 1969
Many quantitative studies & some laws
Bradford’s law, Lotka’s law – regularities
quantity/yield distributions of journals, authors
also related areas:
Scientometrics
covering science in general, not just
publications
Infometrics
all information objects
Webmetrics or cybermetrics
using bibliometric techniques to study the web
© Tefko Saracevic
Table of content
31
Part 5.
People
Professional services
in organization – moving toward knowledge
management, competitive intelligence
in industry – vendors, aggregators, Internet,
Research
user & use studies
interaction studies
broadening to information seeking studies,
social context, collaboration
relevance studies
social informatics
© Tefko Saracevic
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User & use studies
Oldest area
covers many topics, methods,
orientations
many studies related to IR
e.g. searching, multitasking, browsing,
navigation
theoretical & experimental studies on
relevance
Branching into Web use studies
quantitative & qualitative studies
emergence of webmetrics
© Tefko Saracevic
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Interaction
Traditional IR model concentrates
on matching but not on user side &
interaction
Several interaction models
suggested
Ingwersen’s cognitive, Belkin’s episode,
Saracevic’s stratified model
hard to get experiments & confirmation
Considered key to providing
basis for better design
understanding of use of systems
Web interactions: a major new area
© Tefko Saracevic
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Information seeking
Concentrates on broader context not only
IR or interaction, people as they move in
life & work
Number of models provided
e.g. Kuhlthau’s information search process,
Järvelin’s information seeking
Includes studies of ‘life in the round,’
making sense, information encountering,
work life, information discovery
Based on concept of social construction
of information
© Tefko Saracevic
Table of content
35
Paradigm split in
technology - people
Part 6.
Split from early 80’s to date into:
System-centered
algorithms, TREC, search engines
continue traditional IR model
Human-(user)-centered
cognitive, situational, user studies
interaction models, some started in
TREC
relevance studies
© Tefko Saracevic
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Human vs. system
Human (user) side:
often highly critical, even one-sided
mantra of implications for design
but does not deliver concretely
System side:
mostly ignores user side & studies
‘tell us what to do & we will’
Issue NOT
H or
S
approach
even less H vs. S
but how can H AND S work together
major challenge for the future
© Tefko Saracevic
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Great separation
IR in computer
science
completely technology
oriented
VERY international
not aware at all of
the other side
SIGIR growing a lot:
2010 subm. 520
accept. 87, 16.5%
2007 subm. 490,
accept. 85, 17%
2006 subm. 399,
accept. 74, 19%
1999 subm. 135,
accept. 33, 24%
© Tefko Saracevic
IR, user studies,
services in
information science
mostly people
oriented
aware, but
participating less
with other side
only a few LIS
people come to
SIGIR, even fewer
SIGIR to ASIST, none
to ALA
38
Calls vs support
Many calls for user-centered or humancentered design, approaches & evaluation
Number of works discussing it, but few
proposing concrete solutions
But: most support for system work
in the digital age support is for digital
Recent attempt at combining two views:
Book: Ingerwersen, P. and Järvelin, K. (2005). The
Turn: Integration of information seeking and retrieval
in context. Springer.
Table of content
© Tefko Saracevic
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Relations,
alliances, competition
Part 7.
With a number of fields...
Strongest:
1. Librarianship
2. Computer science
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Common grounds
IS & librarianship share:
Social role in information
society
Concern with effective
utilization of graphic & other
types of records
Research problems related to a
number of topics
Transfer to & from information
retrieval
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Differences
IS & librarianship differ in:
Selection & definition of many
problems addressed
Theoretical questions & framework
Nature & degree of
experimentation
Tools and approaches used
Nature & strength of
interdisciplinary relations
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One field or two?
Point of many debates
Suggest: TWO fields in strong
interdisciplinary relations
Not a matter of “better” or “worse” matters little
common arguments between many fields
Differences matter in:
problem selection & definition
agenda, paradigms
theory, methodology
practical solutions, systems
Best example: IR & library automation
© Tefko Saracevic
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Which?
Librarianship. Information science
Library and information science
Libraryandinformationscience
Michael Buckland’s suggestion
Information science
Information sciences
Information
like in the “Information School”
© Tefko Saracevic
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IS & computer science
CS primarily about algorithms
IS primarily about information and its
users and use
Not in competition, but complementary
Growing number of computer scientists
active in IS – particularly in IR and
digital libraries
Concentrating on
advanced IR algorithms & techniques
digital library infrastructure & various
domains
human computer interaction
© Tefko Saracevic
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Interaction and IS
Two streams:
computer-human interaction
human-computer interaction
Many studies on:
machine aspects of interaction
human variables in interaction
Problems: little feedback between
very hard to evaluate
Web interactions: a major area
Another interdisciplinary area
computers sc., cognitive sc.,
ergonomics,
Table of content
© Tefko Saracevic
46
Part 8.
