Reviews of concepts in knowledge organization series editor: Birger Hjørland domain analysis

Abstract

The domain-analytic approach to knowledge organization (KO) (and to the broader field of library and information science, LIS) is outlined. The article reviews the discussions and proposals on the definition of domains, and provides an example of a domain-analytic study in the field of art studies. Varieties of domain analysis as well as criticism and controversies are presented and discussed. © 2017 International Society for Knowledge Organization. All Rights Reserved.

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Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
436
Reviews of Concepts in Knowledge Organization
Series Editor: Birger Hjørland
Domain Analysis*†
Birger Hjørland
University of Copenhagen, Royal School of Library and Information Science,
Njalsgade 76, Room 4A-02-70, DK-2300 Copenhagen S, Denmark,
<birger.hjorland@hum.ku.dk>
Birger Hjørland holds an MA in psychology and PhD in library and information science. He is Professor in
knowledge organization at the Royal School of Library and Information Science in Copenhagen since 2001 and
at the University College in Borås 2000-2001. He was research librarian at the Royal Library in Copenhagen
1978-1990, and taught information science at the Department of Mathematical and Applied Linguistics at the
University of Copenhagen 1983-1986. He is chair of ISKO’s Scientific Advisory Council and a member of the
editorial boards of Knowledge Organization, Journal of the Association for Information Science and Technology and Journal of
Documentation. His H-index is 43 in Google Scholar and 23 in Web of Science.
Hjørland, Birger. 2017. “Domain Analysis.” Knowledge Organization 44(6): 436-464. 151 references.
Abstract: The domain-analytic approach to knowledge organization (KO) (and to the broader field of library
and information science, LIS) is outlined. The article reviews the discussions and proposals on the definition of
domains, and provides an example of a domain-analytic study in the field of art studies. Varieties of domain analysis as well as criticism
and controversies are presented and discussed.
Submitted: 6 April 2017; Accepted 26 April 2017
Keywords: domains, domain analysis, information science, knowledge organization, classification
* Derived from the article of similar title in the ISKO Encyclopedia of Knowledge Organization, Version 1.2; published 2017-06-28. Article cat-
egory: Methods, approaches & philosophies.
† Thanks to Eva Jansen for a careful and detailed critique of the first version of the manuscript, and thanks to Daniel Martínez Ávila for
serving as the editor, and together with two anonymous referees, providing valuable feedback and support. Finally, thanks to Bella Hass
Weinberg for a careful editing of a late version of the manuscript.
1.0 Historical background
1.1 Definition and main characteristics
Hjørland and Albrechtsen (1995) formulated domain anal-
ysis as a new1 approach to information science (IS) or li-
brary and information science (LIS)2. The article stressed
the social, ecological, and content-oriented nature of
knowledge as opposed to the more formal, computer-like
approaches that dominated in the 1980s. The article stated
that the most fruitful horizon for IS is to study knowledge
domains as thought or discourse communities, which are
parts of society’s division of labor. These aims have since
that time represented the core characteristics of domain
analysis. Seven years later, Hjørland (2002a) suggested
eleven ways in which information science may address a
given domain in a relatively specific way:
1. Production and evaluation of literature guides and
subject gateways;
2. Production and evaluation of special classifications
and thesauri;

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3. Research on competencies in indexing and retrieval
of information in specialties;
4. Knowledge of empirical user studies in subject areas;
5. Production and interpretation of bibliometric studies;
6. Historical studies of information structures and ser-
vices in domains;
7. Studies of documents and genres in knowledge do-
mains;
8. Epistemological and critical studies of different para-
digms, assumptions, and interests in domains;
9. Knowledge of terminological studies, LSP (languages
for special purposes), and discourse analysis in
knowledge fields;
10. Studies of structures and institutions in scientific and
professional communication in a domain;
11. Knowledge of methods and results from domain-
analytic studies on professional cognition, knowledge
representation in computer science, and artificial in-
telligence.
It can be seen that these points clearly include knowledge
organization (KO) as a part of the overall study of do-
mains (e.g., indexing, classification, and thesauri). These
eleven approaches emphasize that the objects of study
for information researchers are social and theoretical en-
tities rather than universal minds (which dominated the
field under the label “the cognitive view” at the time). In-
formation science is understood as the study of infor-
mation infrastructures, and is one among other fields in
the study of science. The eleven points are a mixture of
activities performed by (or suggested for) information
specialists on the one hand, and genuine approaches on
the other hand (in particular, 8: epistemological ap-
proaches, and 10: sociological studies). Epistemological
and critical studies are important, because that category
in particular defines domain analysis in the narrow sense
(cf., Section 4 below) and provides the link back to social
epistemology3 (cf., Egan and Shera 1952; Zandonade
2004). It was also stated (Hjørland 2002c) that: a) these
eleven approaches should ideally be combined,4 and b)
knowledge of these approaches—and in particular their
combination—provide the special competency of infor-
mation specialists. Smiraglia (2015, 97) proposed a slight-
ly revised taxonomy of the eleven approaches (leaving
out the third: indexing and retrieval of information in
specialties, and tenth: studies of structures and institu-
tions in scientific and professional communication—and
adding database semantics and discourse analysis). An-
other important suggestion for an addition to the eleven
points is knowledge about provenance, as suggested by
Guimarães and Tognoli (2015).
Smiraglia (2015) analyzed nearly one hundred research
reports in the field of KO in which domain analysis has
been used. He found (97-98) that it is clear that the
knowledge organization community has embraced do-
main analysis as a scholarly methodological paradigm for
the discovery of ontological bases and for the continuing
analysis of the evolution of scholarly communities. There
has been little applied research, however, reporting on the
development or evolution of pathfinders or subject
gateways, even in the face of expanding digital hegemony
over all human activity.
Domain analysis is a theory about and an approach to
LIS and KO. The objects of KO can be generalized to
be, in particular, about knowledge organization systems
(KOSs) and knowledge organization processes (KOPs)
(for example classification systems and the process of
classification). The objects of LIS include, in addition,
other issues, more or less covered by the eleven plus
three approaches presented above. Domain analysis ap-
proaches the issues of KOSs and KOPs from a com-
bined sociological and epistemological perspective and
emphasizes the importance of subject knowledge.
1.2 Subject knowledge and specialization
Domain analysis focuses on the importance of subject
knowledge; this was an important but relatively implicit
assumption for the founders of KO as well as of docu-
mentation, information science, and of the management
of libraries and information institutions and services.
Saracevic (1975, 333) termed this “the subject knowledge
view,” and suggested that it is fundamental to all other
views of relevance, because subject knowledge is funda-
mental to the communication of knowledge. In that pa-
per, he also mentioned the importance and urgency of
work on that view.5
Subject knowledge has been institutionalized in librar-
ies (particularly in research libraries) as well as in other
kinds of mediating institutions by employing interdisci-
plinary teams of specialists. For example, the Russian
State Library’s Department of Systematic and Subject
Catalogues was in 1990 the largest indexing unit of the
world’s libraries, with one hundred thirty staff specialists.
Nearly one hundred of them had a subject specialty plus
a second diploma in library science. All over the world, a
similar model was used and is to some degree still used.6
The tendency has been that the bigger the library, the
more specialized the staff (corresponding to the educa-
tional system: the higher the level, the more specialized
the teachers; no one would claim that general psychologi-
cal and pedagogical knowledge can replace subject
knowledge in university teaching). Of course, in small
public libraries with only one librarian, that person has to
cover every field, and is thus less professional in manag-
ing core information functions.

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Teams involving subject specialists were also consid-
ered essential for designing and updating knowledge or-
ganization systems (KOS) such as the Universal Decimal
Classification, and this is also assumed for indexing of
bibliographical databases of high-standards such as
MEDLINE7 and for the construction of advanced on-
tologies.8 Subject-knowledge specialists also used to be an
important part of the faculty of schools of library and
information science. By implication, information science
(with LIS and KO) must be understood as a metascience
(cf., Hjørland 2016a).
Within information science (or in adjacent fields),
there exist specializations such as chemoinformatics, digi-
tal humanities, geographical information science, legal in-
formatics, and medical informatics—often with their own
journals, conferences, and so on. The Association for In-
formation Science and Technology (ASIS&T) has (in
2017) special interest groups for, among other fields, Arts
& Humanities, Health Informatics, and Scientific &
Technical Information. Schools of LIS used to have spe-
cialized courses in, for example, the literature of the hu-
manities, social science, and science9 just as library associ-
ations were involved in providing guides for different
subjects (e.g., Webb et al., 1986).
1.3 Conflicting views
The domain-analytic view may be in opposition to the
view that it is possible to educate “the complete librarian”
(cf., Audunson et al. 2003). This expression implies that
one person can be “complete,” and can be understood as
an ideology developed by schools of LIS, because public
libraries have been their main target. From the point of
view of the library profession, it may be an advantage to
have libraries staffed with generalists rather than with in-
formation scientists representing different specialties (or
teams of people with different subject degrees in addi-
tion to a degree in information science). In other words,
professional interests may support tendencies towards
uniformity rather than diversity. Such a uniformity may,
however, lower the quality of the information services.
Many approaches to information science and KO (e.g.,
facet analysis, the cognitive view, and statistical taxonomy)
may be understood as attempts to pass over subject
knowledge (or at least not make subject knowledge ex-
plicit in their methodologies). Domain analysis, on the
other hand, makes subject knowledge an explicit and im-
portant part of the methodologies of information sci-
ence and knowledge organization. This makes KO and
information science part of science studies in a broad
sense. Just as philosophers, sociologists and historians,
for example, may study a given domain (such as medi-
cine), information specialists may also study the same
domain, but with a special focus on medical information
infrastructures, information retrieval, and the other areas
defined above (cf., Hjørland 2016a).
Domain analysis stands in contrary to the “one size
fits all” principle in information systems and services.
Bates (1987) considered domains “the last variable” in in-
formation science, and Mai (2010, 629) wrote that the li-
brary literature has generally not problematized the dif-
ferences and commonalities of different domains, and
seems to have assumed that general laws and principles
exist.10
1.4 Conclusion
Information science, LIS, and KO deal with mediating in-
formation, knowledge, documents, and culture. Any me-
diating act is always about some specific content pro-
duced by persons related to the different subject areas. To
mediate subject knowledge requires a degree of subject
knowledge (depending on the level of informing—
higher, for example, in research libraries as compared to
public libraries). Subject knowledge is not, however, the
“specific” qualification of LIS professionals. The specific
competencies of information specialists are information
infrastructures and information retrieval, etc. (the “eleven
plus three” points mentioned above). By implication, LIS
is a metascience or metafield. It is about, for example, the
optimization of the information infrastructures of disci-
plines,11 between disciplines, and for the larger society.
LIS may involve specialized services (such as MED-
LINE) or general institutions and services, such as na-
tional libraries and archives, public libraries, Google, Wik-
ipedia, and the Internet Archive. Domain analysis is the
methodology of LIS that considers the optimization of
information systems and services from the perspective of
their “specific” contents and requirements.12
2.0 What is a domain?
2.1 General definitions
According to WordNet 2, the noun “domain”13 has 5
senses:
1. sphere, domain, area, orbit, field, arena—(a particular
environment or walk of life; “his social sphere is lim-
ited;” “it was a closed area of employment;” “he’s out
of my orbit”);
2. domain, demesne, land—(territory over which rule or
control is exercised; “his domain extended into Eu-
rope;” “he made it the law of the land”);
3. domain—(the set of values of the independent varia-
ble for which a function is defined);

