Visualizing the Invisible: Application of Knowledge Domain Visualization to the Longstanding Problem of Professional Conceptualization in Emergency Management

8/10/2019 Visualizing the Invisible: Application of Knowledge Domain Visualization to the Longstanding Problem of Profession

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Visualizing the Invisible ______________________________________________________________________________________________________

Application of Knowledge Domain Visualization to theLongstanding Problem of Disciplinary and ProfessionalConceptualization in Emergency and Disaster Management

Joseph George Martin III


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Copyright 2012-2014 by Joseph George Martin III

All rights reserved.

Cover Image: Part of a 725-node Author Co-Citation (ACA) Network created by the author from2930 articles in Emergency and Disaster Management, 1994-2013.


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VISUALIZING THE INVISIBLE:

Application of Knowledge Domain Visualization to the Longstanding Problem of Disciplinaryand Professional Conceptualization in Emergency and Disaster Management

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AMERICAN PUBLIC UNIVERSITY SYSTEMCharles Town, West Virginia

VISUALIZING THE INVISIBLE: APPLICATION OF KNOWLEDGE DOMAIN VISUALIZATION TO THELONGSTANDING PROBLEM OF DISCIPLINARY AND PROFESSIONALCONCEPTUALIZATION IN EMERGENCY/DISASTER MANAGEMENT

A thesis submitted in partial fulfillment of therequirements for the degree of

MASTER OF ARTSin

EMERGENCY AND DISASTER MANAGEMENTby


Department Approval Date:December 20, 2012

The author hereby grants the American Public University System the right to display thesecontents for educational purposes.

The author assumes total responsibility for meeting the requirements set by United StatesCopyright Law for the inclusion of any materials that are not the authors creation or in the

public domain.

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DEDICATION

This thesis is dedicated with love to my parents, family, and dear friends: Mom, Mary, Jeff,Sheryl, Ashley, Alex, Stacy, Jen, Randy, Peggy, Cindy, and many others both present and long past.

It has been a long road and you have all helped make completion of the journey to this pointpossible. Most of all, however, this work is dedicated with much love, and some sadness, to thememories of my father, Joseph George Martin, Jr., who lived to see this thesis beginning but notits finish; and my stepfather, William A. Bill Carlson, who passed away less than a month afterthe final version was accepted. This is for you both and I hope it makes you proud...

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ACKNOWLEDGMENTS

I would like to gratefully thank my thesis advisor, Dr. James Smith, for his time, patience,enthusiasm, and understanding throughout the past four months. There were a couple of times I

was unsure if me and this thesis would make it across the finish line, but Dr. Smith did not waiverin his confidence. I would also like to thank the outstanding faculty of American MilitaryUniversity who have made the past two years of study a pleasure, especially Dr. Randall Cuthbert,Dr. Katie Crosslin, and Dr. Tim Bagwell. Thank you to Claire Rubin as well for her thoughtfulquestions, comments, and support. Thank you to Dr. Chaomei Chen, of Drexel University, notonly for taking the time to offer helpful comments and suggestions, but for also making hisincredible KDViz software freely available to the world. Gratitude is also owed to the University ofTexas at Dallas (and its fine staff of librarians) for allowing access to the Web of Science, without

which this thesis would have not been possible. Finally, I would be remiss if I did not say thankyou to my employer (you know who you are...) who has shown infinite flexibility andunderstanding in not only putting up with the demands and neuroses of a graduate studentcompleting a thesis, but continuing to pay me while doing so.

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ABSTRACT OF THE THESIS

VISUALIZING THE INVISIBLE: APPLICATION OF KNOWLEDGE DOMAINVISUALIZATION TO THE LONGSTANDING PROBLEM OF DISCIPLINARY AND

PROFESSIONAL CONCEPTUALIZATION IN EMERGENCY/DISASTERMANAGEMENT

By


American Public University System, December 20, 2012

Charles Town, West Virginia

Professor James Smith, Thesis Professor

The status of emergency and disaster management (EDM) as an academic and professionaldiscipline remains one of the fields lingering, unresolved questions. A majority of the literatureappears to support the claim that emergency management either is, or is in the process of becoming,a recognized academic and professional discipline. The claims key belief is that the field possessesa unique body of knowledge, an essential conceptual requirement for disciplinary status. This thesisexamines the concept of professional/academic disciplines, as it relates to bodies of knowledge, andmore specifically, the EDM body of knowledge. The technique of knowledge domain visualization(KDViz) using co-citation analysis is discussed. Analysis and visualization of the disaster literatureis conducted using CiteSpace II, a KDViz software program, and a dataset of 2385 EDM articles,1994-2011, obtained through the Web of Science bibliographic database. Results are presented anddiscussed within the context of both practical and theoretical concerns affecting not only EDM,but the entire field of disaster studies.

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TABLE OF CONTENTS

PAGE ACKNOWLEDGEMENTS. ........................................................................................v ABSTRACT.................................................................................................................viLIST OF TABLES ......................................................................................................viiiLIST OF FIGURES.....................................................................................................ix

I. INTRODUCTION..............................................................................................1Statement of the problem..........................................................................2Nature, purpose and significance of study.................................................3Research questions and hypotheses............................................................4

Assumptions and limitations.....................................................................5Organization of remainder of paper..........................................................6

II. LITERATURE REVIEW. ....................................................................................8Conceptualizing professional and academic disciplines.............................8Disciplinary status and the body of knowledge in EDM.........................10Bibliometrics, co-citation, KDViz, and CiteSpace II...............................14

III. METHODOLOGY. ..........................................................................................21Design and rationale..............................................................................21Dataset construction..............................................................................22Pre-analysis CiteSpace II Settings...........................................................28Quantitative and qualitative analysis procedures....................................34

.IV. RESULTS...........................................................................................................37

General results........................................................................................37 Author Co-Citation Analysis (ACA).......................................................39Document Co-Citation Analysis (DCA).................................................47 Journal Co-Citation Analysis (JCA)........................................................54

V. DISCUSSION AND CONCLUSIONS.............................................................61

General findings of the analyses..............................................................61Research hypotheses and questions.........................................................61Creating a disciplinary framework..........................................................65Recommendations for further study.......................................................65

REFERENCES..........................................................................................................68 APPENDIX A: SAMPLE OF ORIGINAL WEB OF SCIENCE DATA..................73 APPENDIX B: SAMPLE OF FINAL DATASET (ACA VERSION).......................76

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LIST OF TABLES

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1. FEMA Body of Knowledge Project Top Recommended Readings, 2006-2009..................132. Selected Co-citation/Knowledge Domain Visualization Studies.........................................16

3. Journals Used in the Dataset..............................................................................................264. Summary of Dataset Characteristics...................................................................................265. Ten Most Cited (per WoS) Source Articles in Dataset.......................................................296. CiteSpace II Analysis Settings............................................................................................367. CiteSpace II Network and Cluster Analysis Results............................................................388. ACA: Fifteen Most Cited Individual First Authors, 1994-2011 (All Citations)..................409. ACA: Fifteen Most Cited Individual First Authors, 1994-2011 (Unique Instances)...........4010. ACA: Fifteen Most Cited Agency Authors, 1994-2011 (All Citations)...............................4111. ACA: Fifteen Most Cited Agency Authors, 1994-2011 (Unique Instances)........................4112. ACA: Top Fifteen Authors (Combined) Ranked by Sigma, 1994-2011..............................4213. DCA: Fifteen Most Cited References, 1994-2011..............................................................4714. DCA: Top Ten Cited References Ranked by Sigma, 1994-2011........................................6915. JCA: Twenty-five Most Cited Journals/Book Series, 1994-2011 (Unique Instances)..........5516. JCA: Top Ten Journals/Book Series Ranked by Sigma, 1994-2011....................................56

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LIST OF FIGURES

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1. Screenshot of CiteSpace II Control and Visualization Panels.............................................182. Basic visualization concepts used in CiteSpace II...............................................................193. Distribution of articles in dataset by year...........................................................................244. Distribution of dataset articles WoS times cited................................................................275. Threshold settings in CiteSpace II: number of nodes.........................................................326. Threshold settings in CiteSpace II: number of links...........................................................337. Author Co-citation Analysis (ACA) merged network, 1994-2011......................................438. Close-up of core concentration of authors in ACA network...............................................449. ACA network visualization with topic/subject/concept labels.............................................4510. Evolution of the ACA network, 1994-2011.......................................................................4611. Document Co-citation Analysis (DCA) merged network, 1994-2011................................4912. Close-up of lower right quadrant of super-cluster in DCA network....................................50

