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Katherine W. McCain*, June M. Verner, Gregory W. Hislop, William Evanco, & Vera Cole. College of Information Science & Technology Drexel University Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

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Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain. Katherine W. McCain*, June M. Verner, Gregory W. Hislop, William Evanco, & Vera Cole. College of Information Science & Technology Drexel University. KATE'S. PHILADELPHIA. BRAND. BIBLIOMETRICS. - PowerPoint PPT Presentation

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Page 1: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Katherine W. McCain*, June M. Verner, Gregory W. Hislop, William Evanco, & Vera Cole.

College of Information Science & TechnologyDrexel University

Combining Bibliometric and Knowledge Elicitation Techniques to Map a

Knowledge Domain

Page 2: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

PHILADELPHIABRAND

BIBLIOMETRICS

KATE'S

Page 3: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

PHILADELPHIA brand BibliometricsOrganizations

ISI: Gene Garfield, Henry SmallDrexel: Belver Griffith, Howard White, Chaomei Chen, Xia Lin, Carl Drott, Jackie Mancall, and a host of grad studentsCenter for Research Planning: Dick Klavans, Len Simon

Major themes: citation analysis/core literatures; aging of scholarly literatures; single period and longitudinal studies of scholarly literatures and fields; real-time, on-the-fly mapping of literatures, fields, paradigm shifts, vocabulary structures, etc.; bibliometric applications in collection management, competitive intelligence, institutional evaluation, etc.

Page 4: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

AGENDAIntroduction: Domain analysis & software engineeringMapping methods:

Author Cocitation AnalysisKnowledge Elicitation – card sorting

ResultsACA clusters & mapPFNet author networkCard sorting clusters & map

Comparisons of ACA and KE resultsConclusions

Page 5: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

DOMAIN ANALYSIS

SYSTEMS ANALYSIS: the task of identifying the operations and objects needed to specify information processing in a particular application domain

INFORMATION SCIENCE: the study of the field (knowledge domain) as a thought or discourse community. It focuses on such topics as knowledge organization, structure, cooperation patterns, language and communication forms, information systems, and relevance criteria as a way of understanding these communities (Hjørland, B., & Albrechtsen, H. (1995)

Page 6: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

An Aside On DISCOURSE COMMUNITY

a common public goal or goalsa body of specialized knowledge mechanisms of intercommunication and participationa genre (e.g. scholarly journal)a specialized vocabulary

A group (likely to be geographically dispersed) who share:

Adapted from John Swales, Genre Analysis (1990 Cambridge)

Page 7: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

SOFTWARE ENGINEERING

The establishment and use of sound engineering principles in order to obtain economically software that is reliable and works efficiently on real machines. the technological and managerial discipline concerned with systematic production and maintenance of software products that are developed and modified on time and within cost estimates

Page 8: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

DOMAIN ANALYSIS OF SOFTWARE ENGINEERING

a study of the journal literature of software engineering, based on both author referencing patterns and index term assignments a study of the factors that affect the “visibility” of software engineering authors an INSPEC-based co-descriptor mapping of software engineeringa conjoint study of the intellectual and cognitive structure of software engineeringCitation content analysis of Brooks’ Mythical Man-Month

Page 9: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

TWO APPROACHES TO MAPPING SE

BIBLIOMETRICS: Cocited author mapping uses the patterns of co-occurrence of authors’ names in reference lists to examine the intellectual structure of scholarly literatures and, by extension, the fields that produce those literatures KNOWLEDGE ELICITATION: the process of collecting from a human source of knowledge, information that is thought to be relevant to that knowledge. [Cooke]

Card sorting: structural analysis of mental models elicited via sorting named cards into piles

Page 10: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

AUTHOR COCITATION ANALYSIS

AUTHOR SELECTION: authors highly cited in texts and in the core SE literature = 60 authors selected for studyCOCITATION DATA GATHERED: cocitation counts retrieved from SCISEARCH, 1990 – 1997ANALYSIS:

Raw cocitation counts -- PFNetsCorrelation matrix – cluster analysis & multidimensional scaling

Page 11: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

60 AUTHORS

Abdel-Hamid, Tarek K.

Albrecht, Allan J.

Basili, Victor R.

Beizer, Boris

Biggerstaff, Ted J.

Boehm, Barry W.

Booch, Grady

Brooks, Frederick P., Jr.

Card, David N.

Clarke, Lori A.

Coad, Peter

Curtis, Bill

David, Allan M.

DeMarco, Tom

Dijkstra, Edsger W.

Fagan, M. E.

Fenton, Norman E.

Garlan, David

Ghezzi, Carlo

Gilb, Tom

Glass, Robert L.

Goldberg, Adele

Gomaa, Hassan

Grady, Robert B.

Harrison, W.

Hoare, C.A.R

Humphrey, Watts S.

Jackson, Michael A.

Jacobson, Ivar

Jones, T. Capers

Kaiser, G. E.

Kemerer, C. F.

Kernighan, Brian W.

Kitchenham, Barbara A.

Lehnman, M. M.

McCabe, Thomas J.