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4. world, domain—(people in general; especially a dis-
tinctive group of people with some shared interest;
“the Western world”);
5. domain, region, realm—(a knowledge domain that you
are interested in or are communicating about; “it was a
limited domain of discourse;” “here we enter the re-
gion of opinion;” “the realm of the occult”).
Some of these senses are related to the way the term is
used in domain analysis, but WordNET does not provide
criteria for distinguishing subject, discipline, and domain,
for example. A domain may be a discipline, but it need
not be; it can be distributed in multiple disciplines or spe-
cialties or be a non-discipline, such as a hobby. “Subject”
(Hjørland 2017c) is understood as the object of subject
analysis, which is also a different concept. A domain, on
the other hand, is a specialization in the division of cog-
nitive labor that is theoretically coherent or socially insti-
tutionalized. As can be seen below, domains are not
ready-made divisions of the world but are dynamic, de-
veloping, and theory dependent.
Prieto-Díaz, from the field of software engineering,
provided a definition of “domain analysis” (DA). He is
probably the first to connect the term with library and in-
formation science (“DA/LIS”), specifically to facet analy-
sis. He wrote (1990, 50)14: “In the context of software
engineering it [domain analysis] is most often understood
as an application area, a field for which software systems
are developed. Examples include airline reservation sys-
tems, payroll systems, communication and control sys-
tems, spreadsheets, and numerical control. Domains can
be broad like banking or narrow like arithmetic opera-
tions.”
Domain-analysis was used as a technical term in soft-
ware engineering and related fields before it was intro-
duced in LIS. Prieto-Díaz (1990) considered it equivalent
to faceted classification.15 Writers on faceted classification
in LIS did not use that term, however, and its methodol-
ogy is different16 from the approach introduced by Hjør-
land and Albrechtsen (1995), which may be termed “criti-
cal-hermeneutical,” emphasizing different interests, per-
spectives, epistemologies, and “paradigms” of domains in
classification (see further in Hjørland 2017b on different
philosophies of classification). This last sense is here
termed “DA/LIS narrow,” in contrast to “DA/LIS
broad,” which includes faceted classification and other
kinds of studies.
In addition to software engineering, the concept of
“domain” has been connected to cognitive science, where
the principle of domain specificity of thought is opposed
to the principle of general or universal cognitive mecha-
nisms (see, for example, Hirschfeld and Gelman 1994).
Cognitive psychology, in turn, is connected to artificial in-
telligence and the cognitive view in information science,
and may have influenced developments in computer sci-
ence and software engineering.
2.2. Shapere’s definition
Mai (2005, 605) stated that Hjørland and Albrechtsen
(1995) did not “clearly define what they mean by ‘do-
main.’” Mai (2008, 20) wrote that Hjørland and Al-
brechtsen lacked a concrete suggestion of how to opera-
tionalize the notion of a domain. At the same place he de-
fined “domain” as “an evolving and open concept that will
develop as the concept is used and applied in research and
practice.”17 He also wrote (21) that the “description and
designation of the particular domain to be analyzed de-
pends on the goal and purpose of the design; there is no
set way to determine domains.” Mai also quoted Rasmus-
sen et al. (1994, 35) “identification [of the domain] de-
pends on a pragmatic choice of boundary around the ob-
ject of analysis that is relevant for the actual design prob-
lem. This choice depends on the circumstances.”
Hjørland and Albrechtsen (1995), however, did include
a quote from Shapere and a reference to Hjørland (1994)
in which “domain” was further discussed and in which
the concept of “theory” becomes important. By consid-
ering the scientific characterization of electricity in the
18th century, Shapere (1977, 518) pointed out that what
we today consider the unified subject matter or domain
“electricity” is by no means an obvious conclusion. He
generalized this claim by pointing out that even though
researchers think of science as explaining things, it is not
clear that the things that science explains are really uni-
fied or have any natural unity in themselves. The range of
phenomena to which an explanation can be applied is in
itself controversial. He further wrote that nature does not
happen to come once and for all divided into “areas” or
“fields” for investigation on the basis of anything imme-
diately experienced. Although there are certainly observ-
able features, the sorts of entities to be studied is not a
matter of anything that could be called immediate or ob-
vious sensory characteristics (Shapere 1984, 323). There-
fore, Shapere (1977, 527) stated “that a body of infor-
mation constitutes a domain is itself a hypothesis that
may ultimately be rejected” and he arrived at the follow-
ing definition (528 emphasis original):
The domain is the total body of information for which, ideal-
ly, an answer to that problem is expected to account. In par-
ticular, if the problem is one requiring a “theory” as
answer, the domain constitutes the total body of in-
formation which must, ideally, be accounted for by
a theory which resolves that problem.

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Shapere further wrote that domains can be as broad as
the subject matters of fields such as electromagnetism,
genetics, or organic chemistry, or as narrow as the spe-
cialized interests of individual research workers.
Shapere’s point can be illustrated by considering the
domain “biology.” At the time of Carl Linnaeus (1707-
1778), zoology and botany were considered two different
domains. What later united these two domains into biol-
ogy was the cell theory—that all living organisms consist
of cells (first formulated in 1839 after more than one
hundred years of observation by microscopes). The do-
main “biology” is therefore the result of scientific theory
and research. For Shapere, domains are phenomena that
require careful and deep investigation simply to be de-
fined, and may be given different theoretical perspec-
tives.18 This accords with Mai’s understanding of domain
as “an evolving and open concept that will develop as the
concept is used and applied in research and practice.”
2.3 Ontological, epistemological and sociological
dimensions of domains
The definition of “domain” needs to consider both the
social and the cognitive dimensions of domains. Hjørland
and Hartel (2003) suggested that three dimensions inter-
act in the constitution of domains:
1. Ontological theories and concepts about the ob-
jects of human activity;
2. Epistemological theories and concepts about
knowledge and the ways to acquire knowledge,
implying methodological principles about the
ways objects are investigated; and
3. Sociological concepts about the groups of peo-
ple concerned with the objects.
The relationships between these dimensions are compli-
cated. Basic theories about these relationships are, for ex-
ample, forms of philosophical realism, social epistemolo-
gy and social constructivism. A broad family of theoreti-
cal positions are potentially relevant, including Bour-
dieuian theory on “field”19 and the concept “epistemic
community.”20 From the point of view of social con-
structivism, Dam Christensen (2007, 32) argued that a
knowledge domain does not exist in itself, but only in re-
lation to its frame. Domains are never unambiguous; in-
stead of wholes, stability, and closure, domains are char-
acterized by processuality, fragmentation, indeterminabil-
ity, performativity, or other words that may today be used
for dealing with this ambiguity. In other words, a domain
is never frozen in time and space, but is always changing,
although it may not seem so for either information pro-
ducers, users, or mediators in scholarly day-to-day prac-
tice. Albrechtsen (2015, 561) also expressed a construc-
tivist view: “‘Domains’ are not terrains out there, waiting
to be described and analysed by the initiated few. Funda-
mentally, we may all create them.” What does this mean?
As we shall see, domains are at the same time “given” and
“constructed.” In the first way, (A) domains seem to be
“out there, waiting to be described and analyzed,” but in
the second way, (B) Albrechtsen is right, we may all create
them. We now consider these two perspectives a little
more closely:
(A): When a person is born, the social world is already
organized, for example, with languages and their con-
ceptual distinctions, with social division of labor, with
school subjects, and with academic disciplines. We do
not all have the power to change that, although some
persons (e.g., deans) may have some power to change
an academic discipline at their own university. In this
sense, domains are terrains out there, and as such they
are described and analyzed by historians, sociologists,
anthropologists, and bibliometricans, among others.
(B): At the same time, domains are nothing but the
work of human beings, and if enough people decide
(actively or passively) to change a domain or the sys-
tem of domains, it will change (for example, if too
few people work hard to make a domain successful, it
may vanish). Therefore, Albrechtsen is right; we may
all contribute to creating a domain. This is also true in
the methodological sense to which Albrechtsen refers.
When we describe a domain, e.g., bibliometrically, the
methodology we use influences how that domain
looks. For example, the journals selected to map a
domain such as LIS will always be a choice reflecting
the researcher’s conception of LIS (see further in
Hjørland 2016a). Albrechtsen’s point is thus that map-
ping of domains cannot avoid the subjectivity of the
researcher, and the study of domains is like the her-
meneutical spiral: You start investigating domains
based on your pre-understanding. During your study,
your knowledge changes, and makes you change the
way you study the domain in a spiral.
It is important to understand the dual nature of domains
as intellectual organization on the one hand, and social or-
ganization on the other hand. Toulmin (1972/1977) differ-
entiated between the “content-knowledge” of a science [or
domain] and the “institutional aspects” of science, such as
professional forums, and suggested that science is generally
continuous, because either the content or the institution
will remain stable while the other changes. In response,
then, the former will adapt, in an iterative process of con-
stant change and constant stability. The dual nature of

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441
domains has been addressed in LIS by Fry (2006) and Fry
and Talja (2007), inspired by Whitley (2000). The social de-
velopment of domains is characterized by the findings that
the language of domains tends over time to become more
distinct from general language (owing to increased speciali-
zation) and the language use of individual domains tends
to become increasingly distinct from that of other domains
(owing to diversification, cf., Teich et al. 2016). Communi-
cation in domains may be modeled using biblio-
metric/altmetric methods or by considering the system of
actors, systems, and processes in domains, between do-
mains or from domains to the public sector (cf., Sønder-
gaard et al. 2003).
In Section 5 below, other aspects of defining “do-
main” are discussed, including a criticism of domains as
too related to academic disciplines as well as Tennis’
claim that one must define the area to be studied before a
domain analysis is started through the methodological
application of two axes (the modulation area and degrees
of specialization).
Smiraglia (2012, 114) found that:
A domain is best understood as a unit of analysis
for the construction of a KOS. That is, a domain is
a group with an ontological base that reveals an un-
derlying teleology, a set of common hypotheses,
epistemological consensus on methodological ap-
proaches, and social semantics. If, after conduct of
systematic analysis, no consensus on these points
emerges, then neither intension nor extension can
be defined, and the group thus does not constitute
a domain … It is the interactions of the ontologi-
cal, epistemological and sociological that define a
domain and reveal its critical role in the evolution
of knowledge.
This definition is close to the one suggested in the pre-
sent paper, and can almost serve as the conclusion of this
section. The definition highlights the consensus in the
domain, which is clearly highly important to consider. In
many domains (e.g., LIS), however, consensus seems not
to exist, and it would seem problematic to obtain from
domain analysis in those cases. In cases with no or little
consensus, the role of the domain analyst in actively con-
tributing to the creation of the domain will be more
dominant (and therefore obtain a role that is less distinct
in relation to researchers in the domain).
2.4 Conclusion
A domain is a body of knowledge, defined socially and
theoretically as the knowledge of a group of people shar-
ing ontological and epistemological commitments. Do-
mains are often academic disciplines, but may also be, for
example, hobbies.21 Different theories and social interests
may construe domains differently, and therefore the classi-
fier should be explicit regarding the interests and theoreti-
cal views on which the construction is based. From the
perspectives of LIS and KO, it is important to optimize in-
formation exchange in domains; therefore, domains need
to have a certain level of stability and infrastructure22 in
order to be good candidates for domain analysis.
3.0 An example: domain analysis of art history
This section aims at providing a model of a domain-
analytic study. Different researchers may have different
views on what represents a good example. Talja (2005)
provided some examples and Hourihan Jansen (2016)
found that “given the growing pluralism of approaches, it
appears there is no quintessential research design for do-
main analysis.” Hjørland (1998b) provided an analysis of
the domain “psychology” from the perspectives of em-
piricism, rationalism, historicism, and pragmatism, which
formed the basis for his general understanding of classi-
fication (see Hjørland 2017b, Section 42c). In this paper,
however, Ørom’s domain analysis of art studies is pre-
sented as a model. Ørom (2003)23 presented and dis-
cussed the following “paradigms” in art history and art
scholarship (here with subheadings subordinated to the
metastructure of the present article).
3.1 Cultural history
Ørom (2003, 134) wrote that Jacob Burckhardt (1818-97)
aimed at describing the panorama of an entire age and
“within this panorama he set the visual arts at or near the
centre of the defining characteristics of an age.”
3.2 The iconographic paradigm
Erwin Panofsky created his iconographical paradigm in
the tradition of cultural history. His iconographic analysis
(which included a stylistic analysis) aims at the interpreta-
tion of the intrinsic and symbolic meaning of images.
The interpretation of this intrinsic meaning is based on
the study of contemporary philosophy and literature.
The focus of the iconographic paradigm is allegorical
and symbolic meaning. Panofsky studied the Renaissance
and the Baroque period. Works of art from these periods
have a privileged status for the scholars who subscribe to
this paradigm. In general, the art-historical tradition for
cultural history (E. H. Gombrich) and iconography have
high culture in focus.