13. Super-cluster at center of DCA visualization, with labels....................................................5114. Close-up of densest part of DCA network, with labels........................................................5215. Evolution of the DCA network, 1994-2010.......................................................................5316. Journal Co-citation Analysis (JCA) merged network, 1994-2011.......................................5717. Close-up of lower right section of JCA visualization...........................................................5818. Close-up of center right section of JCA visualization..........................................................5919. Evolution of JCA network, 1994-2010..............................................................................6020. Possible disciplinary structure for Disaster Studies and Sciences.........................................6621. Preliminary framework for the discipline of Disaster Studies and Sciences.........................67

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CHAPTER I INTRODUCTION

That the field of disasters as an academic and occupational pursuit, including what has becomeknown as emergency management (EM), or emergency and disaster management (EDM)1, has comeof age in the last quarter-century, is a statement unlikely to generate significant disagreement. Theprogress would be hard to deny. Born of the Cold Wars vision of civil defense, the fledgling conceptof emergency management survived a neglected childhood as an often poorly staffed, poorly funded,and poorly understood function of local, state, and federal government. Today, as disasters seem togrow in number, size, scope, and impacts at a worrying rate with each passing year, the field entersyoung adulthood. Where it was once more of an afterthought, it is now almost impossible to imaginea future without EDM. In the United States, EDM now exists in some form at every jurisdictionallevel of government, and significant strides have been made in moving EDM from being primarily aninterest of the public sector to being an interest of both the public and private sectors. EDM has alsogrown in acceptance as a valid academic subject area, with a firm foothold now established in higher

education at the undergraduate and graduate level. Finally, in the occupational arena, two nationalassociations (the National Emergency Managers Association [NEMA] and the International Associationof Emergency Managers [IAEM]) exist to promote/advance EDM as a career, as well as provide supportto those currently employed in EDM or a related area.

The rapid progress the field has enjoyed recently in development as an occupation and academicarea of study is not, however, without downside. Such rapid progress and development has potentialto diminish the perceived need to address necessary but difficult issues within the field. Quarantelli(1998/2005a), then Perry and Quarantelli (2005), have twice demonstrated with the same simple (andstill unresolved) question that the very focal point of the field lacks a generally accepted definition. It isentirely conceivable that some, seeing the positive growth and expansion of EDM, might find the needto reach some acceptable working solution to the question of What is a disaster? an unnecessarydefinitional quest. Or perhaps the issue, it might be optimistically felt, will work itself out as the fieldcontinues evolving with time. But Quarantelli and Perrys definitional question is quietly deceptive. Itis not simply a question of definition. It is actually a fundamental question of structure: how one definesdisaster determines what is and is not part of the field. The definitional issue of disasters, however, isnot the only unresolved fundamental structural question within EDM.

Over the course of the past fifteen or so years, unresolved questions have arisen in the literatureabout the disciplinary and professional status of EDM. On the one hand are authors like Darlington(n.d.) and key figures like Mileti (as related by Phillips (2003)), who believe that there is both an

academic discipline and either an outright profession, or at the very least, a profession-in-the-making.1 For the purposes of the first two chapters, emergency and disaster management or EDM refers to both an

academic area of study and an occupational area, and is broadly construed for the purposes of the first two chaptersas a specialty within a larger field called disaster studies concerned with the application of knowledge andpractical skill to the management of emergencies and disasters in the public and private sectors. EDM should beread as equivalent to emergency management and EM. Although the more common terms could have beenused, EDM has been selected as a more neutral term which avoids any preconceptions and biases that might attachto the use of EM.

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The belief also manifests through frequent appearances of the words profession and professional inthe literature. On the other hand, Phillips, and Cwiak (2009b) have indicated the issue is still in doubt,and proclamations to the contrary are premature. Who is right? Is the question of disciplinary andprofessional status important? Is the question even capable of definitive answer? This thesis willexamine the issue of disciplinary and professional status in EDM. The technique of knowledge domainvisualization (KDViz), using the bibliometric technique of co-citation analysis, will be applied in anattempt to provide a visible representation of EDMs intellectual structure, which may provide essentialclues to answering questions about the fields disciplinary and professional status.

Statement of the Problem Just as it is with Quarantelli and Perrys definitional question, the professional and disciplinary

status of EDM also reduces to a fundamental question of structure, though the route to that realizationis less direct than might be supposed. At first the task appears relatively simple: 1) analyze conceptionsof academic disciplines and professions to determine the essential characteristics of disciplines andprofessions; 2) compare the characteristics to those of EDM. If the characteristics are found, one

concludes that EDM is a discipline and/or profession. If the characteristics are not found, one concludesthat EDM is not a discipline. As will be shown in Chapter IIs literature review, an unrecognizedproblem emerges during the first step. The problem is unrecognized because if it were correctlyidentified, authors would understand that moving to the second step is an impossibility, and anyconclusions unsupportable, until the problem is addressed.

The problem centers on the idea of a disciplinary/professional body of knowledge. Authors from avariety of diverse fields, including Wilson (2001), Evetts (2003), Schmidt (2008), and Johnson (2012),have identified the concept of a specializedbody of knowledge as an essential characteristic of academicand professional disciplines. Exactly what constitutes an acceptable body of knowledge, and how onemight empirically test for its presence in a field is more problematic. The problem is especially acute forclaims of disciplinary status by multidisciplinary fields. Depending upon how one defines the concept,such as adding the requirement of uniqueness to make a body of knowledge acceptable, it can belegitimately argued that multidisciplinary fields have no bodies of knowledge themselves. They onlypossess knowledge that can already be claimed by other disciplines. This is not to say that the argumentis correct or incorrect, but instead to say that such issues must be addressed by any attempt to definethe concept of a body of knowledge, or by any field, including EDM, that attempts to justify its ownclaims to disciplinary status. It is intellectually unacceptable, if one agrees that a body of knowledge isan essential requirement for disciplinary and professional status, to fail to provide a conceptualdefinition of a body of knowledge, and to demonstrate how a particular fields claim of disciplinary

status satisfies the body of knowledge requirement. Unfortunately, as will be shown in this paper, thisis, with some exceptions, what has happened in EDM.

The importance of the problem goes beyond the obvious reasons why EDM and other fields desirethe recognition and acceptance as an academic and/or professional discipline, such as the increasedprestige, higher income, market control, and possible access to power that can come from such status(Larson, 1979). As pointed out at the beginning of the section, the question of disciplinary status, by

way of the body of knowledge problem, is a fundamental question of the structure of EDM. If EDMhas an identifiable body of knowledge, then the field possesses a knowable intellectual structure that is

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at the same time both abstract and concrete. The idea of a body of knowledge is itself a conceptualrepresentation of the structured knowledge within an academic/professional discipline, but thatknowledge also exists in concrete form through the fields published literature. Just as the question ofWhat is a disaster? seeks to ascertain the boundaries of EDM, so the question of EDMs body ofknowledge speaks directly to not only possible knowledge boundaries, but also how the fieldsknowledge is internally organized and structured. If evidence of these boundaries, structures, and/ororganization cannot be found, EDM likely has little legitimate claim to disciplinary status.

Nature, Purpose, and Significance of Study This thesis study is an exploratory bibliometric analysis of the literature of EDM, 1994-2011, as

contained in a dataset created using the Thomson Reuters Web of Science (WoS) bibliographicdatabase, and analyzed using the knowledge domain visualization (KDViz) software package, CiteSpaceII. KDViz and co-citation analysis will be the bibliometric methods utilized.2 Much of the study usesthe quantitative (statistical and mathematical) methods of bibliometric and citation analysis developed

within the field of Library and Information Sciences (LIS) since the late 1950s (Bo

rner, Chen, &

Boyack, 2003; Hood and Concepcio

n, 2001). KDViz (also called science mapping, scientific domainmapping, and a variety of similar terms) is a specific application within the broader ILS subject areaknown as knowledge visualization. KDViz seeks to visually depict, or map, scientific knowledgedomains (and in fact, the entirety of science) using bibliometric data, like that contained withinbibliographic databases and citation indexes such as Web of Science, Scopus, and Google Scholar.Rapid advances in computer science and technology near the start of the 1990s (especially the growthof raw processing and graphics processing power in desktop computing) has enabled KDViz softwareprograms to be developed capable of performing the complex calculations necessary for analyzing andcreating visual depictions of networks based upon huge amounts of bibliographic data. It is importantto point out, however, that although KDViz is based in quantitative methods, qualitative analysis is alsoan integral part of KDViz, and is essential in the later stages of analysis for identifying possible patterns,as well as for evaluating the general accuracy/validity of the domain visualizations. The third part ofChapter II will thoroughly examine the history, methods, and applications of bibliometric analysis,citation analysis, and KDViz.