Digital libraries
LARGE & growing area
“Hot” area in R&D
a number of large grants & projects in
the US, European Union, & other
countries
but “DIGITAL” big & “libraries“ small
“Hot” area in practice
building digital collections, hybrid
libraries,
many projects throughout the world
but in the US funding has dryed out
© Tefko Saracevic
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Technical problems
Substantial - larger & more complex
than anticipated:
representing, storing
library objects
& retrieving of
particularly if originally designed to be
printed & then digitized
operationally managing large collections issues of scale
dealing with diverse & distributed
collections
interoperability; federated searching
assuring preservation & persistence
incorporating rights management
© Tefko Saracevic
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Research issues
understanding objects in DL
representing in many formats
metadata, cataloging, indexing
conversion, digitization
organizing large collections
managing collections, scaling
preservation, archiving
interoperability, standardization
accessing, using, searching
federated searching of distributed collections
evaluation of digital libraries
© Tefko Saracevic
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DL projects in practice
Heavily oriented toward
institutions & their missions
in libraries, but also others
museums, societies, government, commercial
come in many varieties
Spread globally
including digitization
U California, Berkeley’s Libweb
“lists over 8000 pages from libraries in over
146 countries”
Spending increasing significantly
often a trade-off for other resources
© Tefko Saracevic
50
Connection?
DL research & DL
practice presently are
conducted
mostly independently
of each other
minimally informing
each other
and having slight, or
no connection
Parallel universes with
little connections &
interaction, at present
not good for either
research or practice
© Tefko Saracevic
Table of content
51
Part 9. Conclusions
IS contributions
IS effected handling of information in
society
Developed an organized body of
knowledge & professional competencies
Applied interdisciplinarity
IR reached a mature stage
penetrated many fields & human activities
Stressed HUMAN in human-computer
interaction
© Tefko Saracevic
52
Challenges
Adjust to the growing & changing social &
organizational role of inf. & related inf.
infrastructure
Play a positive role in globalization of
information
Respond to technological imperative in human
terms
Respond to changes from inf. to
communication explosion - bringing own
experiences to resolutions, particularly to
the web
Join competition with quality
Join DIGITAL with LIBRARIES
© Tefko Saracevic
53
Juncture
IS is at a critical juncture in its
evolution
Many fields, groups ... moving into
information
big competition
entrance of powerful players
fight for stakes
To be a major player IS needs to progress
in its:
research & development
professional competencies
educational efforts
interdisciplinary relations
Reexamination necessary
© Tefko Saracevic
54
Thank you Miró!
Thank you Picasso!
© Tefko Saracevic
55
Hvala Tatjana &
na pozivu!
© Tefko Saracevic
56
Bibliography
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Journal of the American Society for Information Science,50, 10431050.
Bush, V. (1945). As We May Think. Atlantic Monthly, 176, (11), 101108. Available:
http://www.theatlantic.com/unbound/flashbks/computer/bushf.htm
Hjørland, B. (2000). Library and Information Science: Practice,
Theory, and Philosophical Basis. Information Processing &
Management, 36 (3), 501-531.
Pettigrew, K.E. & McKechnie, L.E.F. (2000). The use of theory in
information science research. Journal of the American Society for
Information Science and Technology, 52 (1), 62 - 73.
Saracevic, T. (1999). Information Science. Journal of the American
Society for Information Science, 50 (9) 1051-1063. Available:
http://www.scils.rutgers.edu/~tefko/JASIS1999.pdf
Saracevic, T. (2005). How were digital libraries evaluated?
Presentation at the course and conference Libraries in the Digital
Age (LIDA)30 May-3 June 2005, Dubrovnik, Croatia. Available:
http://www.scils.rutgers.edu/~tefko/DL_evaluation_LIDA.pdf
Webber, S. (2003) Information Science in 2003: A Critique. Journal of
Information Science, 29, (4), 311-330.
White, H. and Mc Cain, K. (1998). Visualizing a Discipline: An Author
Co-citation Analysis of Information Science 1972-1995. Journal of
the American Society for Information Science, 49 (4), 327-355.
© Tefko Saracevic
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