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3.3 The stylistic paradigm
According to Ørom, the stylistic paradigm was established
around 1870 and later developed by Heinrich Wölfflin,
who “considered that laws governed the ways in which
forms changed through time” (Ørom 2003, 135) and:
Based on stylistic characteristics (for instance linear
versus painterly and plane versus recession) Wölfflin
grouped works into related categories. The analysis
of style became the basic and defining method of
the stylistic paradigm in art history and the object
was the works of art belonging to high culture.
The object of the stylistic paradigm is the formal
aspect of the work of art (style, composition, way
of painting and the like). The aim of the stylistic
analysis is to describe, categorize, compare, and sys-
tematize these stylistic features in order to deter-
mine a sequence of historical styles. It means that
the overriding principle in knowledge organiza-
tion—whether in art exhibitions, art histories or
KOS—is the historical sequence of styles.
As a consequence of the focus on styles the inter-
textuality is limited to works of art, i.e. the history
of art is conceived of as an autonomous history.
The meaning of the works of art is beyond the
horizon of this paradigm. The way works of art are
analyzed and organized in taxonomies is similar to
Linné's principles in “Systema Naturae” in which
the forms of nature in the animal kingdom, the
vegetable kingdom, and the mineral kingdom are
analyzed systematically and grouped in families,
species, and so on.
Ørom describes the iconographic and stylistic paradigms
as “the traditional paradigms.”
3.4 The materialistic paradigm (social history of art)
This paradigm was developed in the 1940s and 1950s by
Arnold Hauser, among others. It is based on (Ørom
2003, 137; Fernie quotation in original):
the Marxist thesis that the economic base condi-
tions the cultural superstructure and that as a result
styles vary according to the character of the domi-
nant class” (Fernie, 1995, 18). Within this paradigm
the social functions of art and the sociology of art
are studied … The works of art are considered as
integrated elements in the historical and social con-
text. This materialist conception of art is diametri-
cally opposed to the general Western idea of au-
tonomous art. The materialist paradigm aims at an-
alysing the meaning and the function of art in the
context of material, social, political, and ideological
structures (at the time when the works of art were
created). This paradigm does not understand the
evolution of the art as being continuous. Changes
in the power and class structure cause changes in,
and ruptures with, the artistic tradition.
3.5 Changes in the domain of art history and art
scholarship
Ørom (2003, 139-40) wrote that in the early 1970s, “new”
art historians with different theoretic orientations started
criticizing the “traditional” paradigms. Criticisms included:
the narrowness of the way in which art was defined and
studied, the focus on individual artists, the limited scope of
methods (analysis of style or iconography), and the con-
centration on canonical works of art. In some ways, these
“new” art historians in their “new” art historical practice
were inspired by the social history of art. In general, they
conceive of art in a broader social context, including pow-
er structures and the relations between artists and the pub-
lic. In this view, the structures of meaning have changed.
3.6 Ørom (2003, 141-42) came to the following
general conclusions:
1. First, different socially and historically embedded dis-
courses on art, including pre-paradigmatic studies and
scholarly paradigms pervade knowledge organization
in the art institution at three levels. These three levels
are “articulated” respectively as:
a. Art exhibitions,
b. Primary and tertiary document types (printed, au-
dio-visual, and multimedia documents), and
c. Classification systems, bibliographies, thesauri (and
other secondary document types).
2. Concerning the general discourse in which art is un-
derstood, there is a marked (ideological) difference be-
tween the Soviet BBK [Bibliote no-Bibliografi eskaja Klassi-
fikacija] on the one hand, and Western classification
systems (DDC [Dewey Decimal Classification], LCC [Li-
brary of Congress Classification], and UDC [Universal
Decimal Classification] on the other.
3. Though the universal classification systems as such are
constructed on the basis of (formal) rational and logi-
cal structures, analysis of the art classes shows that the
substantial “layers” “beneath” the rational structures
are constructed as “bricolage” works.
4. The systems analyzed, including the sketched analysis
of UDC, show that there are significant differences

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443
among the four systems, both regarding the under-
standing of art (which is a part of the discourse) and
regarding the concepts of the “bricolage” work. The
LCC system is the one that to a lesser extent includes
concepts from the “traditional” paradigms—the icon-
ographic and the stylistic paradigms. In other words,
scholarly conceptions are of minor importance as
compared to general formal structures in this system.
The opposite is the case with UDC, in which substan-
tial parts of the taxonomy are constructed based on
“traditional” paradigms. The DDC system can be
placed in between LCC and UDC.
5. The taxonomy of the BBK is based on the Marxist
conception of art and has a less “bricolage” like struc-
ture, because the “deep” structure is more rational
than that of the other classifications, as a result of an
overriding theoretically-based construction. On the
other hand, this “firm” construction creates “blind-
ness” in the sense that non-Marxist concepts tend to
be excluded or negated.
6. In simple terms, it can be concluded that the UDC, in
particular, is well suited for representation of
knowledge produced in the contexts of pre-
paradigmatic, iconological, and stylistic studies.
7. During the recent three decades, the so-called “new”
art history or the “new” art scholarship, has developed
interdisciplinary approaches, or paradigms, that break
with both the general discourse on art and the “tradi-
tional” paradigms. This means that the “new” art his-
tory, by introducing new contexts and new theoretical
positions, breaks with the principles (and practice) of
knowledge organization at the three levels noted
above. From a library and information science
(LIS/KO) point of view, the challenge is to be able to
represent the documents produced by the “new” art
scholars in (theoretically) adequate ways, in addition to
the representation of the entire historical corpus of
documents on art.
8. The central problem is that a hierarchical system based
on “traditional” discourse combined with concepts
from the “traditional” paradigms, is “conceptually
closed.” At a pragmatic level, a “polyhierarchical” the-
saurus, such as the Art & Architecture Thesaurus, seems
to be a step towards a solution of some problems
raised by the approaches of the “new” art history. Be-
cause the Art & Architecture Thesaurus is a more “open”
and more expanded work of “bricolage” than univer-
sal classification systems, it is easier to integrate new
aspects of art studies into the facet structure.
9. At a theoretical level, however, the eclecticism and the
“additive” view of conceptual relations mean that the
Art & Architecture Thesaurus has a problematic episte-
mological foundation.
3.7 Conclusion
This summary of Ørom (2003) demonstrates that:
1. Organization of art exhibitions, and of knowledge
recorded in comprehensive works on art and in LIS
classification are influenced by the same paradigms. In
other words, LIS classification is not independent and
cannot ignore paradigms in the domains with which it
deals.
2. LIS classification schemes more or less reflect and
support certain paradigms in a domain, and some par-
adigms may be badly served by existing classifications.
3. The construction of a classification needs to identify
the basic paradigms in the domain and make a choice
or a compromise between (or among) them.
It seems clear that information specialists who have under-
stood Ørom (2003) are in a better position to organize
knowledge, as well as to use existing KOSs for retrieving
information in the domain of art. One could ask whether
information specialists who have acquired this knowledge
have also learned something that can be generalized to
other domains. The answer is yes, on an abstract level; in-
formation specialists will be prepared to look for different
“paradigms” (and their associated criteria of relevance). In
addition, there are certain similarities between paradigms in
different domains. Because of this, knowledge of a philo-
sophical nature (e.g., positivism, hermeneutics, and critical
theory) can be generalized.
4.0 Varieties of domain analysis
Disciplines other than information science and
knowledge organization use the term “domain analysis.”
As mentioned above, the term was used in the field of
computer science before its introduction in the literature
of information science at the beginning of the 1990s. In
this section, a preliminary classification of the various
types of domain analysis is presented.
4.1 Domain driven design
In software engineering, “domain analysis” is the process
of analyzing related software systems in a domain to find
their common and variable parts. Neighbors (1980)
coined the term. This field, also known as “domain-
driven design” (DDD) is huge. Here we apply the term
DDD to this kind of domain analysis in order to distin-
guish it from other kinds. Among the works on DDD are
Arango (1994), Evans (2003), Lisboa et al. (2010), Millett
and Tune (2015), Prieto-Diaz (1990), Prieto-Diaz (1991),
Vernon (2013 and 2016).

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Albrechtsen (2015, 558), citing Prieto-Diaz (1991),
presented facet classification as a kind of domain analysis
in the DDD meaning:
From the point of view of classification research,
Prieto-Diaz’s approach is especially interesting be-
cause its main theoretical basis is Ranganathan’s
theory of faceted classification. Prieto-Diaz devel-
oped a faceted scheme for classification of software
components and introduced the term “domain
analysis” for the analytic-synthetic approach that he
suggested.
This passage is somewhat confusing, however. Facet-
classification has never used the term “domain analysis”
(but employs the term “special classification”) and has
never applied a methodology related to DDD (but it is
mainly based on logical division, cf., Mills 2004). Facet
classification does not share the “critical-hermeneutical”
approach view of Albrechtsen.24 Domain-analysis in the
sense introduced by Hjørland and Albrechtsen (1995) is
therefore considered to be different from DDD.
4.2 Domain-specific modeling
A second approach is termed “domain-specific model-
ing” (DSM) or “ontology-driven domain-specific model-
ing.” It seems to be a framework related to DDD. See,
for example, Banerjee and Sarkar (2016), Kelly and Tol-
vanen (2008), Tairas et al. (2008), and Walter et al. (2014).
4.3 Work domain analysis as a part of cognitive
work analysis
A third approach is termed “work domain analysis.” This
term has been used in relation to problems correspond-
ing to the approach considered in KO and LIS. Work
domain analysis is part of cognitive work analysis (CWA),
a methodology and conceptual framework developed by
Jens Rasmussen and Annelise Mark Pejtersen, from the
Risø National Laboratory in Denmark (see Rasmussen et
al. 1994).25 The focus of the CWA framework is analysis
of the interactions between humans and their cognitive
processes, technology (information systems) and work
domains (work environments and tasks). Mattsson’s the-
sis (2016) (in Danish) is about the use of CWA in the de-
sign of controlled vocabularies. The author examined an
approach for the design of classification systems based
on CWA that was described by Albrechtsen and Pejtersen
(2003). Using a national film-research archive as a case,
they articulated a methodology for developing a classifi-
cation system intended to support the decision-making
of the actors during information retrieval. Mattsson
found (2016, 41ff.; the following four quotations are here
translated from Danish):
– The classification itself (the semantic structure)
was not a product of the CWA, but of the dia-
log between the user and staff.
– Another premise for generalizing the implication
of this cooperation is that the structures represent
prototypical user needs (Albrechtsen and Pej-
tersen 2003, 223). It is not discussed or explained
why they should be considered prototypic.
– Absent from the article is an analysis of differ-
ent epistemological positions in the domain.
This is important because domain analysis with-
out epistemological analyses tends to be superfi-
cial because epistemology provides insight into
the assumptions of theories about user behavior.
Epistemology thus provides a foundation for
evaluating present systems (Hjørland 2002a).
– The facets are, in my reading of the article, to a
large extent derived from the staff of the archive
on the basis of their experience and background
knowledge applied to the specific problems of the
users .… What seems to be missing in this inves-
tigation is a discussion of the validity of the
staff’s “expert knowledge.” The domain “film ar-
chives” is not defined or delimited, and it is there-
fore unclear whether it represents the three film
archives investigated or film archives in general.
There is no discussion of the theories or assump-
tions underlying the decisions of the actors. To
construe a classification ought to mean that one
knows about, and takes a stand on, the assump-
tions, which underlie the production of
knowledge. Such assumptions influence how an
actor classifies something (and thereby have an in-
fluence on the semantic structures studied in this
investigation). The aspects of the information
needs that the expert identifies must depend on
assumptions related to film studies as well as to
studies of information searching. The designer of
classification systems in the domain needs to
know about the different theories and paradigms
in film studies [see, e.g., Stam 2000]. It may be
problematic to take “the expert’s” (i.e., archive
staff’s) guidance of users as the measure for un-
derstanding their information needs. It is as if the
applied method leave the analysis of user needs to
a “black box” in the form of an expert.
Work domain analysis in CWA (like DDD) differs from
domain analysis as understood in the present article, by
avoiding theoretical involvement with the domain, for ex-