Though many, if not most, academics and professionals within EDM will likely find KDViz andmany of the topics covered in this thesis unfamiliar territory, a key starting point is the understandingthat a significant research literature has developed during the past 15 years (which will be discussed inthe third part of Chapter II) demonstrating that KDViz is capable of revealing the subtle intellectualstructure of scientific disciplines. If this is the case, then it seems reasonable to suggest that KDViz

might be of use in looking for an EDM body of knowledge and a possible disciplinary structure to thefield. Although various types of bibliometric, co-citation, and and/or visualization analysis haspreviously been applied within the field of terrorism research (Chen, 2006a; Reid, 1997; Reid & Chen,

2 Technically, KDViz and co-citation analysis are not entirely equivalent. It is possible to conduct KDViz usingother bibliometric techniques, but co-citation has become the primary method. For the purposes of maintainingconsistency throughout this thesis, unless otherwise specified, KDViz will refer to domain visualization based uponco-citation analysis.

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2007); and direct citation analysis has been applied within EDM (Janssen, Schoon, Ke, & Bo

rner, 2006; Janssen, 2007; Comfort, Waugh, & Cigler, 2012); an attempt to reveal the possible underlyingdisciplinary structure of EDM (if it exists) through co-citation and KDViz has not yet been attempted.

The purpose of this thesis is to reveal the structure of EDM using KDViz through CiteSpace II, anopen-source KDViz software package created by Dr. Chaomei Chen of Drexel University, a leadingKDViz researcher for many years.

As this is the first application of KDViz within EDM, this study has potential for significance onseveral levels. First and foremost, if the research hypotheses are confirmed, it opens the door to furtherexamination and application of KDViz by others as a tool for examining EDM from new perspectives.This will hopefully facilitate progress towards resolving the longstanding, niggling, questions andconfusions that surround EDM regarding its identity and structure, as both body of knowledge andpossible academic/professional discipline. It is believed that resolving these issues would be a major stepforward for the field. Secondly, the methods used in this thesis, if shown to have value, also havefuture use in tracking and depicting the development of the field and its literature, on a yearly basis asa sort of yearbook of the field. Third, by applying and showing the general applicability of KDViz to a

complex, emerging, multidisciplinary, field, this thesis contributes to the LIS and KDViz bodies ofknowledge by demonstrating new applications for the approach, as a majority of previous research onKDViz has focused on its use in fairly well-defined scientific disciplines. Finally, if the hypotheses ofthis thesis are shown correct, then it is also a powerful reminder of the importance of disciplinary cross-fertilization in the creation of new knowledge, as well as demonstrating the growing problem in scienceof what is called latent domain knowledge, where information that may be highly valuable to oneparticular discipline is overlooked because it originates in different disciplines or fields, or is publishedin less recognized sources (Chen, Kuljis & Paul, 2001).

Research Questions and Hypotheses At the core of this study, there are three primary research questions, and five research hypotheses.

These are the primary research questions asked in this study:1. Is EDM a suitable area for application of co-citation analysis and KDViz? If it

is, what does it reveal about the possible structure and organization of EDM?2. Does the analysis reveal evidence of a significant academic and/or professional

EDM body of knowledge; and how does KDViz compare to other attempts todetermine the key works, journals, and trends in the EDM body of knowledge, suchas the FEMA Higher Education Program Body of Knowledge Project?

3. How do the findings of the analysis relate to questions of disciplinary and

professional status in EDM?

These are the primary research hypothesis:1. Co-citation analysis and KDViz are approaches ideally suited, so long as

methodological limitations are understood, to provide unique views of the possibleintellectual structures and relationships within EDM that have not previously beendetected.

2. The sources (authors, articles, and journals) that are the foundation of

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EDM/EM are vastly larger in size and scope; are more diverse in their multidisciplinaryorigins; and are more poorly integrated into the field than possible realized.

3. Analysis and visualization will reveal an identifiable disciplinary structure to alarger knowledge domain than what is commonly thought of as EDM/EM. The largerknowledge domain will refer to that which has been called many names, but in thisthesis will be called the discipline of Disaster Studies and Sciences. EDM/EM do notrepresent the entirety of the field, but instead are subdomains or specialtieswithin thelarger knowledge domain of Disaster Studies and Sciences.

4. Uncertainty in the field regarding a professional body of knowledge in EDM will be reflected in the visualizations. Visualizations are hypothesized to show structurefor EDM/EM as an academic discipline within the larger field of Disaster Studies andSciences, but less so for evidence of a structure of the practical application of thatknowledge, which should be expected in the knowledge structure of a profession.Professions should show a distinction between the basic science of the field thatunderlies the profession, and the knowledge that is part of the practice of the

profession. In medicine, for example, there is a discrete knowledge structure for thebranches of basic medical sciencesand for the branches of clinical medical practice.Such structure is anticipated to be poorly realized, if at all, in professional EDM.

5. When compared to other attempts to identify a professional EDM/EM bodyof knowledge, such as FEMAs yearly Body of Knowledge Survey, KDViz will show agap between the actual knowledge domain that exists and the knowledge domainpresented by the survey.

Assumptions and Limitations As will be seen shortly in Chapter II, citation analysis and KDViz are founded on empirical not

theoretical grounds, though greater effort is being made now to develop an underlying theory (Chen,2006b; Purchase, Andrienko, Jankun-Kelly, & Ward, 2008). Although the origins may be empirical,there are still theoretical assumptions underlying citation analysis and KDViz: 1) the citation is afundamental unit of communication, acknowledgement, and recognition within, and across, theliterature of scientific/academic/professional disciplines; 2) because of the function of citations, directand indirect measures and methods can be developed to evaluate the influence/significance of authors,articles, journals; subjects, etc. based on citation patterns; 3) the connections, linkages, and relationshipsbetween cited authors, articles, journals, subjects, concepts, keywords, disciplines, etc., form networkscapable of being analyzed and visually represented the same as social networks; and 4) the intellectual

structure and organization of scientific/academic/professional disciplines is reflected in the structure oftheir citation (particularly co-citation) networks, allowing them to reveal the unseen structure ofdisciplinary knowledge.

The use of bibliometric and citation analysis techniques also carries with it limitations and ethicalimplications, particularly when such analysis is presented as representing a true and accurate picture ofthe weight of individuals intellectual contributions to a field. Such considerations, controversies, andcriticisms of bibliometric methods are not new in the history of citation analysis, examples of which canbe found in papers by Schoonbaert and Roelants (1996), and Van Raan (2005). As seen in these papers,

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the harshest criticisms are usually reserved for the use of bibliometrics and citation analysis as a form ofacademic quality evaluation and/or academic ranking. Although this is not the purpose or intention ofthe present study, the same issues that have led authors to question the use of bibliometrics as anevaluation metric are also issues that affect the general use of citation analysis. The issues can be broadlydivided into those of theoretical assumptions and those of methodology.

Osareh (1996a, 1996b) presents a comprehensive literature review of citation and co-citationanalysis, detailing eleven key limitations of the method, including both theoretical assumptions andmethodological issues. These theoretical problems are also presented by Harzing (2010). The issuescenter around the general bibliometric assumption that citations have a similar meaning and role acrossall scientific and academic disciplines: in fact, it is likely that not all citations are created equal.Differences and variations in citation patterns and rates have been found to exist across fields of study,and with time within a single field. There are also disciplinary differences in preferred methods ofscientific communication (e.g. journals; conference papers and proceedings; books; and monographs),

which can mean that the source of a citation can affect its value, depending upon the field of study.Methodological issues pointed out by Osareh include: the problem of whether to count or remove self-

citations from totals (including the self-citations of secondary and tertiary authors where there ismultiple authorship); incompleteness of sources indexed within the major bibliographic databases;biases in the databases for citations in English-language publications; variations in how the same nameor title is presented within databases, including misspellings (E.L. Quarantelli, for example, couldappear as EL Quarantelli, E.L Quarranntelli, Enrico L. Quarantelli, E Quarantelli, E. Quarantelli,etc.-- each of which would be recognized as a distinct author by citation and co-citation analysissoftware); difficulties distinguishing different authors who share identical surnames and initials; anddifficulties in verifying that the citation counts listed within databases are accurate. Within the samevein, Harzing (2010) reports various studies that have found significant variations in citation totalsproduced by different databases, with the variation being affected by factors such as the database beingused (which determines the sources indexed), and the particular field under study (different databasesrepresent different fields of study to greater or lesser degrees).

