© Tefko Saracevic 1 Information Science: Where does it come from and where is it going? Tefko...

© Tefko Saracevic 1

Information Science: Where does it come from

and where is it going?Tefko Saracevic, PhDSchool of Communication, Information and Library StudiesRutgers UniversityNew Brunswick, New Jersey USA

http://www.scils.rutgers.edu/~tefko

Gutenberg1397-1468




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

http://www.m-w.com/cgi-bin/dictionary?book=Dictionary&va=information+science&x=16&y=13


Organization of presentation

1. Big picture – problems, solutions, social place2. Structure – main areas in research & practice3. Technology – information retrieval – largest part4. Information – representation; bibliometrics5. People – users, use, seeking, context6. Paradigm split – distancing of areas7. Relations – librarianship, computer science8. Digital libraries – whose are they anyhow?9. Conclusions – big questions for the future


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

http://www.theatlantic.com/doc/194507/bush




… solution

Bush suggested a machine: “Memex ... association of ideas ... duplicate mental processes artificially.”

Technological fix to problemStill with us: technological determinant


At the base of information science:Problem

Trying to control content inInformation explosion

exponential growth of information artifacts, if not of information itself

PLUS todayCommunication explosion

exponential growth of means and ways by which information is communicated, transmitted, accesses, used


technological solution, BUT …

applying technology to solving problems of effective use of information

BUT:from a

HUMAN & SOCIALand not only TECHNOLOGICAL perspective


or a symbolic model

Information

Technology

People


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


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.”


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


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


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


How to view structure?by decomposing areas & efforts in research & practice emphasizing

Technology

Information

or

People

or

Table of content


Identified with information retrieval (IR) by far biggest effort and investment international & global commercial interest large & growing

Part 3.

Technology


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

http://www.cbi.umn.edu/collections/inv/cbi00081.html

http://www.cbi.umn.edu/collections/inv/cbi00081.html


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


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) Gerard Salton

1927-1995


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 …


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


Text REtrieval Conference (TREC)

Major research, laboratory effortStarted in 1992,

“support research within the IR community by providing the infrastructure necessary for large-scale 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

http://trec.nist.gov/


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 RetrievalEdited by Ellen M. Voorhees and Donna K. Harman

http://trec.nist.gov/pubs.html


TREC tracks 2007116 groups from 20 countries

Genomics Spam Blog Question answering Enterprise Million query (new) Legal

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


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


Commercial IR

Search engines based on IRBut 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


Commercial IR: brave new worldLarge 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


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

Table of content


Part 4.

InformationSeveral 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


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


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, Brookes3. Information also as related to context,

situation, problem-at-hand USERS, USE,TASK

For information science (including information retrieval):

third, broadest interpretation necessary


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

Table of content


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


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


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

http://www.db.dk/pi/iri/

http://www.db.dk/pi/iri/

http://www.scils.rutgers.edu/~tefko/ProcASIS1997.doc

http://www.scils.rutgers.edu/~tefko/ProcASIS1997.doc


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

Table of content


Part 6. Paradigm split in technology - people

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


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


Great separation

IR in computer science completely technology oriented

VERY international not aware at all of the other side

SIGIR growing a lot: 2007 subm. 490,

accept. 85, 17% 2006 subm. 399,

accept. 74, 19% 1999 subm. 135,

accept. 33, 24%

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


Calls vs support

Many calls for user-centered or human-centered 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


Part 7. Relations, alliances, competition

With a number of fields...Strongest:

1. Librarianship

2. Computer science


Common grounds

IS & librarianship share:Social role in information societyConcern with effective utilization of graphic & other types of records

Research problems related to a number of topics

Transfer to & from information retrieval


Differences

IS & librarianship differ in:Selection & definition of many problems addressed

Theoretical questions & frameworkNature & degree of experimentation

Tools and approaches usedNature & strength of interdisciplinary relations


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


Which?

Librarianship. Information scienceLibrary and information scienceLibraryandinformationscience

Michael Buckland’s suggestion

Information scienceInformation sciencesInformation

like in the “Information School”


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


Interaction and ISTwo 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 areaAnother interdisciplinary area

computers sc., cognitive sc., ergonomics,

Table of content


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 drying out


Technical problems

Substantial - larger & more complex than anticipated: representing, storing & retrieving of library objects

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


Research issuesunderstanding objects in DL

representing in many formatsmetadata, cataloging, indexingconversion, digitizationorganizing large collectionsmanaging collections, scalingpreservation, archivinginteroperability, standardizationaccessing, using, searching

federated searching of distributed collections evaluation of digital libraries

http://www.scils.rutgers.edu/~tefko/DL_evaluation_LIDA.pdf


DL projects in practiceHeavily 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 7700 pages from libraries in over 145 countries”

Spending increasing significantly often a trade-off for other resources

http://lists.webjunction.org/libweb/


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

Table of content


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


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


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


Thank you Miró!

Thank you Picasso!

http://www.artcyclopedia.com/artists/miro_joan.html

http://www.artcyclopedia.com/artists/miro_joan.html


Thank you Javier &

for inviting me!


Bibliography

Bates, M. J. (1999). Invisible Substrate of Information Science. Journal of the American Society for Information Science,50, 1043-1050.

Bush, V. (1945). As We May Think. Atlantic Monthly, 176, (11), 101-108. 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.

http://www.theatlantic.com/unbound/flashbks/computer/bushf.htm

http://www.scils.rutgers.edu/~tefko/JASIS1999.pdf

http://www.scils.rutgers.edu/~tefko/DL_evaluation_LIDA.pdf

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