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445
ample, by not considering ways of “classifying” films,26
by genres (Bondebjerg 2001). Work domain analysis
(CWA) has not provided an example of a classification
system constructed on the basis of the suggested meth-
odology.27 At most, CWA has been able to demonstrate
the need for classification systems.
4.4 Domain analysis as a “knowledge elicitation”
technique
A fourth sense of domain analysis is used by Lykke-
Nielsen (2000) in the paper “Domain Analysis, an Im-
portant Part of Thesaurus Construction,” of which was
written (Hjørland 2002b, 259-60):
The methodology for thesaurus construction de-
scribed in Lykke Nielsen (2000) is a combination of
group interviews and word association tests to col-
lect data and content analysis and “discourse analy-
sis” to analyze data. The “domain” or “discourse
community” is a specific Danish pharmaceutical
company. Given the purpose and conditions of this
research, I have no serious objections to the methods
used. On the contrary, I welcome this initiative as tal-
ented and relevant. We need very much this kind of
information research that goes into foreign fields and
develops tools for their optimal information gather-
ing. I wonder, however, if the term domain analysis
is well chosen and whether it is in accordance with
my and with other people’s use of this concept.
The data collection methods described in Lykke
Nielsen (2000) are well known in AI (artificial intel-
ligence) as techniques or methods of knowledge
elicitation. If you are going to build an expert sys-
tem, you have to get the expert knowledge from
somebody or somewhere. An obvious solution is to
elicit the needed knowledge from somebody con-
sidered an expert on the task or issue. Cooke
(1994), for example, presents a variety of such
knowledge elicitation techniques, including group
discussions and free associations. Such methods
have primarily been considered of a psychological
nature, while the domain-analytic methods that I
have been a spokesman for have mainly been of a
sociological and epistemological nature.
Lykke Nielsen’s use of the term “domain analysis” thus
seems misplaced for two reasons: 1)what was analyzed
was a company rather than a domain; and, 2)the tech-
nique used is known as “knowledge elicitation” and is as-
sociated with cognitive views rather than with epistemo-
logical-sociological views.
4.5. Domain analysis in LIS (broad sense)
A fifth sense of domain analysis in knowledge organiza-
tion may be termed “the broad meaning of domain analy-
sis” (DA/LIS broad). In the broader sense, domain analy-
sis includes bibliometric mappings and facet analysis (or
any of the 11 points considered separately) of disciplines
or other domains. Smiraglia (2015) may be classified as one
of the documents belonging to this broader interpretation
of domain analysis. As stated by Albrechtsen (2015, 559),
however, “it needs to be highlighted that the development
of knowledge organization systems for specific domains is
not, in and of itself, a domain analysis.” (The same applies
to bibliometric mapping, for example).
4.6. Domain analysis in LIS (narrow sense)
In the sixth and narrow sense (DA/LIS narrow), studies
are therefore considered domain analysis only if they con-
sider different theories, “paradigms,” or traditions in the
domains. The reason is that a domain is not “given” to the
domain analyst, but is something that involves the consid-
eration of perspectives, goals, values, and interests in the
constitution of a given domain (cf., Hjørland 2016a).
4.7. Conclusion
This section provided a preliminary classification and
evaluation of different domain-analytic approaches. The
section thus uncovered different interpretations of do-
main analysis, including those within the field of
knowledge organization. Six different senses of domain
analysis were discussed. The sixth sense corresponds to
the one originally suggested by Hjørland and Albrechtsen
(1995) and to the methodology used by Hjørland (1998b)
and by Ørom (2003), which was presented in Section 3
above; this methodology may be considered a social epis-
temological approach.
There seems to be a tension, also within KO, between
approaching domain analysis from more positivist ideals
or from more critical-hermeneutical ideals, as we shall
now observe in Section 5.
5.0 Criticism and controversies
5.1 The need for an
a priori
operationalization of
domains
Not all researchers find the hermeneutic spiral in domain
analysis satisfactory. Castanha et al. (2016, 219) wrote:
According to Tennis (200328; 2012), before starting
any Domain Analysis, one must define the area to

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be studied, specify the scope of this analysis by the
two axes and establish the ultimate purpose of the
analysis.
The two axes suggested by Tennis (2003, 193) are: 1) are-
as of modulation; and, 2) degrees of specialization29:
– The Areas of Modulation, axis one, is an explicit
statement of the name and extension of the do-
main examined. It states what is included, what is
not included, and what the domain is called.
– Degrees of Specialization qualify and set the in-
tension of a domain. It may be neither desirable,
nor feasible, to describe an entire domain. The
whole domain may have a name and an exten-
sion that can be defined, but it may not easily
lend itself to analysis. Thus, the domain must be
qualified. By qualifying a domain, its extension is
diminished and its intension in increased. For
example, to study Hinduism is not to study all of
Religion. The qualified domain is Hinduism.30
Tennis posited that these axes should serve as analytical
devices for the domain analyst to delineate what is and
what is not being studied as a domain analysis. He consid-
ered that both are necessary for setting the parameters of a
domain. Khalidi (2013, 120-122) also introduced two di-
mensions of a domain—the spatiotemporal and the aspec-
tual—but he found that there may be no way of fully spec-
ifying the latter without circularity, that is, without referring
to the laws, causal processes, entities, properties, and kinds
that are characteristic of that level. Khalidi’s circularity
seems to correspond well with Hjørland’s critical and her-
meneutical methodology on how to analyze domains.
Tennis is obviously right that some decisions must be
made before a domain analysis is started, in particular, the
goal of the analysis is highly important. The quote by
Castanha et al. (2016) and others seem, however, to sug-
gest an a priori determination of a domain that is simply
impossible from the hermeneutic point of view. As ar-
gued by Khalidi (2013, 122):
For any given domain, D, there may be no way of
specifying necessary and sufficient conditions to
single out the purview of D in terms not derived
from the theory or theories that apply to D, since
even the individuals identified in a domain are gen-
erally picked out against the background of the
theory or theories prevalent in that domain. And:
Domains are both spatiotemporal and aspectual,
but they may not be capable of being individuated
noncircularly without recourse to the theories,
properties, and kinds that occur in those domains.
Tennis (2012) illustrates this with a narrow and well-
defined domain: Shakerism.31 In knowledge organization,
however, we often have to construe classifications in a
top-down fashion, starting with the total universe of
knowledge or with disciplines such as biology, chemistry,
psychology or religion (e.g., designing a universal classifi-
cation or a thesaurus for a given discipline). From this
perspective, Tennis’ example seems unusual in that it
suggests a bottom-up strategy. Let us also examine Ten-
nis’ criticism (2003, 193) of Hjørland’s domain analysis
of psychology:
Hjørland (1998[b]) has offered a rigorous analysis
of Psychology from an epistemic point of view. He
reviews the many ways Psychology might be de-
scribed as a domain. Because “classification of a
subject field is theory-laden and thus cannot be
neutral or ahistorical,” (Hjørland, 1998[b], p. 162)
Hjørland seeks to show “how basic epistemological
assumptions have formed the different approaches
to psychology during the 20th century” (Hjørland,
1998[b] p. 162). And precisely because the classifi-
cation of a subject field (its domain analysis) is the-
ory-laden, the basic question arises: whose psychol-
ogy does Hjørland analyze? What is its extension?
Is Hjørland’s psychology, an academic psychology,
the same psychology as Naropa University’s
Transpersonal Psychology? …
He [Hjørland] provides the reader with an introduc-
tion to a variety of psychologies in his 1998 article.
One example is psychoanalysis. Yet, when taken as
a whole these psychologies are called “traditional
mainstream psychology” (Hjørland, 1998[b] p. 176).
We are left unsure of the scope, the extension and
intension of the domain under study. The reader is
provided with an open concept of psychology, ra-
ther than an operationalized concept of psycholo-
gy.
This example illustrates very well the problem of the
hermeneutic spiral (see also Hjørland 2016a). In order to
examine a domain, you must know something about that
domain, and this knowledge determines what you do and
influences the results of your research. There is simply
no way to escape this hermeneutic spiral, but that does
not mean that there are no criteria for what counts as
good research. For example, a mapping of psychology
may
a. Take as its point of departure a literature32 in which
transpersonal psychology is relatively well represented;
or,

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b. Take as its point of departure a literature in which
transpersonal psychology is not well represented (or
not represented at all).
The selection of (a) or (b) must be considered a method-
ological and theoretical choice made by the domain ana-
lyst that needs justification (although it is often implicit,
unconscious, and influenced by the domain analyst’s
(sub)culture and training, or by the availability of sources,
and therefore not considered a theory).
Some views on psychology (and on all other domains)
are more established and influential than others. The
most influential views are often represented by prestig-
ious universities,33 journals, and publishers (the institu-
tionalized aspect of a domain). People may, however—
rightfully or wrongly—disbelieve mainstream views or
ruling ideas (the content or cognitive aspect), and may
fight to get alternative views accepted and made influen-
tial. For domain analysis, this means that choices should
be well informed; domain analysts should have broad and
deep knowledge about theories of the domain (in case
psychology) with which they work. It also means that
domain analysis cannot be neutral, but it will always sup-
port some views at the expense of other. Therefore, if
Tennis wants to make “Naropa University’s transpersonal
psychology” an important part of his domain analysis of
psychology, he should provide an argument (in this case
in particular, because it is not generally recognized as an
important view of psychology). The suggestion made
here is that we have to take the mainstream view as the
point of departure, and examine its implications and
philosophical assumptions, including the social interests
that have formed modern psychology. Such work often
leads to a minority view (and could lead to the view that
“Naropa University’s transpersonal psychology” is the
most important psychological view). We should not be
afraid of defending minority views, for, as Kierkegaard
([1850] 2015) said, “the minority is always right.”34 Again,
to describe or model a domain requires a theory of that
domain,35 and to make domain analysis is to participate in
the construction of the domain.
5.2 The need for universal classifications
5.2.1 Universalism
Szostak et al. (2016) is probably the most recent and
comprehensive discussion36 of universalism in classifica-
tion and a more focused presentation of this view is
Gnoli and Szostak (2014, [1]):
Supporters of domain analysis claim that the only
solution to these challenges [cultural biases implied
in universal systems] is to develop a plethora of sys-
tems explicitly biased, each representing the perspec-
tive of a different community. However, the current
evolution of information systems brings a further
need in front of us that domain analysis alone can-
not solve: that of interoperability.
Let us consider this quote. In recent years, there has been
a revolution in biological classification, for example, in
the classification of birds (see, e.g., Fjeldså 2013). The
point of view of domain-analysis (and common sense?)
is that this new classification, when firmly established,
should be used both in special biological classifications
and in universal classifications (if these are not to be ob-
solete), just as we should expect this new knowledge to
be recorded in books about birds and taught in public
schools, etc. In other words, a universal classification
should be considered the sum of a number of domain-
specific systems (birds, cars, countries, religions, sciences,
etc.). In order to classify birds (or in order to classify
documents about birds), we do not need a universal clas-
sification (although Mills 2004 claimed this37), but in or-
der to develop a universal classification, we need to know
how to classify living organisms, including birds. Ad-
vanced classification systems such as the UDC have
therefore relied on domain-specific knowledge and sub-
ject specialists. Whether or not there is one “best” classi-
fication of birds, or what kinds of classification are need-
ed for different purposes, constitute other questions.38
These questions, however, can be addressed only by peo-
ple involving themselves with bird classification and its
methodology. It is problematic to believe that a priori
principles (learned in schools of LIS or in philosophy or
elsewhere) provide a satisfactory solution.39 In other
words, domain-specific knowledge is always needed in
classification. This is the first answer to the issue raised
by Gnoli and Szostak (2014). Other issues are discussed
below.
Fox (2016, 379) has put forward another argument for
general classifications:
Domain analysis (Hjørland 2004, 18), which treats
users as “belonging to different cultures, social
structures and ... communities that share common
languages, genres and other typified communication
practices” is another proposed option that has met
with acceptance in the field. However, by defini-
tion, domain analysis caters to prescribed domains,
and thus has limited effectiveness for general col-
lections, and moreover, identity categories such as
gender and race relate to many human activities and
have relevance across collections and domains.