Despite these problems and limitations, Osareh concludes that, aside from the questionable use ofcitation totals to assess the quality of an authors work, ...bibliometric methods, particularly, citationanalysis techniques are useful tools in evaluating science and technology activities... (1996b, p. 223).Bibliometric and citation analyses should be carried out conscientiously, and results presented carefully,not only to ensure that the analyses are technically correct, but that the interpretation of results arepresented so that others are directly steered away from erroneous conclusions that are not justified bydata, or that could be taken out of context. Some of the problems and limitations discussed in this

section did surface during the study, and will be discussed in detail in Chapter III.

Organization of Remainder of Paper In Chapter II, a three-part literature review is conducted. First, the conceptualization of disciplines

and professions is examined. The next section turns the focus onto the literature regarding the body ofknowledge, and the disciplinary status of EDM. The final part of Chapter II gives an overview of thehistory and methods of bibliometric analysis, citation- and co-citation analysis, KDViz, and CiteSpaceII. Chapter III provides details of the methodology used in this study, including its structure and

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rationale; details of dataset collection and construction; and the software settings used in the analysisand the reasons for those choices. The results of the analysis, including Author, Document, and JournalCo-citation network visualizations, are presented in Chapter IV. In Chapter V, these results arediscussed in relation to the original research questions and hypotheses. Implications of the research,both present and future, and how the steps taken in this study might be progressed in future research,are also presented.

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CHAPTER II: LITERATURE REVIEW

The present study involves three distinct but inter-related topics. The first concerns howacademic/professional disciplines have been historically conceptualized, particularly as related to theconcept of a body of knowledge. The second requires the first topic as a foundation, for it examinesattempts to establish the disciplinary status of EDM, academically and professionally, especially in termsof demonstrating a body of knowledge. Finally, the third topic provides an overview of bibliometricmethods, including co-citation analysis, KDViz, and the CiteSpace II software that resides at theanalytic core of this thesis. It therefore seems entirely appropriate that the chapter be divided into threeparts, with each part devoted to one of the three topics.

Conceptualizing Professional and Academic Disciplines Wilson (2001) provides an excellent historical, linguistic, and sociological survey of professional

emergence. As detailed in her paper, although some authors have asserted a far earlier historicalbeginning to professions, the term itself dates back to the 15th-16th Century, and the three originaluniversity-taught learned professions: medicine, law, and theology. Attempts to define a set ofgeneralized criteria to describe professions, though, were still several hundred years away, and did notbegin until the early 1900s (Schmidt, 2008). The core sociologic traits of a profession, originally putforth by the sociologist Friedman, and summarized in Wilson, are autonomy and monopoly (Wilson,2001, p. 26). Professions are autonomous in that they control the professions entry requirements,education, training, and discipline, and that the professional controls their own work. As a monopoly,professions prevent unapproved individuals from practice, either directly through government licensureor indirectly by development of market preference for a professional credential. Half a century later,sociologist Ernest Greenwood (1957) proposed a slightly expanded set of essential characteristics:

Succinctly put, all professions seem to possess: (1) systematic theory, (2) authority, (3) communitysanction, (4) ethical codes, and (5) a culture (Greenwood, 1957, p. 45). He also proposed that there isno bright line distinction between professions and non-professions based on the presence or absence ofthe characteristics. The characteristics are present in many occupations but it is the degree to which thecharacteristics are present that is important in deciding where along the line of professionalism theoccupation resides: ...we must think of the occupations in a society as distributing themselves along acontinuum (p. 46). In the 1960s, Wilensky (cited in Schmidt, 2008) defined the professionalizationof occupations as a progressive process starting first with the establishment of training schools/programs;university programs follow; local associations are created then national associations; state licensure isestablished; and reaches completion with the establishment of a code of ethics.

These traditional views of professions, however, have been questioned in recent years, with somefinding the criteria out of step with modern developments. Evetts (2003) proposes a broaderunderstanding that defines professions as: dealing with work associated with the uncertainties ofmodern lives in risk societies. Professionals are extensively engaged in dealing with risk, with riskassessment, and through the use of expert knowledge, enabling customers and clients to deal withuncertainty (p.397). For Evetts, rigid boundaries are no longer useful, and even identification of anoccupation as a profession can vary between societies/cultures. For Evetts, it is more useful to examine

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the rise of occupational professionalism instead of professions, per se . Blending the traditional criteria with a more modern interpretation of professions, the work of Bayes (cited in Schmidt, 2008) identifiesthree essential characteristics: extensive training; significant intellectual investment; and provision of animportant service to society.

Common to both traditional and modern definitions of a profession, whether stated explicitlyor implicitly, directly or indirectly, is the idea that a profession requires possession of some specializedsphere of knowledge/theory. This is itsbody of knowledge(BOK), or common body of knowledge(CBOK).

According to Swick (2000), and echoing Evetts, it is the application of expert knowledge (p. 613) which has become the predominant characteristic of modern professions. Of course, the question thenbecomes what is it that distinguishes expert knowledge from the non-expert knowledge required ofother occupations and skilled trades? Why is the knowledge applied by a carpenter not consideredexpert but that applied by a structural engineer is? The answer lies in the fact that distinct bodies ofknowledge are not limited to professions, but are also one of the defining characteristics of scientificand academic disciplines (Johnson, 2012). As presented by Johnson, a discipline can be said to exist

where either a distinct body of knowledge, and/or a unique methodology can be shown to exist in a

field. Thus, although it may at first appear that speaking of academic and professional disciplines is tospeak of concepts with separate identities, they both must meet, more or less, the requirement ofpossessing specialized knowledge and/or methods. The difference between an academic and aprofessional body of knowledge lies in the knowledge content contained within that body. Academicbodies of knowledge contain the unique knowledge of the field itself, whereas professional bodies ofknowledge pertain to the practical application of one or more academic bodies of knowledge.It is therelationship between disciplines, professions and professional practice, and the included bodies ofknowledge that gives rise to expert knowledge.

The relationship between professional and scientific/academic bodies of knowledge is logical andnecessary. It is not accidental. Professions, in the view of this thesis, are occupations that requireapplication from one or more scientific and/or academic bodies of knowledge towards issues of humanconcern. This often first requires basic mastery of skills and knowledge from multiple foundationdisciplines (e.g. chemistry, biology, physics, and mathematics) before one is allowed access to the coreacademic discipline of the profession (e.g. medical science), its subspecialties (e.g. internal medicine),and the body of knowledge required for professional practice (e.g. internist). The professional body ofknowledge contains information, skills, methods, techniques, results, and standards of application thatmust be mastered (and perpetually updated) by those who wish to practice (Sefton, Shea, & Hines,2011).

This leads to an important conclusion:before there can be a professional body of knowledge, and

a professional discipline, there must first exist one or more academic disciplines that the professupon.One should not confuse a professions unique body of knowledge withknowledge, skills, and abilities

(KSAs) needed for professional practice. An example of KSAs can be found in those offered by theInternational Association of Emergency Managers (n.d.). There are many generic KSAs (e.g.communication; interpersonal; team-building) that many professions require but they are not uniqueto any profession. A professional body of knowledge is also generally conceived to be distinct from thecore discipline of the profession it is based upon (Klingenberg, 2009). This is to say that professional

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bodies of knowledge are generated fromwithin professions, not from outside. Although knowing thelegal aspects of medicine is essential to the practicing physician, the knowledge itself could belegitimately said to belong to the body of knowledge of law, not to medicine. Without a unique bodyof knowledge separate from those of other disciplines and professions, an occupation has no expertdomain, and any claim it may make to professional status might ultimately lack legitimacy.