Meyer, Bertrand

Mills, Harlan D.

Musa, John D.

Myers, Glenford J.

Parnas, David L.

Pfleeger, Shari L.

Pressman, Roger S.

Prieto-Diaz, R.

Ramamoorthy, C. V.

Rombach, H. D.

Rumbaugh, James

Selby, R. W.

Shaw, Mary

Shepperd, M.

Shneiderman, Ben

Sommerville, Ian

Tichy, W. F.

Tracz, Will

Wasserman, A. I.

Weiser, M.

Weyuker, Elaine J.

Wing, Jeanette, M.

Yourdon, Edward

Zave, Pamela

Page 12: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

1. 1982 Brooks, FP... 2. 1987 Brooks, FP... 3. 4. 5. 1981 Jones, TC.. 6. 7. 1973 Pfleeger, S... 8. 1984 Weyuker, E 9. 10.

CITATIONS

Source Papers

CA = BROOKS FP AND CW = JONES TC *

CA = BROOKS FP AND CA = PFLEEGER S

Retrieval Strategy *

* Multiple forms of authors' names were used in the search strategies

558 338 271 1392

1333 1213

Raw Cocitation MatrixBROOKS FP

DIJKSTRA E

GLASS RL

JONES TC

HUMPHREY W

WEYUKER E

BASILI V 831

367 118 288

159 333 197 106 639

74 66 9 129 2249 230

BASI

LI V

BRO

OK

S FP

DIJ

KST

RA E

GLA

SS R

L

JON

ES T

C

HU

MPH

REY

W

ALB

RECH

T W

32 5 15 8 363 14 1276

Data Gathering for ACA

Page 13: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Analytical Tools for Raw Cocitation counts

Page 14: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Analytical Tools for Proximity Matrix

Page 15: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

ACA ANALYSESRaw Cocitation Matrix

PFNet: links nodes (authors) based on their single highest co-occurrence counts. The result is generally a network structure with some authors appearing as major foci (many links to others) representing specialties

Correlation MatrixHierarchical cluster analysis: 8 cluster solution identifies major subject clustersMultidimensional scaling: 2 dimensional map shows overall structure and major themes

Page 16: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Knowledge Elicitation Methods

Interviews and observation Process tracing (e.g. protocol analysis) Conceptual techniques

Card sorting is a conceptual technique that can be done alone or combined with semi-structured interviews.

Page 17: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Card Sorting

Software engineers contacted via e-mail, invited to participate in studyTask: sort cards bearing authors’ names into piles, label piles, complete short questionnaire

As many piles as desiredPiles with single authorsPile of “don’t know” or “aren’t software engineers

46 respondents participated in postal mail study (a few interviews)

Page 18: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Brooks, F.

Stack of cards with authors' name sent to respondents with instructions

Don't Know

MetricsFormal Methods

Cards were sorted into piles and labeled, based on respondents' perceptions

7

0 1

0 1 8

1 2 5 37

0 0 30 4 3

7 28 0 0 1 0

0 0 3 2 1 1 2

BOOCH

DIJKSTRA

HOARE

JACOBSON

PFLEEGER

SOMMERVILLE

BASILIA

BD

EL-

HA

MID

BA

SIL

I

BO

OC

H

DIJ

KS

TRA

HO

AR

E

PFL

EE

GE

R

JAC

OB

SO

N

RAW "CO-PILE" COUNTS

Card Sorting Procedure

Page 19: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

CARD SORTING ANALYSES(correlation matrix)

Hierarchical cluster analysis—8 cluster levelMultidimensional scaling – 2 dimensional map