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As has already been argued, general collections can be
seen as sets of more specific domains (e.g., birds) that
need to be classified. “Gender” and “race” play a double
role in classification: 1) they are subjects that need to be
classified by knowledgeable people in those domains;
and, 2) they have given birth to critical epistemologies
(feminist, Marxist, and postcolonial epistemologies40)
and, thus, classification criteria that “have relevance
across collections and domains.” Fox’s reservations about
domain analysis therefore seem misplaced.
5.2.2 Ontology and epistemology
There is a related difference between domain analysis and
the view of Szostak et al. (2016, 72-73, notes omitted)
concerning the role of epistemology in classification:
Gnoli (2007) argued that classification systems are
best grounded in both ontology (an understanding
of what things exist in the world and how these are
related) and epistemology (an understanding of how
scholars study things). The domain-specific approach
leans heavily on epistemology: it seeks to ground
classifications in an understanding of how scholars
in that domain operate. Comprehensive classifica-
tions can and should have an ontological base. Yet
most comprehensive classifications rely on disci-
plines as a classificatory device and are thus to a con-
siderable extent largely epistemological in approach.
The sort of classification advocated in this book is
grounded in ontology, for it is grounded in the phe-
nomena (things) that exist in the world. Yet as noted
above the details of such a system are worked out
with careful attention to how scholars study things.
Szostak et al. (2016) recognized the need for domain analy-
sis and López-Huertas (2015) addressed the application of
domain analysis to interdisciplinary fields. In the quote
above the point of view seems to be that we have direct
access to things in the world and may distinguish and de-
scribe them independently of our concepts and theories.
This is the opposite of the domain-analytic view that any
ontology is based on epistemological assumptions. Szostak
and his coauthors need to defend their view.41 Although
they claim that classification systems are best grounded in
both ontology and epistemology, they need to explain how
ontological analysis can be done independently. Again, tak-
ing birds as an example, we may perhaps agree that the
new classification proposed by Fjeldså (2013) should be
preferred; however, the argument regarding why it should
be preferred must always be based on a consideration of
the scientific basis of the classification and thereby its epis-
temology. It is simply not possible to make advances in
bird classification independently of research and theory.
This can easily be seen by considering the history of bird
classification (e.g., Bruce 2003).
The quote above from Szostak et al. (2016) connects
epistemology with discipline-based classification, and on-
tology with phenomena-based classification; however, ra-
ther than disciplines, “theories” are what is behind differ-
ent ontologies (A discipline may contain several theoreti-
cal views, as demonstrated by Ørom in Section 3, above,
just as a given theory may be distributed in different dis-
ciplines). Influenced by the philosophy of Kuhn (1962)
and many others, it is an important thesis in the contem-
porary philosophy of science that our observations and
classifications are theory-laden. The idea of describing
things in the world in an atheoretical way is therefore na-
ïve. All classification depends on the methodology used,
which is again connected to epistemology (see further in
Hjørland 2017b). Epistemology is therefore not just a
requisite for discipline-based classifications, but also for
phenomena-based classifications.
5.2.3 Interoperability, standardization and the needs
of interdisciplinary research
Szostak has emphasized in many publications that we
need classifications that serve interdisciplinary research
(and thus are not tied to single disciplines). He has argued
(Szostak 2010 and 2013) for the complementary pursuit
of domain analysis and a universal classification, which
would at least ensure that the concepts of a domain’s lit-
erature are well captured in the universal classification.
He also finds it advantageous to have domain-specific
classifications that are translatable into the universal.
As described above, however, a universal classification
cannot be made without considering the specific contents
(e.g., birds) and the problem of different meanings seems
not to be associated with disciplines as much as with the-
ories. Given that we have different theories in which
terms have different meanings and which implies differ-
ent classification, how can we obtain interoperability and
satisfy the needs of interdisciplinary research?
In papers such as Gnoli and Szostak (2014), the need
for standardized classification and interoperability seems to
influence the authors in a way that drives out the under-
standing of the theory-dependency of meanings and clas-
sifications. It is argued that universal classification systems
“are necessary in an era that values interoperability. Such
systems have numerous other advantages.” The arguments,
however, seem more like wishful thinking than an academ-
ic investigation of the conditions and implications of es-
tablishing such universal systems (or standardized sys-
tems42). If different theories imply different classifications,
then a standardized classification makes one theoretical

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449
view authoritative (and if this is not made explicit, then it is
to make a subjective choice disguised as objectivity).
Another issue is also related to interdisciplinary re-
search: the dynamics of specialties and disciplines. This is
addressed by Tengström (1993, 12), who emphasizes that
cross-disciplinary research is a process, not a state or
structure. He differentiates three levels of ambition for
cross-disciplinary research:
– The pluridisciplinarity or multidisciplinarity level;
– The genuine cross-disciplinary level: interdisci-
plinarity; and,
– The discipline-forming level: transdisciplinarity.
Tengström suggested that library and information science
started as a pluridisciplinary activity, and is on the way to
becoming a discipline. By implication, interdisciplinary re-
search may not need standardized classifications, that are
common for all disciplines, but is in the process towards
developing a new classification that accords with its own
special needs (this is a model of how new scholarly fields
develop).
Hjørland (2016b, 320) discussed the best solution for
creating interoperability, and found that the solution for a
classification to serve as a “boundary object” or “episte-
mological hub” for defining and classifying objects
should probably be outlining the most important alterna-
tive theories, their conceptions, and classifications. Then
a conversion table or “crosswalk” should be established.
5.3 Resistance to study scholarly domains
In the field of KO there seems to be a certain skepticism
considering scholarly disciplines. We saw above in Section
4 that Albrechtsen and Pejtersen (2003) did not consider
film genre or research in film studies when they were in-
volved in designing of a classification system for a na-
tional film-research archive. Far too few papers in LIS
and KO study domains from the perspective of philoso-
phy of science and science studies. López-Huertas (2015)
also failed to illustrate her discussion with concrete ex-
amples. In LIS and KO there seems to be resistance to
the study of concrete domains, whether they are disci-
plines or interdisciplinary fields. After all, it is an im-
portant part of our historical heritage to classify all
knowledge domains, disciplines, interdisciplinary fields, or
phenomena, expert groups for the UDC, for example.
5.4 Critique of the idea of a common theoretical
framework for LIS/information science
Some critiques focus on the attempt to develop infor-
mation science (or LIS or information studies) as a field
of study with some kind of identity. Limberg (2017), for
example, said:
Domain analysis (Hjørland and Albrechtsen 1995;
Hjørland 2002[a]) was developed by Birger Hjørland
from the mid 90’s as a competing theoretical ap-
proach [to the cognitive viewpoint], not acknowledg-
ing cognitive psychology as a relevant framework,
and instead suggesting social aspects of information
science as foundational. However, domain analysis
was based in a similar ambition to create a common
theoretical framework for the discipline of infor-
mation science.
It is difficult to understand this criticism. Limberg’s
speech (2017) quoted a definition that reflects her own
view of the field (FRN [Forskningsrådsnämnden] 1989,
85, Limberg’s translation):
The discipline [LIS] takes its point of departure in
problems related to the mediation of information
or culture, stored in some form of document. The
objects of study are processes such as information
provision or the mediation of culture, as well as li-
braries and other institutions with similar functions,
involved in this process. The discipline has connec-
tions to a range of other disciplines within the so-
cial sciences, the humanities and technologies.
I share the view expressed by Limberg that the FRN def-
inition constitutes a broad and fruitful conception of in-
formation studies. It is, however, one conception out of
many, and, as such, it includes something (it includes
many things because it is broad) and excludes something
else. In my opinion, Limberg, by supporting this defini-
tion, is also trying “to create a common theoretical
framework for the discipline of information science.”
This seems therefore to be a misplaced criticism of do-
main analysis. It should also be emphasized that it is nec-
essary for any discipline to exclude something. The field
of information studies suffers greatly from a tendency to
accept any paper or thesis as a part of the field as long as
it is written in one of our educational programs. Son-
nenwald (2016) is a book about theory development in
the information sciences. It contains a chapter by Hilary
S. Crew entitled “Illuminating daughter-mother narratives
in young adult fiction.” As written in a book review
(Hjørland 2017a) daughter-mother narratives in young-
adult fiction cannot be considered a part of information
science—no matter how we define our field. Crew’s
chapter is about literature studies, not about information
science. Our field is in a crisis if we accept contributions
from any other field as a valid contribution to our field.

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If information science is about everything, then we are
not experts in anything but amateurs in everything.43
Therefore, we must have the goal of creating a common
theoretical framework for the discipline of information
science (or LIS or KO).
5.5 Conclusion
This section examined some44 of the arguments that have
been put forward against the domain-analytic point of
view. Most visible have been arguments that may be in-
terpreted as critical of the more historicist, hermeneutic,
pragmatic, and critical aspects of domain analysis. There
has also been a broader criticism that seems to question
the very goal of an identity for LIS/KO. There probably
exist other forms of criticism that have not been ex-
pressed in the literature. To argue against the silent criti-
cism is difficult because the criticism has not been ex-
pressed and therefore cannot be examined. There may be
beliefs that more straightforward or easier approaches ex-
ist. Many scholars subscribe to alternative views, such as
the cognitive view. Such views need to be examined and
evaluated, if not, KO cannot progress. We need to exam-
ine what Slife and Williams (1995) called “the hidden
theoretical assumptions” of the field, and to take theory
seriously in KO.
6.0 Further methodological examples and
considerations45
6.1 Domain-analytic studies made outside KO
Beak et al. (2013) and Smiraglia (2015) have provided val-
uable studies of domain analysis within knowledge or-
ganization. Here it must be stated, however, that domain
analysis needs to consider in addition studies made out-
side information science and KO. It cannot be overem-
phasized that information science, LIS, and KO are part
of the metasciences and need closer cooperation with
them–as well as with the specific knowledge domains
they investigate.
The degree to which domains study themselves vary.
Budtz Pedersen, Stjernfelt and Emmeche (2016, xiii)
wrote:
We are aware that the humanities very rarely make
themselves an object of study. In contrast to the
social sciences, where there is a longstanding tradi-
tion for not only examining the field’s own research
practices but also for studying research cultures in
the natural sciences, there has never been a “hu-
manities studies.”46 The humanities are over-
debated, but under-investigated.
The book by Budtz Pedersen, Stjernfelt and Emmeche
(2016) can be considered a domain analysis of the humani-
ties, and part of a greater research program “humanom-
ics.” The quote above indicates that various disciplines’
study of themselves as well as the study of disciplines
made by other fields should be considered. Although the
focus of KO is the making of classification systems, the-
sauri, ontologies, and other kinds of knowledge organiza-
tion systems (KOS), this field should not consider itself
too narrowly, and the methodology should not be under-
stood too narrowly, mechanically, or positivistically.
Lee’s book (2009) challenges mainstream economics in
the twentieth century (the neoclassical paradigm), includ-
ing the influence of the British Research Assessment Exercise
and the ranking of journals and departments in econom-
ics. It is relevant to information scientists doing biblio-
metric research and to domain-analysts in KO, whether
they use bibliometrics or other methods. The field of
economics seems to be a domain that to a large degree
has studied itself, and those in KO who want to study
this domain should consider such studies.
A third example of a valuable contribution from out-
side KO is Andersen (2000). He found that social scienc-
es differ with respect to the degree of consensus on what
constitutes their core journals. Within the single social
sciences, the picture is a pluralistic view rather than a
monolithic hierarchy. This finding confirms that different
perspectives on a given domain need to be considered,
and that journal rankings such as the one made by Journal
Citation Reports® should not be used uncritically.
6.2 The status of “ordinary people” in domain
analysis
One of the issues sometimes raised in domain analysis is
the status of “ordinary people” (i.e., people not associat-
ed with formal disciplines). Here this problem is illumi-
nated by considering the example of homosexuality in re-
lation to psychiatric diagnoses. According to Drescher
(2015), the American Psychiatric Association decided in
1973 to remove homosexuality as a mental disease from
the official American diagnostic manual (Diagnostic and
Statistical Manual of Mental Disorders, DSM). Homosexuali-
ty was considered a mental disease in the two first edi-
tions (American Psychiatric Association 1952 [DSM-I]
and 1968 [DSM-II]) until the sixth printing of DSM-II
(in 1974). Here we do not go into detail regarding how
homosexuality was considered in later editions, but the
overall picture is that homosexuality was depathologized
after 1973. Within the discipline of psychiatry (as in other
disciplines, e.g., psychology), different theories of homo-
sexuality competed at that time and still compete today.
These theories are associated with broader “paradigms”