What constitutes uniqueness, however, may be less the absolute requirement it first appears to be.It is well within reason to imagine many important pieces of knowledge that may be rightly claimed bymore than one disciplines body of knowledge, just as the preceding law/medicine example illustrates.

As pointed out in the Introduction, absolute uniqueness is a difficult, if not impossible, standard formultidisciplinary fields to meet. Many of these fields may begin life as subfields within an existingdiscipline. Sociology and sociologists, for example, have played an essential role in the early history anddevelopment of disaster studies (Drabek, 2007). Would the development of a disaster studies disciplinemean that the contributing work of these sociologists cannot continue to exist within both disciplinarybodies of knowledge? This seems patently absurd. Yet removing the requirement of uniqueness entirely

would also appear to make the very idea of disciplinary bodies of knowledge meaningless. What is

missing is to understand that uniqueness can exist along a continuum just as Greenwood suggested acontinuum exists for whether an occupation is or is not a profession. When uniqueness is viewed inthis way and applied to the present problem, it allows for parts of bodies of knowledge to be held incommon between disciplines, so long as there is a much larger share of knowledge not held in common.In the case of multidisciplinary fields, they become more unique as the number of disciplinescontributing to the body of knowledge increases, and as the production of distinct knowledge underthe banner of the new field grows. For example, if the bulk of current disaster knowledge is found tostill fall under the purview of sociology, or it is found to be held in common between only a fewdisciplines, then it would be right to conclude that the field of disaster studies is not yet a discipline. Itremains a subfield/specialty within one or more other fields of study. If, however, we find that theknowledge in disaster studies is split across numerous existing disciplines, and we find there is also agrowing, substantial part of its body of knowledge recognized as being unique to the field of disasterstudies, then we could rightly conclude the field either is, or is on the verge of becoming, a discipline.

Disciplinary Status and the Body of Knowledge in EDM The significance of connecting EDM to a unique body of knowledge is understood by many authors

within the field. Jensen (2010), who is among those authors that believe that EDM is both an academicand professional discipline, states: the body of knowledge that one has to know to be competent inemergency management is vast, specialized, and separate from any one other discipline (Jensen, 2010,

p. 15). Phillips (2003) while never directly placing the discussion within the context of the body ofknowledge question, doubts that the debate in EDM regarding its disciplinary status has been settled,even though key figures like Mileti believe that the debate has been settled in favor of disciplinary status.Phillips, however, does seem to be optimistic that EDM is far closer to such status than it is distant.Lindell, Prater, and Perry (2006) see EDM as an emerging profession and repeatedly stress that a keygoal for continued progress must be to build and grow an identifiable body of knowledge forpractitioners (Lindell et al., 2006, p. 363). As mentioned in the Introduction, it is much easier to findopinions in the literature regarding EDMs body of knowledge and disciplinary status than it is to find

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empirical support for the opinions. If there is an EDM body of knowledge, it should be discoverable,identifiable, quantifiable, and qualitatively describable. Many fields/occupations, including massagetherapy, geographic information science (GIS), and civil engineering, have formal Body of Knowledge(BOK) documents (Massage Therapy Body of Knowledge (MTBOK) Task Force, 2010; UniversityConsortium for Geographic Information Science, 2006; American Society of Civil Engineers (ASCE),2008). To date, there have been two attempts, one indirect and one direct, to detail the body ofknowledge in EDM: the International Association of Emergency Managers (IAEM) AssociateEmergency Manager (AEM)/Certified Emergency Manager (CEM) examination; and the FederalEmergency Management Agencys (FEMA) Emergency Management Higher Education ProgramsBody of Knowledge Project.

IAEM AEM/CEM Examination The AEM/CEM examination is one of four elements in IAEMs AEM/CEM credentialing program

(IAEM, 2011; Lindell, Prater & Perry, 2006). The 100-item, multiple-choice exam includes country-specific versions for the United States, Canada, Australia, and New Zealand, with sample questions

provided in IAEMs exam brochure (IAEM, 2011). Although a credentialing examination is not a bodyof knowledge, a well-designed, well-constructed professional credentialing or licensing exam is a reliableand valid sample of a professional fields body of knowledge. Many professions have no formal BOKdocuments. It then becomes the credentialing/licensing examinations that establish, through theircontent and structure, the body of knowledge requirements practitioners must master.

In the case of the AEM/CEM exam, there is little available information regarding test design andconstruction, question/item generation, and other important metrics of the exam. Lindell et al., whodiscuss the CEM program at great length, also fail to elaborate on the question of exam validity, onlysaying than it is comprehensive (Lindell, Prater & Perry, 2006, p. 359). The IAEM brochure suggeststhat applicants brush up on basic emergency management literature (IAEM, 2011, p. 4), and thatthe exam questions will focus on emergency management principles and practices reflected in thepublications listed on the back page (IAEM, 2011, p. 4). It is exactly the publications listed on theback page of the brochure that reveal the most about the relationship between the AEM/CEM examand the EDM body of knowledge it purportedly draws from. The recommended publications that maybe used to make up all exams (IAEM, 2011, p. 16) are FEMA Independent Study courses. Lookingat country-specific recommendations, only Australias country-specific references includes books and

journal articles. For the United States, Canada, and New Zealand, virtually every other reference citedis a law, policy document, or product of government agency. Thus, according to the AEM/CEM exam,a substantial part of the EDM professional body of knowledge can be found in FEMAs online self-

study training catalog. If studying FEMA training courses, public law, and public policy contains allthere is to know in professional EDM, one might be led to question why there is any need for EDMundergraduate and graduate programs.

With FEMA being identified as the primary source of the EDM body of knowledge rather thanIAEM itself first identifying and creating the BOK for professional EDM, the certification examinationas currently constructed does not appear to be a tool capable of validly illuminating the EDM body ofknowledge. There is, however, another more direct effort, also supported by FEMA, to define the bodyof knowledge within the field and profession.

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FEMA Higher Education Program Body of Knowledge Project

In 2005, the FEMA Higher Education Program started the Body of Knowledge Project, a highlypromising yearly survey of the academic and practitioner communities in EDM to identify the essentialreadings of the field/profession (Spiewak, 2005). The purpose of the program, as explained by Spiewak,is to assist in the development of an actual EDM BOK, which could also provide a source for updatingIAEM CEM examination questions. The initial one-question survey asked respondents to name threebooks, articles, policy documents, etc. that they would recommend to others. Over 1000 surveys weresent; 326 usable responses were received; and the result was the top 50 reading recommendations. Inaddition to expected recommendations like theNational Incident Management System, the Stafford Act ,Emergency Management: Principles and Practices for Local Governments, and Disasters by Designthe 2005survey included classic EDM works likeWho Moved My Cheese , Rudi GuilianisLeadership, and Volcano:The Movie (Spiewak, 2005).

Since 2006, the survey sample for each year has alternated between the EDM academic communityand practitioners, the number of works for respondents to recommend has increased to 10, and the

recommendations are ranked according to the number of respondent lists a work appears on. The 2009edition (Cwiak, 2009a) also includes a summary of top selections from the 2006-2009 surveys, whichis presented in Table 1. The 2011 edition (Cwiak, 2011) is the most recent, and includes 93 entriesbased on responses from 56 out of 133 (42%) surveys sent to EDM higher education programs. At thetop of the 2011 list is Haddow, Bullock, & Coppolas Introduction to Emergency Management , which

was included on the lists of 12 respondents.The idea that there is value in an EDM recommended reading list cannot be faulted. Blanchard

(2007; 2008) not only created his own top 50 reading list as a companion piece to the Body ofKnowledge Project, but also created perhaps the most detailed bibliography of the field in existence,totaling 750 pages in length. FEMA also has its online ALL-HAZARTS database of EDM scholarlyarticles (http://www.lrc.fema.gov/allhazarts.html). The idea that a survey-based recommended readinglist can be used to extract a body of knowledge, however, is rather nave. If anything, the surveys inpractice have shown a greater potential for revealing the fields lack of awareness of its own body ofknowledge. Cwiak (2009a) comments that the increasing repetition of certain works from year to yearindicates growing consensus among respondents. This is likely true, but such consensus is also evidenceof intellectual/technical stagnation within EDM. Examining the lists produced by the project, it is hardnot to notice that although entire journals have been included, not a single specific journal article, whitepaper, or conference paper appears. Since journal articles and conference proceedings are often thepreferred source for communicating empirical research and theoretical development within scientific

and professional fields, this may be a sign EDM is failing to develop an infrastructure that supportsintegrating research and practice so that there is the eventual emergence of evidence-based EDMpractice.

