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
© Tefko Saracevic
4
… 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
© Tefko Saracevic
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technological solution, BUT …
applying technology
to solving
problems of
effective use of
information
BUT:
from a
HUMAN & SOCIAL
and not only
TECHNOLOGICAL
perspective
© Tefko Saracevic
7
or a symbolic model
People
Information
Technology
© Tefko Saracevic
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
© Tefko Saracevic
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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.”
© Tefko Saracevic
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
© Tefko Saracevic
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
© Tefko Saracevic
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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
© Tefko Saracevic
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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
© Tefko Saracevic
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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
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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 …
© Tefko Saracevic
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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
© Tefko Saracevic
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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
© Tefko Saracevic
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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
© Tefko Saracevic
24
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
© Tefko Saracevic
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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
27
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
© Tefko Saracevic
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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
© Tefko Saracevic
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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”
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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
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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
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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
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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
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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
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Thank you Miró!
Thank you Picasso!
© Tefko Saracevic
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Hvala Tatjana &
na pozivu!
© Tefko Saracevic
56
Bibliography
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http://www.theatlantic.com/unbound/flashbks/computer/bushf.htm
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Theory, and Philosophical Basis. Information Processing &
Management, 36 (3), 501-531.
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http://www.scils.rutgers.edu/~tefko/JASIS1999.pdf
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Age (LIDA)30 May-3 June 2005, Dubrovnik, Croatia. Available:
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