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such as behaviorism, psychoanalysis, cognitivism, and
neuro-biology that more or less prevail in different disci-
plines and in the broader community at different times
(in relation to disciplinary interests and the “Zeitgeist”).
What is interesting in the case of homosexuality is that it
was political pressure from the homosexual community
that influenced the scientific and scholarly psychiatric
community. “Ordinary people” in this case consists of
people in the homosexual movement and others, and it
therefore does not constitute a homogenous group.
“Others” may be more or less influenced by different
views—some by official psychiatry, some by religious
ideologies, some by the homosexual and antipsychiatric
movements, etc. For domain analysis, the conclusion is
that it is important to consider the relative dominance of
different paradigms in different domains at different
times, including their relation to the broader society.
Whether or not homosexuality should be classified as a
mental disorder can be done only by considering the the-
oretical and political arguments, not by studying the opin-
ion of people in general.47
6.3. Epistemological dimensions of bibliometric
domain-analysis
Raghavan et al. (2015) contributed to the second thematic
issue of the journal Knowledge Organization that was devot-
ed to domain analysis48 (the first appeared in 200349).
Their paper is a fine descriptive, bibliometric study of the
domain “information retrieval” (IR) as treated in two da-
tabases (Institute of Electrical and Electronics Engineers
database, IEEE and EBSCO’s Library, Information Sci-
ence & Technology Abstracts, LISTA) during the period
2001-2014. The authors assumed that the IEEE database
in particular reflects the computer-science community,
whereas LISTA in particular reflects the LIS community.
Of course, these kinds of assumptions are legitimate;
they appear frequently in almost all research. Here we try
to suggest how that study could be followed up by new
domain analytic studies. What we try to do here, is to
suggest how this study could be followed up by new do-
main studies, and in particular relate the suggestions to
the narrow view on the methodology of domain analysis
(see Section 4.6).
First, Raghavan et al. (2015) were interested in the
relative differences in contributions to IR from different
communities. The hypothesis that IR has largely migrated
from information science to computer science has re-
cently been stated (see, for example, Bawden 2015 and
Hjørland 2017a). In order to examine this hypothesis bib-
liometrically, it is necessary to identify the set of infor-
mation sources associated with each community. Just a
few problems are mentioned here:
1. Even at the journal level, the disciplinary link is often
unclear. Journal of the Association for Information Science
and Technology used to be the journal mainly about (li-
brary and) information science, but LIS is now a mi-
nority field in its own flagship journal (cf., Chua and
Yang 200850).
2. Some of the journals that are considered to represent
LIS in LISTA in fact belong to other communities (In-
formation Systems, for example, is a third community,
and ACM Transactions classified as LIS is clearly a
journal associated with computer science).
3. The coverage of the different databases needs to be
known in much more detail if the hypothesis concern-
ing IR is to be tested.
4. Raghavan et al. (2015) relied on the terms that were
assigned to each document (INSPEC Control Terms
in the case of IEEE and Subject Terms in the case of
LISTA). This, however, makes the investigation de-
pendent on the indexing in the respective databases.
Such indexing inserts a level of interpretation between
the document and the searcher. It is important sepa-
rately to study: 1) the development of specialist lan-
guage in different communities; and, 2) the develop-
ment of indexing languages and their representation
of documents (including the quality of indexing).
Studies of language and terminology in domains is
one of Hjørland’s eleven points, but it is currently
poorly represented in domain studies.51
These four points are not meant as a criticism of the pa-
per by Raghavan et al. (2015). They have made an im-
portant start and identified, for example, that “clearly the
Web has been the major influencing factor in determining
the direction of research in IR” (598). The purpose of
the present article is, however, to outline methodological
issues in domain analysis and to consider how such issues
may improve our studies. We have not yet considered the
epistemological point, which was claimed to be the most
important. The choice of journals and conferences and
other sources covered is, however, of major importance,
and so is the choice of assigned terms, title words, words
from abstracts or full text, and the way they are studied.
Any deeper level of bibliometrics/domain analysis has to
consider such issues.
IR seems today dominated by statistical approaches,
and we might ask whether Robertson (2008) is correct in
his claim: “statistical approaches won, simply. They were
overwhelmingly more successful [than other approaches
such as controlled vocabularies, including thesauri].” If
the community of KO still believes it has a role to play in
relation to IR, how has it responded to this challenge?
Has it joined the statistical approaches or has it devel-
oped alternative approaches to information retrieval?

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What theoretical assumptions are dominant in the LIS
and KO communities in relation to information retrieval?
Many publications in the fields of LIS and KO seem
not to consider this challenge and instead stick to tradi-
tional issues. There may be two views here: 1)that such
publications are also important contributions to the future;
or, 2)that they are not. Any responsible person should, of
course, determine the course of his/her research and
teaching, based on an informed consideration of such is-
sues. Therefore, the identification, examination, and evalu-
ation of the basic theoretical assumptions in the fields re-
lated to information retrieval are the most important things
to do from the perspective of domain analysis. Examples
of such approaches were presented in Hjørland (2016b).
Other assumptions should also be examined, including the
idea that KO should give up its ambition of making con-
trolled vocabularies for full-text retrieval (and major disci-
plinary databases?) and restrict itself to applications where
no other IR technology is effective, such as small- and me-
dium-scale in-house collections or non-text collections (cf.,
Dextre Clarke 2016, 141).
It is much more important to learn about the (theoret-
ical) development of a domain than to simply map which
topics have been most studied. A study of the theoretical
development of a domain needs to identify different
“paradigms” or major theoretical views, such as those
listed above. The first step to clearly identify the para-
digms and examine them. The next step is to support in-
formation retrieval in order for the important approaches
to develop. In a way, the disciplinary affiliation seems to
be less important than the theoretical assumptions. It is
highly important to uncover and examine theories and as-
sumptions, whether they are implicit or explicit. Biblio-
metric techniques, such as those used by Raghavan et al.
(2015), are important, and should form part of the com-
petencies of information and KO researchers. The point
made here is that other kinds of knowledge of the do-
main examined may improve future studies and, in par-
ticular, that domain-knowledge is needed and the domain
analyst needs to consider herself part of the effort to de-
velop the domain. More about bibliometrics and the phi-
losophy of science in Hjørland (2016a).
Smiraglia (2015, 97-98) found that domain analysis
“helped to enrich the contextual understanding of the
functions, activities, shared semantics, and evolving con-
straints of knowledge-based domains. There has been lit-
tle applied research, however, reporting the development
or evolution of pathfinders or subject gateways, even in
the face of expanding digital hegemony over all human
activity.” Smiraglia also observed (98): “we have studied
our own domain in detail, but we have studied few other
domains adequately for either knowledge discovery or
development of knowledge organization systems.”
It is important that KO contribute to other domains.
Dubitzky et al. (2013) edited an encyclopedia of systems
biology to which many concepts from knowledge organi-
zation and related fields have been integrated. It contains,
for example, entries on classification, controlled vocabu-
lary, data mining, interdisciplinarity, international classifi-
cation of diseases, interoperability, ontology, paradigm,
and XML. To have knowledge organization and infor-
mation science integrated in disciplinary encyclopedias
should be an important goal, but so far this is done much
too seldom.
6.4 Conclusion
This section considered some methodological issues in
addition to the model provided by Section 3 and by the
discussion of criticism in Section 5.52 The methodologi-
cal implications of the arguments are that domain analy-
sis should not just search for a narrow methodology to
organize a set of items, but must be based on broader
knowledge of the domain under investigation.
7.0 Conclusion
Imagine a librarian answering a question about a given
topic, such as birds. Or imagine a specialist in a domain
such as the arts, chemistry, or medicine working as a sub-
ject specialist in a library. In both cases, two kinds of
qualification are needed: 1. subject expertise (e.g., about
specific terminology and important theories); and, 2. LIS
expertise (e.g., about information retrieval, bibliometrics
and knowledge organization). Domain analysis suggests
that the specific competencies that information specialists
have or should have is information about information in-
frastructures and information retrieval (and the others of
the “eleven plus three” points listed in Section 1).
Domain analysis further suggests that subject qualifi-
cations and LIS qualifications are not independent of
each other. Just as one cannot study Chinese medicine by
studying Chinese and medicine as separate subjects, in-
formation science needs to study infrastructures in all the
domains that should be served by information profes-
sionals. Further, to be considered a research-based field
of study, information science and KO must provide ex-
planations of information use as well as criteria of rele-
vance and optimal informational infrastructures. The
domain-analytic view finds that criteria of relevance are
implicated by the theories in a given domain, and expla-
nations of information behavior relate to the information
seekers epistemological beliefs. From the domain-analytic
point of view, information specialists should know about,
for example, the relevant databases, search strategies, sub-
ject terminology, knowledge organizing systems (e.g., the-

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453
sauri), bibliometric methods, and criteria for what counts
as valid knowledge (epistemology). Clearly, it is a huge
advantage if the information specialist has background
knowledge in the domain, but that is not what defines the
information professional. Many things related to scholar-
ly communication, genres, and documentation processes,
and retrieval processes need to be mastered if someone is
to consider himself or herself an information profes-
sional—and this always needs to be combined with rele-
vant subject knowledge.
Notes
1. Hjørland and Albrechtsen (1995, 400) wrote: “You
may ask: Is domain-analysis really new? Or is it old
wine in new bottles? Is the phrase “domain-analysis”
new, is it given a new meaning, and what fundamental
claims in the theory behind this view are new? We will
try to show that many past and contemporary ap-
proaches to IS implicitly share many of the basic as-
sumptions in this view, but that an explicit formulation
of this view and its theoretical assumptions and con-
sequences has hitherto been absent from the contem-
porary scene.”
2. An anonymous reviewer wrote: “There is too much
emphasis on LIS. First, KO is not LIS. It is not offi-
cially a part of LIS. Some acknowledge its relationship
to LIS, and it often is taught in schools of LIS, but
many consider it to be its own domain (especially its
founder). Also, an encyclopedia of KO should not
have articles about LIS, but rather about KO. And, the
author should try to understand that ‘library science’
was a naïve term from the early 20th century; that that
discipline, brought together at Chicago with Carnegie
money to use empirical methods for the problems of
managing information institutions, merged about 1961
with documentation into what has been known as ‘in-
formation science’ but now is more often called, simp-
ly, ‘information.’ See work by W. Boyd Rayward, and
especially the work by Machlup and Mansfield, itself
now quite old. This change was made 60 years ago!”
Answer: Hjørland (2002a and elsewhere) considered
domain analysis as part of information science and
LIS, and KO as a subfield of information science/LIS.
Other prominent researchers consider KO an inde-
pendent field (Dahlberg 2006, Smiraglia 2015, 1). How
can it be decided which claim is correct? In an infor-
mal communication dated August 29, 2016, Ingetraut
Dahlberg wrote: “With regard to my professional ac-
tivities which Richard [Smiraglia 2014, 40] called ‘in-
dexer’, etc., I was trained to become a documentalist,
but I developed into an Information scientist and this
is what I usually say when people ask me and this you
can also find in my description in Wikipedia.” This
quote by the founder of ISKO documents that KO
must be considered part of information science. Alt-
hough Smiraglia (2015) considers KO an independent
science, many of the contributors presented in the
same book can best be described with the label “li-
brary scientists,” or “library and information scien-
tists” (e.g., Jesse Shera, Margaret Egan, Patrick G. Wil-
son and Elaine Svenonius), which also demonstrates
that KO must be considered part of LIS. “Library sci-
ence” was certainly not a term that was used only in
the early 20th century. Saracevic (1992), for example,
discussed its relation to information science, naming it
both “librarianship” and “library science.” He wrote
(14): “While information science and librarianship are
great allies, to the point that the term ‘library and in-
formation science’ is assumed by many to describe
one and the same field, the reality is that differences
described are of such qualitative magnitude that they
make this assumption not only unwarranted, but also
moot.”
Concerning the referee’s claim that KO “is not offi-
cially a part of LIS,” there is no official agency or cri-
terion that has the authority to determine the relation
between sciences. People in the field of KO who are
concerned with classifying knowledge and disciplines
should know that better than anyone else.
Three other arguments are: 1) the literature of KO
(e.g., as published in the journal Knowledge Organization)
is bibliometrically more closely coupled with infor-
mation science than with science studies, for example;
2) in developing theory for KO, we need to consider it
from the perspectives of the Internet, search engines,
and research in information-seeking and retrieval. It
seems dangerous to isolate the field from the broader
field of information science; and, 3) The institutional
frame of KO is overwhelmingly institutions of infor-
mation science, and it seems dangerous to contribute
further to the fragmentation of that field.
Concerning the complicated relations among fields as-
sociated with information science, see Hjørland
(2013b), in which it is documented that LIS emerged
in 1964 as the integration of information science and
library science. As for domain analysis, it serves as a
theoretical frame for IS, KO, and LIS and a general
outline, like the one in the present article, will be iden-
tical in these three contexts (if it makes sense to con-
sider them as different contexts).
A sad conclusion is that KO and LIS, which deal with
organizing knowledge, are themselves ill-defined and
disordered.
3. Egan and Shera (1952) were the first people to use the
term “social epistemology.” It can be argued, however,