The ultimate problem is deeper still. Not even creation of an infinitely comprehensive bibliographyof emergency management can overcome the fact that a bibliography, although closer to the goal, is stillnot the same as a body of knowledge. EDMs disciplinary body of knowledge (should it actually beshown to exist) lives within the bibliography, waiting to be extracted, analyzed, defined, detailed,organized, structured, and disseminated. Methods have emerged that could assist in this task, though it

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Table 1FEMA Body of Knowledge Project Top Recommended Readings, 2006-2009.

2009-Practitioner 2008-Academic 2007-Practitioner 2006-Academic

1. Principles ofEmergency Management(Blanchard, et al.) 2. National Incident Management System(NIMS) 3. National FirePrevention Association1600 (NFPA 1600)4. National ResponseFramework (NRF)5. Disasters By Design: A Reassessment ofNatural Disasters inthe U.S.(Mileti)6. Emergency Management: The American Experience

(Rubin)7. Emergency Management:Principles and Practice for Local Government(Drabek& Hoetmer) 8. Emergency Planning(Perry & Lindell)9. Stafford Act

1. Emergency Planning(Perry& Lindell) 2. Introduction to Emergency Management(Haddow &Bullock) 3. Disasters by Design: AReassessment of NaturalDisasters in the U.S.(Mileti)4. Emergency Management:Concepts and Strategies forEffective Programs(Canton)5. Emergency Management:The American Experience(Rubin) 6. Introduction to Emergency Management(Lindell, Prater& Perry) 7. 9/11 Commission Report8. Emergency Management

Principles and Practices forLocal Government(Waugh& Tierney)9. At Risk: Natural Hazards,Peoples Vulnerability &Disasters(Wisner, et al.) 10. Disaster Response andRecovery(McEntire)11. Facing the Unexpected:Disaster Preparedness andResponse in the U.S.(Tierney, Lindell, Perry) 12. Living with Hazards,Dealing with Disasters(Waugh)13. NRF

1. Living withHazards,Dealing withDisaster(Waugh) 2. Emergency Management:Principles and Practice for Local Government(Drabek & Hoetmer) 3. Disasters by Design: A Reassessment ofNatural Disasters inthe U.S.(Mileti)4. FEMA IS 100/200,ICS 300, 400, 4025. 9/11 CommissionReport6. NIMS 7. National ResponsePlan (NRP)

8. Stafford Act

1. Disasters by Design A Reassessment ofNatural Disasters inthe U.S.(Mileti) 2. Introduction toEmergency Management(Haddow & Bullock) 3. Facing theUnexpected: DisasterPreparedness andResponse in the U.S.(Tierney, Lindell,Perry) 4. Living withHazards, Dealingwith Disaster(Waugh)5. 9/11 Commission

Report6. Disasters &Democracy(Platt)7. NIMS8. NRP

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requires looking for methodological help from a very different discipline, that of Library andInformation Sciences (LIS). This will be explored in the final section of the chapter.

Bibliometrics, Co-citation, KDViz, and CiteSpaceThe application of mathematical and statistical methods to the analysis of bibliographic materials

is an LIS specialty usually referred to as bibliometrics. Hood and Concepcio

n (2001) have traced theearliest history of bibliometrics to the late 1800s and early 1900s. The term itself, although somebelieve it existed as early in French publications as early as the 1930s, is generally held to have beencoined and defined by Pritchard in 1969. The term is often used synonymously with the termscientometrics, which according to Hood and Concepcio

n, was also coined in 1969, and appliesbibliometric methods in analyzing the literature of science and technology. The two specialties arealmost indistinguishable from one another most of the time, and where the distinction lies depends on

whose definitions are being used. Bo

rner, Chen, and Boyack (2003), see all scientometric research asbibliometric in nature, but not all bibliometric research is concerned with science and technology.Hood and Concepcio

n, however, define scientometrics as the quantitative analysis of all outputs of

science and technology, which includes bibliographic and non-bibliographic materials. For them, notall scientometric analysis is bibliometric, and not all bibliometric analysis is scientometric. This thesisaccepts Hood and Concepcio

ns distinction, though as it applies to the present study, it can be correctlyconsidered both bibliometric and/or scientometric, regardless of definition. For the sake of consistency,only bibliometrics and its variations will be used throughout the rest of the paper.

Bibliometric methods were substantially advanced, as explained by Bo

rner et al., by the birth ofmodern citation indexing and citation analysis, which can be traced to Eugene Garfields (1955) seminalarticle on citation indexing and its possible applications in science. Garfield would eventually establishthe Institute for Scientific Information (ISI) and create the Web of Science (WoS) bibliographicdatabase. Garfield and scientist Henry Small are generally considered the founding fathers of modernbibliometrics. Creation of map-based visualizations based upon the analysis ofdirect citations (whenlater papers or authors cite earlier ones) began as early as 1964, and soon other researchers were exploringthe possibility of mapping the networks of science (Bo

rner et al., 2003). Further groundbreaking in thefield took place a few years later when Small (1973) advanced the idea ofco-citation analysis . Co-citationanalysis is similar tobibliographic coupling (examining the shared references among papers or authors),

which had already joined direct citation analysis in the bibliometric toolbox. What makes co-citationdifferent is the fact that it is an indirect citation relationship. Co-citation is defined as the frequency

with which two items of earlier literature are cited together by the later literature (Small, 1973, p. 265). White and McCain also provide an excellent definition: Co-citation occurs when any two works appear

in the references of a third work. The authors of the two co-cited works are co-cited authors. If the co-cited works appeared in two different journals, the latter are co-cited journals (as cited in Bo

rner et al.,2003, p. 11).

If, in a sample of journal articles, Article 1 cites Articles C and D; then C and D are said to be co-cited. If Article 2 also cites C and D, then C and D have been co-cited twice. The greater the frequencyof co-citation occurrences, the stronger the likely connection or similarity between the co-cited items.Co-cited pairs, such as Articles C and D, are not required to have cited one another. Small suggested inhis paper that co-citation, because it appears to measure the strength of an intellectual connection

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between items, could be used to reveal and map the structure of scientific specialties, including how thestructure changes over time. What can be revealed by co-citation, in Smalls view, are very much theinvisible colleges proposed by Crane (1972), which are created by the invisible links between scientistsand academics, and are key mechanisms of knowledge transfer and dissemination.

Since the publication of Smalls paper in 1973, co-citation has become the primary form ofbibliographic analysis for examining how scientific fields develop and are structured.Table 2 lists someof the many co-citation studies where the method has been used to visualize various scientific knowledgedomains, including the entire domain of scientific knowledge over a single year. The most commonlyused forms of co-citation includes analysis of cited authors (Author Co-citation Analysis, or ACA); citedarticles (Document Co-citation Analysis, or DCA); and cited journals (Journal Co-citation Analysis, or

JCA). ACA is the most frequently used form of co-citation analysis. More recently, co-citation analysisusing WoS journal classifications has also emerged as a promising tool for mapping very large scientificdomains (Vargas-Quesada, de Moya-Anego

n, Chinchilla-Rodriguez, & Gonza

lez-Molina, 2006;Vargas-Quesada & de Moya-Anego

n, 2007 ). Almost from the beginnings of citation analysis, visualization (in the form of mapping) of resulting

citation networks appear as an integral part of analysis. All of the studies in Table 2 include both analysisand visualization. The capabilities of visualization and graphic technology in the early years of citationanalysis, unfortunately, lagged some years behind advances seen in citation analysis methods. In fact, it

would take until the later parts of the 1990s for the pace of research and publication on informationvisualization, and more specifically knowledge domain visualization (KDViz) to quicken substantially(Bo

rner et al., 2003). Since then there has been an explosion in visualization methods, procedures,algorithms, refinements, interpretations, evaluations, and visualization software packages (many of

which are available freely online for research purposes). This has allowed for the simultaneous growthin KDViz studies of scientific domains, especially in the last ten years, which is also reflected in Table2. In addition to the technical aspects of producing visualizations, research attention has also focusedon other issues such as user interfaces, user interaction with visualized information, and aestheticconcerns (Chen, 2004).

