© 2009 tefko saracevic 1 information science: where does it come from and where is it going? tefko...

© 2009 Tefko Saracevic 1

Information Science: Where does it come from

and where is it going?Tefko Saracevic, PhDSchool of Communication, & InformationRutgers UniversityNew Brunswick, New Jersey USA

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

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


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

actually, it all started long ago

In China:

Wang Zhen developed wooden movable type & published first book in 1313

In Europe Johannes Gutenberg is credited with being the first European to use movable type printing around 1439


http://en.wikipedia.org/wiki/Wang_Zhen_(official)

http://en.wikipedia.org/wiki/Johannes_Gutenberg

http://en.wikipedia.org/wiki/Movable_type

http://en.wikipedia.org/wiki/Printing


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. Digital libraries – whose are they anyhow?7. 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

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 of information explosion

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

Dealing with effects of this abundance


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

Information science: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


ElaborationKnowledge records =

content-bearing structures texts, sounds, images, multimedia, web ... ‘literature’ in given domains

Communication = human-information interaction

study of information science is the interface between people & information

Information need, seeking, and use = reason d'être

Effectiveness = relevance, utility


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

Three big questions for information science (Bates, 1999)

The design question: [Technology]How can access to recorded information be made most rapid and effective?

The physical question: [Information]What are the features and laws of the recorded information universe?

The social question: [People]How do people relate to, seek and use information?

© 2009 Tefko Saracevic 16Table 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


Streams in IR research & development

1. Information science: Services, users, use; Human-computer interaction; Cognitive aspects

2. Computer science: Algorithms, techniques Systems aspects

3. Information industry: Products, services, Web, search engines

Market aspects Problem:

relative isolation between these streams


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 Salton1927-1995

http://www.sigir.org/

http://www.sigir.org/


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, natural language processing, data mining, artificial intelligence, organization – ontologies …


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


Talking about relevance

Major objective of IR is to retrieve RELEVANT information

But what is “relevance?”Spurred many research studies in IS

manifestations, models, theories, experimental studies on people behavior, effects, criteria in judgments, variability, clues …

Still major criterion in search engines


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, incl. in Asia

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

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10667

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10667

http://mitpress.mit.edu/catalog/author/default.asp?aid=8198

http://mitpress.mit.edu/catalog/author/default.asp?aid=28068


Broadening of IR – ever changing, ever new areas added

Cross language IR (CLIR) Natural language processing (NLP IR) Specific media IR: music, spoken language, image,

video, multimedia

IR for bioinformatics, genomics, law … Categorization, clustering, filtering Information summarization & extraction Question answering Machine learning IR & database search – XML retrieval; structured

queries

Web IR; Web search engines Digital libraries


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 & IR facing many challenges lead in innovations


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

information representation large area connected with IR, librarianship metadata

bibliometricsscientometrics, informetrics, webometrics structures of literature – authors, journals… impact of authors, journals, institutions …


What is information?Intuitively well understood, but formally not well stated Several viewpoints, models emerged

Signals: transmission source-channel-destination signals not content – not really applicable, despite many tries

Cognitive: changes in cognitive structures content processing & effects

Social: context, situation dependent 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, changes in cognitive states3. 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

Informetrics all information objects

Webometrics or cybermetrics using bibliometric techniques to study the web

Major branches of bibliometricsRelational - older

Patterns, structures, relations, mappings where bibliometrics

started Data on what was

observed e.g. no. of

articles/citations by/to an author; no. of journals with articles relevant to a topic; no. of articles/citations in/to a journal …

Used for description, mapping of relations & prediction

Evaluative - newer

Impacts, effects where bibliometrics

became a big deal in many arenas

Data from what was observed but looking for measures of impact,

prominence, ranking … Discovers who’s up &

how much up Used for decisions,

policies

34© 2009 Tefko Saracevic

Major bibliometric factors for evaluation of academic performance

For individuals

Number of publications in peer reviewed journals

impact factor of those journals

Citation tracking The h-index

combines no. of publications & no. of citations

For institutions

Total no. of publications

Total no. of citations

Institutional impact factor

Various ratios - per faculty, project …


Example: University rankings Times Higher Education ranking: QS World University Rankings 2008 - Top 400 Universitieshttp://www.topuniversities.com/worlduniversityrankings/results/2008/overall_rankings/fullrankings/

Shanghai ranking: Academic Ranking of World Universities – 2007 - Shanghai Jiao Tong University http://www.arwu.org/rank/2007/ranking2007.htm Miscellaneous Information on University Rankings

http://www.arwu.org/rank/2008/200810/ARWU2008Resources.htm

Leiden ranking: Top 100 & 250 universities, Europe & world, 2008 - Leiden University, Netherlandshttp://www.cwts.nl/ranking/LeidenRankingWebSite.html


http://www.topuniversities.com/worlduniversityrankings/results/2008/overall_rankings/fullrankings/



http://www.arwu.org/rank/2007/ranking2007.htm

http://www.arwu.org/rank/2008/200810/ARWU2008Resources.htm

http://www.cwts.nl/ranking/LeidenRankingWebSite.html

SCImago Journal & Country Rank (SJR) a great resource – from Spain


http://www.scimagojr.com/

Used in a variety of functions & areas

In collection developmentidentifying the most-useful materials: by analyzing

circulation records; journal / e-journal usage statistics; etc.

In information retrievalidentifying top-ranked documents, authors: those most

highly-cited; most highly co-cited; most popular; etc. In the sociology of knowledge

identifying structural & temporal relationships between documents, authors, research areas, universities etc.

In policy makingjustifying, managing or prioritizing support for course

of action in a number of arease.g. science policy, institutional policy, promotion & tenure, grants, support for journals, evaluation of institutions

38© 2009 Tefko SaracevicTable of content

39

Part 5.

People Research

user & use studies interaction studies broadening to information seeking studies, social context, collaboration

relevance studies social informatics

Professional services in organization – moving toward knowledge management, competitive intelligence

in industry – vendors, aggregators, Internet,

© 2009 Tefko Saracevic


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

http://www.scils.rutgers.edu/~tefko/Advances_Librar_2006.pdf


Interaction and ISThree streams:

computer-human interaction human-computer interaction human-information interaction

Many studies on: machine aspects of interaction human variables in interaction interaction with information

Web interactions: a major areaAnother interdisciplinary area

computers science, information science, cognitive science, ergonomics…


Interaction & IR

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.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. Digital libraries

LARGE & growing area – many in IS involved, but also in computer science, & other fields (e.g. Perseus – classics)

“Hot” area in R&D a number of large grants & projects in the US, European Union, & other countries

but “DIGITAL” big & “libraries“ small but in the US & Europe funding is drying out

“Hot” area in practice building & managing digital collections, hybrid libraries, digitizing, preservation

many projects throughout the world


Technical problems

Substantial - larger & more complex than anticipated e.g.: 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, automating representation conversion, digitizationorganizing large collectionsmanaging collections, scalingpreservation, archivinginteroperability, standardizationaccessing, using, searching

federated searching of distributed collections evaluation of digital libraries


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

Spending increasing significantly most often a trade-off for other resources

U California, Berkeley’s Libweb “lists over 7700 pages from libraries in over 146

countries”


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 7. 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 keep progressing in its: research & development professional competencies educational efforts interdisciplinary relations

Reexamination necessary


Thank you Miró!

Thank you Picasso!


& Prof. Sam Chufor inviting me!

Thank you:


Selective 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.

© 2009 tefko saracevic 1 information science: where does it come from and where is it going? tefko...

Documents

tefko saracevicactually

base of information

problems solutions

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technological fix

technological determinant

technological solution

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