Knowl. Org. 44(2017)No.6
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454
that social dimensions of epistemology first became
influential in the groundswell of Kuhn (1962). Thus,
Egan and Shera (1952) (or Shera’s later works) do not
have a clearly expressed epistemological position. This
is to be found in later works, mainly from outside LIS.
4. The eleven approaches should not necessarily be
combined in the same study (as this would probably
be awkward), but different studies of the same domain
based on these approaches may supplement each other
and provide the basis for a deeper understanding of
the domain.
5. However, as noted in Hjørland (2017a) in 1975 Sara-
cevic declared “the subject knowledge view” the most
fundamental perspective of relevance, but this view
was since forgotten or repressed without argument by
Saracevic.
6. It is difficult to say what the trends in employment of
different kinds of professionals are in research librar-
ies, in public libraries, in university departments for
LIS etc. One example is provided by Larsen’s study
(2009, 17) of the State Library in Aarhus, Denmark,
showing decline in the employment of both subject
specialists, general librarians, and support personnel
but an increase in computer specialists.
7. “Most MEDLINE indexers are either Federal employ-
ees or employees of firms that have contracts with
NLM [the United States’ National Library of Medicine] for
biomedical indexing. A prospective indexer must have
no less than a bachelor's degree in a biomedical science.
A reading knowledge of certain modern foreign lan-
guages is typically sought. An increasing number of re-
cent recruits hold advanced degrees in biomedical sci-
ences” (https://www.nlm.nih.gov/bsd/indexfaq.html#
qualifications).
8. “But nowadays, in the context of a very complex world,
upper ontology had to be divided into a lot of practical
formal ontologies. Such a project has been carried out
in a very competent way by Barry Smith in more than
450 papers, and a lot of collaborative experiments have
established not only a set of principles for ontology de-
velopment but real open ontologies in biological and
biomedical domains (genes, proteins, infectious diseases,
embryology, anatomical information ... ), in geospatial
sciences (geographical categories, spatial objects, tools
for geographic representation ... ) and also in social and
cognitive sciences (information artifact, theory of the
act, documents, naive physics, cognitive geometry of
war, etc.)” (Parrochia and Neuville 2013, xiii). Further:
“So, for Barry Smith, an alternative to ‘fantology,’ might
be set out for a better applying of mathematical con-
cepts to the real complexity of the world, at different
levels and in different domains: that is what the author
tried to do. In more that 450 publications, 15 books and
the management of impressive projects, the author has
begun to build formal regional ontologies. He has done
all that with the help of eminent scientists in several
domains like medicine, biology, genetics, geography or
ecology, and our intention is not to criticize a so massive
work” (Parrochia and Neuville 2013, 49).
9. For a discussion of the education of medical librari-
ans, see Smith (2005).
10. Mai (2010, 629) wrote: “Research on specialized librar-
ies and information services has challenged the assump-
tions and begun working out frameworks that are do-
main specific and pluralistic; the work of the British
Classification Research Group in the 1960s and 1970s
(cf., e.g., Foskett, 1974; Vickery, 1975; Langridge, 1976)
and Hjørland et al. recently (cf., e.g., Hjørland and Al-
brechtsen, 1995; Hjørland, 2002[a]) are good examples
of this line of work.” To the prehistory of domain
analysis may be added Mote (1962) and Shera (1965).
11. The American Psychological Association (APA) car-
ried out a large research project studying scientific
communication in psychology for the purpose of op-
timizing both specific products such as the Psychological
Abstracts, and its system overall, including the journal
program. Among the many publications from this pro-
ject (the so-called “APA studies”) is Garvey and Grif-
fith (1964).
12. By its focus on specific contents, information science
may be different from media studies, for example. De-
pending on the research question raised in the study, a
study of Google may be considered part of LIS, or it
may be considered part of media studies or other fields.
A typical information science question is the compari-
son of Google’s retrieval of medical knowledge with
that of other kinds of systems (e.g., Dragusin et al.
2013a and 2013b). A study of Google’s importance for
printed newspapers (as a competitor for advertisements)
is, on the other hand, a media study.
13. Many terms are near-synonyms of “domain.” Tennis
(2003, 194-195, note 2) provided the following “terms
related to a domain”: ba, communities of practice, con-
text, cynefin, discipline, discourse community, field, po-
sition, situated knowledge, subject matter, and work en-
vironment.
To Tennis’ list may be added: academic tradition, con-
ceptualization, (a) literature, (sub)culture, hobby, (a) sci-
ence, sect, specialty, subject area, topic, and trade. These
and many more terms (such as theory and paradigm)
may be examined with respect to their varying implica-
tions for the study of domains.
14. According to Arango and Prieto-Díaz (1991, 12), in the
context of software reuse, the expression “domain
analysis” was introduced by Neighbors (1981[sic]).
Neighbors (1980, 1) wrote, “The concept of domain

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
455
analysis is introduced to describe the activity of identify-
ing the objects and operations of a class of similar sys-
tems in a particular problem domain. A domain analysis
is represented by a domain-specific language, a pretty-
printer, source-to-source transformations, and software
components.”
15. Prieto-Díaz wrote (1990, 50): “Library Science—
Another application of domain analysis occurs in Li-
brary Science when deriving specialized classification
schemes [Vickery1960]. Specialized faceted classification
schemes are derived through a manual process that con-
sists of grouping related terms from a sample of select-
ed titles, defining facet names from such groups, order-
ing the terms in each facet, and specifying rules for syn-
thesizing compounded classes. The resulting classifica-
tion scheme becomes a conceptual model for the do-
main of the collection. Grouping of terms from titles is
equivalent to finding objects and operations in an appli-
cation domain. The naming of facets and defining clas-
sification rules is equivalent to deriving a domain model
or creating a domain language.”
16. The methodology of facet analysis was discussed by
Hjørland (2013a), who characterized it a “logical ap-
proach.”
17. Is there a contradiction in this quote? Is it possible
both to consider a domain “open” and, on the other
hand, demand that it must be “more concrete” and
“operationalized?” Of these two demands, the quality
of openness should be considered the most im-
portant.
18. Khalidi (2013, ix) also uses the term “domains” in re-
lation to classification. “This picture of the world,
which is the one conveyed to us by modern science,
suggests realms of existence arranged in levels, from
smallest to largest. But these are not self-contained,
compartmentalized levels like the floors in an apart-
ment building, since there are intricate relations and
interactions between the levels, or domains, as I shall
call them later in this book. Additionally, the domains
are not discretely arranged in a hierarchy. Much of the
universe is a jumble of domains, some coexisting at
the same spatiotemporal scale and within the same re-
gions of space-time and others overlapping partially,
or, to use a term that I have used elsewhere, ‘crosscut-
ting’ each other. Modern science has evolved an array
of disciplines, subdisciplines, and interdisciplinary re-
search programs to study this complex multiplicity,
each with its toolkit of categories, generalizations, and
methods. This book is about the assortment of cate-
gories that scientists have devised to study the multi-
faceted nature of reality, and specifically which of
these categories are valid or, to use the philosophical
jargon, correspond to ‘natural kinds.’”
19. Nascimento and Marteleto (2008) relates Hjørland’s
concept “domain” to Bourdieu’s concept “field.”
20. The concept “epistemic community” has been dis-
cussed in relation to domain analysis by Guimarães et al.
(2015), Mustafa El Hadi (2015), as well as in Martínez-
Ávila et al. (2017). The last publication understood epis-
temic communities as networks of knowledge-based
experts that hold in common a set of principled and
causal beliefs, have shared notions of validity, exchange
knowledge, and shape, demarcate, and articulate the
identities of present and future knowledge producers.
21. Keilty and Smiraglia (2016) is a study of male homo-
sexual communication on an Internet contact site,
which provides an argument for considering this a
domain. It is clearly an example of a domain that is an
alternative to an academic discipline.
22. Andersen (2000, 689) provided an interesting domain
analysis of Danish social science. He wrote: “Never-
theless, on the whole these results show that although
a set of common journals can function as a medium
of communication, thus making visible the reputation
of research results and researchers, this function is
weak, at least in the Danish social sciences.”
In general, it can be said that if a domain has no, or
extremely little, consensus concerning the most im-
portant information sources, it is impossible to pro-
vide efficient library and information services for that
domain.
23. An anonymous reviewer wrote: “Ørom’s study in 2004
was interesting, but it also was published prior to the
decade and a half of progress in domain analysis in
KO. An encyclopedia article in 2017 should not be
dependent on it, but rather should show how domain
analysis for KO has evolved over time.” Answer: Hjør-
land (2017b, 114) concluded: “the study of classifica-
tion involves the study of theories in different do-
mains and the ontological claims of those theories.
The justification of a good classification in this per-
spective is to make a justification of the theoretical
premises on which it is based.” In spite of the many
studies mentioned by the reviewer, there have still
been very few such studies, and therefore Ørom
(2003) is still considered a model of domain analysis.
24. In an email dated June 19, 2016 Hanne Albrechtsen
wrote (abbreviated and translated): “11 approaches in
my opinion opened the door for methods that do not
match the critical-hermeneutical approach which you
and I recommended in the article from 1995, but in-
clude Smiraglia’s and Lykke’s quantitatively oriented
approaches, which may be said to consider domains in
a traditional sense. In my opinion a paper is not do-
main-analytic just because it contains the term ‘do-
main’ in the title.” In a 2015 article, Albrechtsen wrote

Knowl. Org. 44(2017)No.6
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456
(559): “Yet the proposition at this point is: We did not
do domain analysis. While the projects were domain-
specific: software development for diverse work do-
mains ranging from libraries to the space industry and
medical informatics and robotics, we also developed
knowledge organization systems (KOSs) for specific
domains like software. Still, it needs to be highlighted
that the development of knowledge organization sys-
tems for specific domains is not, in and of itself, a
domain analysis.”
25. The intellectual foundations of the CWA framework
were further developed by Vicente (1999), and a recent
text on that subject is Naikar (2013). Raya Fidel, the
former Head of the Center for Human-Information
Interaction, the Information School, University of
Washington, and co-director Jens-Erik Mai also used
CWA as theoretical framework (cf. Fidel 2012).
26. The term “film classification” is normally understood
the classification of films for different age groups.
Perhaps “film genre” is among the better alternative
terms for classifying films in libraries, archives, and da-
tabases/filmographies.
27. Mark Pejtersen also developed “the Book House” da-
tabase for fiction retrieval, based on a large-scale re-
search program. See further in Eriksson (2010) (sum-
marized in English in Hjørland 2013c).
28. According to Google Scholar on February 19, 2017,
this article (Tennis 2003) has been cited eighty-five
times. It is thus rather influential, and is Tennis’ most
cited paper.
29. Guimarães et al. (2015) consider “that axis one, the ex-
tension of the domain, can be characterized as the
analysis of the researchers that contribute to the de-
velopment of the domain ‘knowledge organization,’ by
means of citations and co-citations; while axis two,
specialization and depth, can be used to identify, by ci-
tation and co-citation analysis, the domain of the re-
searchers that constitute the scientific community in
order to characterize the core of researchers that the
community recognizes as fundamental, or more im-
pactful, in knowledge organization and its main areas
of research. We aim to build a co-citation network to
analyse the degrees of the density and centrality of the
researchers in the network.”
30. Tennis’ two dimensions are understood by Smiraglia
(2015, 4) as “extension and intension. The terms mean
breadth and depth, respectively.”
31. Tennis wrote (2012, 10; emphasis original): “If we
pick a constrained domain, like Shakerism, we can see
perhaps what the definitions, scope and reach, and
purpose might be of one of its domain analyses.
Definition of Shakerism: The church is official called
United Society of Believers in Christ’s Second Appear-
ing. It is a religious movement founded by the Ward-
leys of England, by recognizing Ann Lee as the sec-
ond coming of Christ in 1747. From that time ‘til
1990s with the publication of Stephen Stein’s The
Shaker Experience in America (Yale University Press) in
1992.
Scope and Reach: For the purposes of this domain anal-
ysis I will use Stein’s 1992 work and sources cited in
that work. These comprise some 300 resources, both
primary and secondary resources. Extension: All con-
cepts I can identify in these texts, and their relation-
ships. Exclusion: I am not considering anything after
1992 and not considering other sources for this do-
main analysis. Name: Shakerism according to Stein. Fo-
cus and Specialization: Specifically looking at theological
and architectural terms, not focused on the music or
art.
Purpose: The purpose of this domain analysis is de-
scriptive. I hope it will serve as a starting point to cre-
ate an ontology of early American theological termi-
nology in relation to the built environment, but that is
not the primary concern. The primary concern is to
take stock of Stein’s perspective of Shakerism given
the constraints above.
It is perhaps by following these outlines that we can
see more clearly the core, the scope the reach, and the
purpose of a domain analysis, form one perspective
and at one particular point in time.”
32. A mapping of a domain may take as its point of de-
parture the literature of and on that domain, or it may
use other information sources (e.g., people). Neverthe-
less, the problem of selecting the sources is the same,
and in all cases needs justification.
33. For example, according to Wallerstein et al. (1996), the
existing disciplines of the social sciences appeared be-
tween 1850 and 1914, when the structure received
formal recognition in universities. The five main lo-
cales for social science activity during the nineteenth
century were Great Britain, France, the Germanies, It-
aly, and the United States.
34. “The truth is always in the minority; and the minority
is always stronger than the majority, because the mi-
nority is ordinarily composed of those who do actually
have an opinion, whereas the strength of the majority
is illusory, composed of the crowd which has no opin-
ion—and which therefore the next minute (when it
becomes apparent that the minority was the stronger)
embraces the opinion of the minority, which now be-
comes the majority, that is, the opinion becomes rub-
bish by statistics and the whole crowd on its side,
while truth is again in a new minority. As far as truth is
concerned, the same thing happens to this awkward
monster, the majority, the public etc. as we say hap-