Within the KDViz research literature of the past fifteen years, one of the frequently recurring namesis that of Dr. Chaomei Chen, of Drexel University. He has participated in, and researched most of themajor developments of the field, including: methods of information visualization (Chen, 2004);methods of analysis and mapping of various scientific knowledge domains (Bo

rner et al., 2003; Chen,2003); identification and visualization of citation bursts (high rates of citation for a particular author,article, or journal during the first few years after publication, which can be an indication that the itemis of particular importance to a field) using Kleinbergs (2002) algorithm (Chen, 2006a, 2006b);

visualizing latent domain knowledge (Chen, Kuljis, & Paul, 2001; Chen, 2003); quantitative measuresof the quality of a visualized network (Chen, 2005); and most recently, use of KDViz in the analysis ofmultidisciplinary fields (Chen, Hu, Liu, & Tseng, 2012). Chen, like many in LIS, is influenced byThomas Kuhns landmark work on the nature of scientific discovery,The Structure of ScientificRevolutions (Kuhn, 1962/1996), and his work takes special interest in the use of KDViz to identify keyturning points in scientific knowledge domains (Chen, 2003, 2006a). Chen believes these visualizedturning points may indicate the paradigmatic shifts in scientific fields referred to by Kuhn.

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Table 2Selected Co-citation/Knowledge Domain Visualization Studies

STUDY DOMAIN(S) ANALYZED

White and McCain (1998) Information Science, 1972-1995

Chen & Paul (2001) Hypertext; Computer Graphics; Virtual Environments

Boyack (2004) 20 years of Proceedings of the National Academy of Sciences (PNAS)

Chen (2004) Superstring Field in Physics

Mane & Bo

rner (2004) PNAS, 1982-2001

Boyack, Klavans, & Bo

rner(2005)

Entire structure of science

Synnestvedt, Chen, &Holmes (2005)

Medical Informatics

Chen (2006a) Mass Extinction; Terrorism

Vargas-Quesada, de Moya- Anegon, Chinchilla-Rodriguez, & Gonzalez-Molina (2006)

Co-citation analysis and mapping of Web of Science categories for allindexed articles produced in the United States in 2002; all records ofscientific literature produced in China in 1990 and 2002

Reid & Chen (2007) Terrorism research

Vargas-Quesada & deMoya-Anegon (2007)

Category co-citation of world scientific literature, 2002; comparisonEU and US domains, 2002; evolution of Spanish scientific literature1990-2002

Dwivedi, Lal, Mustafee, & Williams (2009)

Analysis of articles published inInformation Systems Frontiers , 1999-2008

Zhao & Wang (2011) Ubiquitous Computing

Chen, Hu, Liu, & Tseng(2012)

Regenerative Medicine

Rorissa & Yuan (2012) Information Retrieval

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All of these various interests and developments find full expression in CiteSpace and the most recentversion, CiteSpace II, the open access, Java-based, Windows and Linux-compatible KDViz softwareprogram created by Chen, and widely used in KDViz research (Chen, 2003, 2004, 2006a, 2006b,2011). The program has also performed extremely well in comparisons to other KDViz applications(Cobo, Lopez-Herrera, Herrera-Viedma, & Herrera, 2011). CiteSpace can either be downloaded orstarted directly from the CiteSpace download page(http://cluster.ischool.drexel.edu/~cchen/citespace/download.html). Figure 1 shows a screenshot of the programs two main control panels.

CiteSpace is a progressive KDViz program capable of dividing a time period under study into smallertime slices that can be displayed in a variety of formats, including merged networks representing theentire study timeframe; or a series of individual visualizations of each time slice (Chen, 2004). Thisallows the temporal evolution of co-citation networks to be visualized. Other visualization formats arealso offered. CiteSpace is primarily designed for analyzing bibliographic data obtained from theThomson Reuters Web of Science (WoS), though several other data formats are supported to differentdegrees. CiteSpace offers multiple types of citation analysis, including Author, Document, and Journalco-citation analysis. The user is given numerous options for configurations and settings to tailor/fine-

tune analyses and visualizations to need. CiteSpace also uses a distinctive approach to networkvisualization, one that utilizes a tree ring node design, as well as size and color, to represent citationfrequencies, link strengths, years, and significant metrics values. This approach allows a single co-citation network visualization to incorporate large amounts of quantitative and temporal information.The most important of these visual concepts are shown in Figure 2. Although a full explanation of allof the features in CiteSpace is beyond the scope of this paper, interested readers are directed to theCiteSpace website(http://cluster.cis.drexel.edu/~cchen/citespace/), which includes links to user guides,tutorials, Wiki, and videos.

One of the primary reasons why Chen created CiteSpace was to research the identification ofemerging research areas and trends in scientific literature (Chen, 2003, 2006a). This is in keeping withhis interest in scientific turning points and Kuhns philosophy of science. As discussed in Synnestvedt,Chen, and Holmes (2005), and Chen (2006a), work by Price showed there is a structural relationshipbetween the source articles used as data in co-citation analysis (theciting articles ) and the references thatare contained within those articles(thecited references ) . The set of citing articles during a given timeperiod with high citation counts represent the research fronts of the discipline, those emerging,transient, areas of current research, some of which may continue to grow into significant newdisciplinary directions, and others which will not bear fruit and will be abandoned. The cited referencesof these articles establish theintellectual base of the discipline, which is the prior literature that supportsthe research fronts. This intellectual base is what is directly visualized in KDViz, and this finding is the

basis for the present research. Although discovering disciplinary research fronts is an important part ofKDViz, the answers to the research questions in the present study are to be found in the intellectualbase, not the research fronts. Work by Persson, discussed by Chen (2006a, 2006b), found thatintellectual bases are quite stable over time; and that lowering the co-citation thresholds used in ananalysis results in the expansion of the visualized intellectual base. The observed characteristics ofdisciplinary intellectual bases in KDViz are exactly the characteristics one would expect to observe indisciplinary bodies of knowledge. Thus, the intellectual bases found in KDViz are equivalents, or near-

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http://cluster.ischool.drexel.edu/~cchen/citespace/%20download.htmlhttp://cluster.ischool.drexel.edu/~cchen/citespace/%20download.htmlhttp://cluster.ischool.drexel.edu/~cchen/citespace/%20download.htmlhttp://cluster.ischool.drexel.edu/~cchen/citespace/%20download.htmlhttp://cluster.cis.drexel.edu/~cchen/citespace/http://cluster.cis.drexel.edu/~cchen/citespace/http://cluster.cis.drexel.edu/~cchen/citespace/http://cluster.cis.drexel.edu/~cchen/citespace/http://cluster.ischool.drexel.edu/~cchen/citespace/%20download.htmlhttp://cluster.ischool.drexel.edu/~cchen/citespace/%20download.html


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Figure 1. Screenshot of CiteSpace II Control and Visualization Panels. The program can beintimidating at first, and takes substantial time to learn. Available documentation explains the basicprogram functions adequately, but the use of many advanced programs functions must be gatheredfrom the research literature.

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Figure 2. Basic visualization concepts used in CiteSpace II. CiteSpaces use of size and color allows alarge amount of important information to be conveyed within a single visualization.

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equivalents, of disciplinary bodies of knowledge. CiteSpace should therefore be a means of visualizingthe body of knowledge within a discipline, if it exists.

Finally, a word of caution needs to be given to any readers tempted to immediately downloadCiteSpace and begin their own KDViz research projects. CiteSpace is a powerful, interesting, andextremely useful KDViz software program. But it should be remembered that CiteSpace is research,not commercial software. This author has found that for someone coming to the software from outsidethe world of LIS and KDViz, it can also be intimidating and at times, highly frustrating. The UsersGuide (Chen, 2011) shows that a basic analysis can be conducted in a set of six steps. Once a basicanalysis and visualization is completed, however, understanding and interpreting the results is neverdirectly discussed in depth in the documentation. More importantly, one can complete a basic analysis

without understanding if the program settings are appropriate for the intended research purpose. Muchof this material is absent or incompletely present in CiteSpaces documentation, and must bedetermined as best as possible from the research literature, as well as through a substantial amount oftrial and error. Ultimately, this requires a major investment of time and mental energy to learn not

only operation of the program, but also the underlying aspects of bibliometrics, citation analysis, andnetwork analysis CiteSpace is based upon. These comments are not meant to in any way to lessen thevalue and usefulness of the program, for these issues appear to be present in many, if not all, KDVizapplications available. Potential researchers coming from outside LIS and KDViz, however, should haverealistic expectations of the learning curve required.