Page 20: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

•Goldberg

•Meyer

•Ghezzi

•Rumbaugh

•Booch•Coad•

Jacobson

•Hoare

•Wing

•Kernighan

•Dijkstra

•Tichy

•Kaiser

•Jackson

•Tracz

•Shaw

•Biggerstaff

• Davis

•Prieto-Diaz

•Zave

• Wasserman

•Parnas

•Gomaa

•Weiser

•Yourdon

•Jones

•Sommerville•Shneiderman

• Ramamoorthy

•Brooks•

Pressman

•Mills

•Lehman

•Glass

• Harrison

•Clarke

•Boehm

•Curtis

•Myers

•Humphrey

•Abdel-Hamid

•Albrecht

•Pfleeger

•Gilb

•Kemerer

•Beizer

•Basili

•Musa

•Selby•Fagan

•Grady

•Rombach

•Weyuker

•Fenton

•McCabe

•• Card

•Shepperd

DeMarco

Garlan

Kitchenham

Cocitation Map of 60 Highly Cited Authors in Software Engineering

1990 - 1997

LOW FORMALSW ARCHITECTURE/ SW REUSE

OBJECT-ORIENTED ANALYSIS & DESIGN/ PROGRAMMING

FORMAL APPROACHES TO DEVELOPMENT/ FORMAL METHODS

SYSTEMS ANALYSIS & DESIGN

SW TESTING/ RELIABILITY

SW METRICS

SW PERFORMANCE

MACRO LEVEL

SW PROJECT MGT

MICRO LEVEL

Page 21: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

ABDEL-HAMID

ALBRECHT

BASILI

BEIZER

BIGGERSTAFF

BOEHM

BOOCH

BROOKS

CARD

CLARKE

COAD CURTIS

DAVIS

DEMARCO

DIJKSTRA

FAGAN

FENTON

GARLAN

GHEZZI

GILB GLASS

GOLDBERG

GOMAA

GRADY

HARRISON

HOARE

HUMPHREY

JACKSONJACOBSON

JONES

KAISERKEMERER

KERNIGHAN KITCHENHAMLEHMAN

MCCABE

MEYER

MILLS

MUSA

MYERS

PARNAS

PFLEEGER

PRESSMAN

PRIETO-DIAZ RAMAMOORTHY

ROMBACH

RUMBAUGH

SELBYSHEPPERD

SHAW

SHNEIDERMAN

SOMMERVILLE

TICHY

TRACZ

WASSERMAN

WEISER

WEYUKER

WING

YOURDON

ZAVE

PFNet of Raw Cocitation Counts for 60 Software Engineering Authors

1992 - 1997.

Page 22: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain
Page 23: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Comparisons: ACA and KE

Cluster similarity – most authors in similar clusters in terms of membership. Some differences in labeling There are differences between the way authors’ works are cited and the way the authors are perceived in terms of labels (known for textbook writing, cited for specific textbook content)

Page 24: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

CARD SORTING CLUSTERS COCITATION CLUSTERS JONES BASILI BASILI PFLEEGER PFLEEGER ROMBACH ROMBACH SW METRICS CARD CARD SW METRICS MCCABE MCCABE GRADY GRADY FENTON FENTON KITCHENHAM KITCHENHAM HARRISON HARRISON SELBY SELBY SHEPPERD SHEPPERD KEMERER WEYUKER ALBRECHT KEMERER ALBRECHT

SE MANAGEMENT BOEHM BOEHM

PROCESS MODELING GILB GILB SE PROJECT CURTIS CURTIS MANAGEMENT HUMPHREY HUMPHREY ABDUL-HAMID ABDUL-HAMID LEHMAN LEHMAN BROOKS

Page 25: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

CARD SORTING CLUSTERS COCITATION CLUSTERS GARLAN JONES RAMAMOORTHY DAVIS FORMAL DIJKSTRA DIJKSTRA FORMAL METHODS/ METHODS/ HOARE HOARE FORMAL APPROACHES SW ARCHITECTURE PARNAS PARNAS SHAW SHAW WING WING ZAVE ZAVE GHEZZI GHEZZI KERNIGHAN KERNIGHAN OBJECT ORIENTED BOOCH BOOCH OO ANALYSIS PROGRAMMING & RUMBAUGH RUMBAUGH & DESIGN DESIGN JACOBSON JACOBSON PROGRAMMING MEYER MEYER COAD COAD GOLDBERG GOLDBERG SHNEIDERMAN SE METHODOLOGIES/ PRESSMAN PRESSMAN SYSTEMS ANALYSIS SE TEXTS SOMMERVILLE SOMMERVILLE & DESIGN DEMARCO DEMARCO YOURDON YOURDON WASSERMAN WASSERMAN GOMAA GOMAA JACKSON JACKSON BROOKS GLASS MILLS MYERS DAVIS

Page 26: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

CARD SORTING CLUSTERS COCITATION CLUSTERS BIGGERSTAFF BIGGERSTAFF SW REUSE TRACZ TRACZ SW ARCHITECTURE PRIETO-DIAZ PRIETO-DIAZ SW REUSE KAISER SW TOOLS & KAISER TICHY ENVIRONMENTS TICHY GARLAN

Page 27: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Comparisons: ACA and KE

Map similarity – similar distribution of authors and clusters along X-axis (r=0.73) but not along Y-axis (r=-0.08)The most important structural theme in Software Engineering, the “micro macro” dimension, exists in both citation patterns and in perceptions of the field by citing authors. Along the Y-axis, citing patterns focus on the content of authors’ work while general perceptions include more aspects of the authors’ personae.

Page 28: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Conclusions

Boehm, Basili, Booch, and Hoare are central figures in the Software Engineering R&D literature; we can identify other authors as probable linkers between research specialties. The main organizing principle in SE is a continuum of activities related to the process of software design, development, and evaluation. Key specialties in Software Engineering (in the decade of the 1990s) included Object-Oriented Programming, Analysis & Design, Formal Methods, Software Reuse, Software Testing & Reliability, Software Process Management, and Software Metrics.

Page 29: Combining Bibliometric and Knowledge Elicitation Techniques to Map a Knowledge Domain

Conclusions

ACA (mapping, PFNets) and KE (cardsorting) provide complementary views of software engineering. KE methods increase our understanding of the domain by capturing subjects’ mental models of the domain and providing additional information about mapped entities ACA and KE provide useful cross-validation. The structure of the literature as seen through networks of author indebtedness (citation of previous work) is a good reflection of their mental models of the field, the place of the (cited) authors, and the relationships among their contributions