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CHAPTER III: METHODOLOGY

The idea for the present study first originated during the spring of 2012, when the authoraccidentally discovered KDViz and CiteSpace II while performing online research into the connectionbetween bodies of knowledge and ontologies. Dataset construction took place during September and

October, 2012, during which time there were numerous trial runs of CiteSpace II as part of the processof learning the software and determining the thresholds to be used in the final analyses. Multiple analysisruns on the dataset to finalize CiteSpace II settings, and to further refine the quality of the dataset tookplace during late October, 2012. The final dataset was completed and the final analyses and visualizationruns presented in this paper were conducted during early and mid-November, 2012. All analyses wereconducted on the authors desktop computer running on an AMD Phenom II X4 830 2.8 GHz,processor with 8 GB RAM, and Windows 7 64-bit operating system.

Design and Rationale

One of the difficulties in developing a KDViz study is that there is no singular analysis andvisualization method or rationale to be found that can be turned to for guidance. The research literaturecan be used to provide possible models of study design, and the literature on KDViz presented inChapter II was used as an essential resource. There are some frequently used methods, such as onlyusing in a co-citation analysis those dataset articles that have received at least 5-7 citations. Traditionallythis has been used to find out who those that are cited most in a field are themselves referencing. Thus,it helps focus knowledge domain visualizations on those most likely to be influential within theirdisciplines. Although this may be quite useful in a well-established scientific discipline, would it stillhold true for a small, multidisciplinary, emerging candidate discipline that may not have the sameresearch and publication pressures present in other disciplines? As it is believed that the answer is infact no, and because there may be other ways in which the nature of EDM might need to be takeninto consideration, research proceeded under four guiding principles/assumptions:

1. EDM is much smaller than even many of the specialties previously examined by KDViz,and its multidisciplinary nature may further decrease the likely number of citations articles receive,particularly in any EDM specialties that may exist.

2. The professional side of EDM does not have the tradition of research and publicationcommon to academic/scientific disciplines, and many professional disciplines like medicine and clinicalpsychology. Again this is a factor that would contribute to relatively low citation rates in some parts ofthe field. This would also suggest that citation totals may or may not necessarily represent howimportant or influential something is to the field.

3. Selection of articles for the dataset should come from a broad spectrum of possible coredisaster-related journals, rather than potentially influencing results with preconceptions of what EDMshould be by only searching for a particular term or using a single journal as the source of data.

4. Larger, more complex, and messier co-citation network visualizations will be preferable inthis study to smaller, more elegant appearing networks.

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The purpose of the study is to first visualize and understand as much of the EDM body ofknowledge and its structure as possible. A leaner network visualization, although this may be useful infuture studies, may likely not provide the full picture required to answer questions of disciplinary statusand structure. CiteSpace II threshold settings therefore should generally favor as much as possible,enlarging rather than contracting the intellectual base visualized (recall the work of Persson discussed in

Chen, 2006a, 2006b). This would need to be balanced with the practical limits of how large a networkvisualization CiteSpace II and the computer hardware used can handle before systemperformance/stability is substantially diminished; as well as the amount of time required for the programto process the analysis and produce a visualization.

Because KDViz has not been attempted before in EDM, all three forms of co-citation analysis(ACA, DCA, and JCA) would be included. Initially, an analysis and visualization of the Web of Science(WoS) subject categories of the citing articles was also to be conducted, but it was discovered, asconfirmed by Vargas-Quesada and de Moya-Anegn (2007), that multidisciplinary journals areclassified by WoS under multiple categories, regardless of the subject matter of the article (e.g. an article

on earthquakes in Natural Hazards would be classified under all three of the journals WoS subjectcategoriesGeosciences, Multidisciplinary; Meteorology and Atmospheric Sciences; and WaterResources). Any co-citations to the journal co-cite to all three subject categories. Many of the journalsincluded in the dataset are affected by this problem, and it fatally affects the validity of results obtainedunless each article is individually reassigned to a single WoS subject category based on article subjectmatter. Because of the additional effort and substantial time this would require, the analysis waseliminated from the research plan. It was also eventually decided that the three primary analyses weresufficient enough in themselves, and a plan to visualize the country affiliations of first authors in thedataset was also dropped.

Having established the basic principles/assumptions of the research approach, and the types ofanalysis to be included, attention turned to acquisition and construction of the dataset.

Dataset Construction Data for the study comes from the WoS bibliographic database. Access to WoS is generally only

available to institutional subscribers, such as university libraries and research centers. Access to WoSthrough the researchers home institution was not available, but visitor access was successfully obtainedthrough the University of Texas at Dallas McDermott Library. Prior to accessing WoS, an online listof WoS indexed journals was reviewed and eleven EDM-related journal titles were identified for researchinclusion. Additionally, based in part on the findings of Comfort, Waugh, and Cigler (2012),Public Administration Review and Administration and Society were selected for conducting a search for EDMarticles. For the eleven journal titles, all articles and proceedings papers indexed in WoS between 1986and 2011 were exported in the complete format (which includes cited references) as a series of text files.Multiple text files were required, as WoS limits the number of records that may be exported at once.The two public administration journals were searched in WoS for any articles or proceedings papersbetween 1986 and 2011 containing emergency management, or disaster in the title, subject, or

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keyword fields, and the records were also exported to file. Appendix A provides a sample of what the WoS data looks like in its original form.

The individual text files containing the WoS data were loaded into a duplicate removal tool that ispart of CiteSpace II. The tool also reorganizes the articles into new WoS text files organized by date.Only articles and proceedings papers were included for analysis. Examination of these files revealed

that many of the proposed study years had 10 or fewer articles, and that there was a distinct drop innumber of articles for years prior to 1994. This drop is seen in the distribution of dataset articles shownin Figure 3. For this reason, the research time period was established at 1994-2011. Test runs beganbeing conducted to learn and test both CiteSpace II and the data. It was during this process that asignificant problem with the dataset emerged, one that would take up enormous amounts of time andeffort to resolve.

If one looks closely at Appendix A, and specifically the cited references section of the original WoSrecord (abbreviated as CR) it may be noticed that there is great inconsistency in how the referencesare presented, including capitalization, punctuation, and even in how a name or title is spelled or

abbreviated. This problem was first discussed in the Introduction section of this paper. Thesediscrepancies will result in each variation of an authors name, journal title, or document, being treatedby CiteSpace II as separate entities, which will affect not only citation totals but also the constructionof networks. There is an alias function within CiteSpace II that is supposed to, in theory, allow suchvariations to be assigned to a primary alias. Unfortunately, this function is barely documented in theCiteSpace literature, and this author was unable get the function working properly. The eventualsolution decided upon was to edit the dataset, but this cannot be done using a regular word processingapplication, for WoS text files are in Unicode and follow a specific format. If the correct formatting isaltered, which can happen if normal word processing programs are used, it may result in the data beingunreadable to CiteSpace II. A moderate amount of online searching discovered the open source Unicodetext editor, BabelPad (West, 2012). BabelPad was used first to reassemble the individual files of thedataset into a single file, containing approximately 185,000 lines of text. This single data file wouldallow faster editing.

As a first step, all fonts used in the data were converted to uppercase. Then, a general system wasestablished for prioritizing the correction of the dataset. Results of trial CiteSpace II runs were used toprioritize by highest citation frequencies which authors, journals, and documents would be givenattention first. A format was created for standardizing any variations discovered. The standard formatfor author names used the last name, one space, then any initials without spaces or punctuation. Journaltitles were standardized by their WoS abbreviation. For book and government documents, astandardized title was simply decided upon. Not all items were changed to standardized versions: namesand titles were left as is if no variations were discovered. Correction was a slow and painstakingprocess, and required first searching for a particular name variation, changing all instances of thatvariation to the standard version, then looking for the next variation. On numerous occasions internetsearching was required to identify items when doubt emerged (e.g. D. Alexander mi

Documents

Visualizing the Invisible: Application of Knowledge Domain Visualization to the Longstanding Problem of Professional Conceptualization in Emergency Management