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
457
pens to the person traveling for his health: he always
arrives one station too late” (Kierkegaard [1850] 2015,
120-1). To Kierkegaard’s quotation should be added,
however, that even if the truth is always in a minority,
that does mean that is in any minority view, whatsoev-
er.
35. This is opposed to the philosophies of rationalism and
empiricism. I therefore disagree with Mai’s (2008, 18)
statement: “Each of these approaches [empiricist, ra-
tionalist, historicist and pragmatic] could lead to dif-
ferent classifications of the domain. It would be diffi-
cult to argue that any of these approaches is more cor-
rect or better that the others—they are just different,
based on different assumptions, leading to different
classifications.” Epistemological positions are not
simply something free to choose, however. To argue
for a critical-hermeneutical view, for example, is to ar-
gue against opposite views.
36. “Hjørland and Szostak have disagreed on multiple oc-
casions regarding the possibility of a comprehensive
phenomenon-based classification (Hjørland 2008,
2009; Szostak 2008, 2011, 2013; Fox 2012)” (Szostak
et al. 2016, 189).
37. Mills (2004, 548) wrote: “Remember that all special
classifications need to draw on a more general one, of-
ten extensively.” This claim is not justified, however,
and the opposite is true: Any general classification
needs to draw extensively on special classifications in
all areas of knowledge.
Dahlberg (2017, 66-67) seems to share Mills’ view: “It
is quite obvious that the emergence and upgrading of
thesauri is occurring, whereby it is clear that an as-
sessment of all concepts would reveal that a lot of
them duplicate in the various systems, whereas a uni-
versal knowledge ordering system reserves for each
concept its proper and unique place, so that users can
tailor the system to their needs.” Dahlberg writes fur-
ther (70): “The endeavours outlined towards a uni-
form, yet universal, ordered representation of human
knowledge match the work of standardisation centers
whose concerns are vital for our economy; just as vital
would be the virtual, proposed innovative yet improv-
able ICC [Information Coding Classification] based on
knowledge areas, whose operation would certainly en-
tail considerable economies when it is estimated that
the elaboration of a single ontology page for a manual
of chemistry costs 10,000€. To improve ICC would
require an academy or a ‘Leibniz-Institut’ for
knowledge organization staffed by experts in classifi-
cation, thesaurus construction, terminology, ontolo-
gies and ad hoc disciplines.”
38. Different cultures tend to classify living organisms dif-
ferently. This is studied by the field known as ethnobi-
ology (see, e.g., Berlin 1992). Normally, biological tax-
onomy rather than ethnobiology is used in biblio-
graphical classification systems. Even if a classification
is designed to be adjusted to a specific culture, howev-
er, domain-specific (ethnobiological) knowledge is
needed.
39. Domain-specific classification cannot be deduced
from a set of a priori principles. It is the other way
around; classification research needs to be “natural-
istic,” to be based on the study of classification in dif-
ferent domains.
40. Fulani (2000, 151) discussed epistemology from the
perspective of being black: “As an African-American
child growing up in Chester, Pennsylvania, I (not sur-
prisingly) never heard the word epistemology, rarely
heard the word identity, and frequently heard the word
race. My race faced mistreatment, poverty and poor
education, and I decided that I was going to become a
psychologist so that I could help people, and so that
together we could change the world. As an undergrad-
uate I was immediately disappointed by what psychol-
ogy had to offer and disturbed (outraged, really) by the
official assessment of the African-American commu-
nity as a tangle of pathology. I soon became a militant
Black Nationalist and immersed myself in Black psy-
chology. I still never heard anyone speak about epis-
temology, although just about everyone was talking
about race, and we nationalists spoke about identity all
the time. I rapidly developed one. It was becoming a
political activist, a Marxist, a social therapist and a
builder of a multi-racial development community that
taught me about epistemology and its links to race and
identity.” Although the quote continues “Having
learned what it [epistemology] is, I strongly urge that
we get rid of it!”
It can be claimed, however, that Fulani’s position is an
epistemological position derived from his experiences
as a black person (see Bakhurst 1993, on Marxist epis-
temology).
41. Consider, for example, the classification of mental
diseases (Hjørland 2016c). It is not possible to even
imagine a classification that is not connected with an
epistemological point of view (atheoretical classifica-
tion is a paradox). Any ontology reveals the episte-
mology of its author. To claim that classifications can
or should be made without considering epistemology
is naïve. Therefore, the defenders of “ontological” or
atheoretical classification should suggest a classifica-
tion of, for example, mental diseases. Hjørland’s view
is supported by Wesolek (2012), who provides Witt-
gensteinian support for domain analysis.
42.
One distinction is between universal or general classi-
fications on the one hand, and special classifications

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
458
on the other. Another distinction is between standard-
ized classifications and non-standardized classifica-
tions. Universal systems need some degree of stand-
ardization, and are therefore less qualified to fulfill the
requirements of a specific domain. The subdiscipline
social psychology, has to be classed in a universal sys-
tem either under psychology (which renders sociolo-
gists badly served) or under sociology (which makes
psychologists unhappy). In special classifications (as in
the thesauri of PsycINFO and Sociological Abstracts),
however, both disciplines may have social psychology
and be well served. To standardize in order to improve
interoperability is to say X should always be classed
under Y, which may be unacceptable to those prefer-
ring to have X classified under Z. Standardization
therefore requires negotiation of different interests—
and, again, domain knowledge.
43. It is, however, easy to understand how this situation
(that literature and other disciplines are confused with
information science) has arisen; the mediation of fic-
tion is an important part of the function of public li-
braries, and LIS is supposed to educate students for
this task; therefore, fiction becomes part of the cur-
riculum. (Around the year 1990, the Royal School of
LIS in Copenhagen had separate departments for,
among others, fiction, humanities, social sciences, sci-
ence and technology; all these fields were part of the
curriculum). The domain-analytic point is, however,
that fiction (or humanities, science … ) as a part of in-
formation science has a different perspective as com-
pared to how these subjects are researched and taught
in their respective departments at the university. This
special focus is defined by the eleven approaches listed
at the beginning of this article. These eleven ap-
proaches cannot be explored in depth with adequate
subject knowledge—ideally information studies should
be combined with subject studies, and information
specialists should have double qualifications. This is
probably the only way LIS can be broad enough and
still keep the claim of being a field of its own. I have
never seen a proposal by Limberg on how to solve this
problem. In relation to Limberg’s own domain (school
librarianship) and research, Hjørland (1998a) asked
about the competencies of school librarians if infor-
mation-science knowledge does not exist in pure, con-
tent-independent form. We may have developed too
little concrete knowledge to assist information special-
ists with their specific tasks (an exception to this rule
is probably the medical domain, where relevant do-
main-specific research is done in relation to medical
information retrieval).
44. Holmberg (2013) is a critical analysis of domain analy-
sis from the perspective of Bruno Latour’s philosophy.
Holmberg found that domain analysis bears resem-
blance to the “modernist settlement” where the
knowledge of a few experts is considered sufficient
for the study of a domain. This is, according to
Holmberg, problematic.
45. One of the anonymous referees asked for a section on
the methodology of domain analysis. This was done
to some extent in Section 3, but Section 6 attempts to
illuminate this issue further.
46. There are of course many introductory courses in the
humanities (see, for example, Pittsburgh University of-
fers a bachelor degree on Humanities (http://www.
cgs.pitt.edu/academics/majors/humanities-ba) and Ox-
ford University offers a graduate course on Humanities
(https://www.ox.ac.uk/admissions/graduate/courses/h
umanities?wssl=1). Such courses are, however, not typi-
cally based on empirical, historical, philosophical, or sci-
entometric studies of the humanities; in our terminolo-
gy, they are not domain-analytic. In the single humani-
ties disciplines, there are of course often studies of their
history and philosophy. The claim made by Budtz
Pedersen, Stjernfelt and Emmeche (2016) is that their
research program “humanomics” pioneered such a
study. Whether or not this is true is not addressed here.
The claim here is just that these kinds of studies are rel-
evant for domain analysis.
47. Influence also goes the other direction, of course—
from academic disciplines to the broader public. In the
1920s, behaviorism was a strong force in American psy-
chology. It strongly influenced how parents treated their
children. Watson’s book, (1928) The Psychological Care of
the Infant and Child, was a bestseller, and probably every-
one in America has been affected, or knows someone
who has been affected, by Watson’s behaviorist theory,
according to which the child's wishes, needs, and feel-
ings were treated as if they did not exist.
48. The second issue of Knowledge Organization devoted to
domain analysis appeared in 2015 (vol. 42, no. 8) and
contained papers including Albrechtsen (2015) about
the misuse of the term “domain analysis,” Guimarães
and Tognoli (2015) about the principle of provenance
as a domain-analytic approach in archival knowledge
organization; Marteleto and dos Santos Carvalho
(2015) about health as a knowledge domain and as a
social field in the theory of Pierre Bourdieu, and
Raghavan et al. (2015) about visualization of infor-
mation retrieval as a domain.
49. The first thematic issue of Knowledge Organization about
domain analysis appeared in 2003 (vol. 30, no. 3-4) and
contained papers such as Ørom (2003) on the domain
of art studies; Abrahamsen (2003) on musical genres;
Tennis (2003) on two axes of domains; Albrechtsen and
Pejtersen (2003) on cognitive work analysis (CWA); and

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
459
Hjørland and Hartel (2003) on ontological, epistemo-
logical, and sociological dimensions of domains.
50. “Top authors [in JASIST] have grown in diversity
from those being affiliated predominantly with li-
brary/information-related departments to include
those from information systems management, infor-
mation technology, businesss, and the humanities”
(Chua and Yang 2008, 2156).
51. The very term “information retrieval” may need theo-
retical justification. Other terms such as “document
retrieval” or “literature searching” might be preferred;
the last mentioned term is often used in the medical
domain and seems to be more appropriate. A domain
analysis of IR should therefore include a conceptual
analysis of IR and other terms.
52. Many other domain-analytic studies might be consid-
ered. For example, Talja and Maula (2003) identified and
defined factors that account for disciplinary differences
in e-journal use in the fields of nursing science, litera-
ture/cultural studies, history, and ecological environ-
mental science. Their findings suggest that e-journals
and databases are likely to be used most heavily in fields
in which directed searching is the dominant search
method, and topical relevance the primary relevance
type; they are used less in fields in which browsing and
chaining are the dominant search methods, and para-
digmatic relevance the primary relevance type.
There are also many studies of specific domains, in-
cluding but not limited to:
– Art history: Dam Christensen (2014);
– Earth systems science: Weber et al. (2012);
– Fiction: Beghtol (1995);
– Health and medicine: Marteleto and dos Santos
Carvalho (2015), and Roos and Hedlund (2016);
– Music: Abrahamsen (2003), Pietras and Robinson
(2012), and van Venrooij and Schmutz (2015);
– Philippine history: Luyt (2015);
– Picture collections: Kjellman (2006).
References
Abrahamsen, Knut Tore. 2003. “Indexing of Musical
Genres: An Epistemological Perspective.” Knowledge
Organization 30: 144-69.
Albrechtsen, Hanne. 2015. “This is not Domain Analy-
sis.” Knowledge Organization 42: 557-61.
Albrechtsen, Hanne, and Annelise Mark Pejtersen. 2003.
“Cognitive Work Analysis and Work Centered Design
of Classification Schemes.” Knowledge Organization 30:
213-27.
American Psychiatric Association. 1952. Diagnostic and
Statistical Manual: Mental Disorders. Washington, DC:
American Psychiatric Association.
American Psychiatric Association. 1968. DSM-II: Diagnos-
tic and Statistical Manual of Mental Disorders, 2nd ed.
Washington, DC: American Psychiatric Association.
http://www.behaviorismandmentalhealth.com/wp-
content/uploads/2015/08/DSM-II.pdf
American Psychiatric Association. 1974. Diagnostic and sta-
tistical manual of mental disorders, 2nd ed, 6th printing.
Washington, DC: American Psychiatric Association.
Andersen, Heine. 2000. “Influence and Reputation in the
Social Sciences-How Much do Researchers Agree?”
Journal of Documentation 56: 674-92.
Arango, Guillermo. 1994. “Domain Analysis Methods.”
In Software Reusability, ed. Wilhelm Schäfer, Rubén
Prieto-Díaz and Masao Matsumoto. Ellis Horwood
workshops series. Chichester: Ellis Horwood, 17-49.
Arango, Guillermo and Rubén Prieto-Diaz. 1991. “Intro-
duction and Overview: Domain Analysis Concepts and
Research Directions.” In Domain analysis and software sys-
tems modeling, ed. Rubén Prieto-Diaz and Guillermo
Arango. IEEE Computer Society Press tutorial. Los
Alamitos, CA: IEEE Computer Society Press, 9-32.
Audunson, Ragnar, Ragnar Nordlie, and Inger Cathrine
Spangen. 2003. “The Complete Librarian - an Outdat-
ed Species? LIS Between Profession and Discipline.”
New library world 104: 195-202.
Bakhurst, David. 1993. “Marxism.” In Companion to Epis-
temology, ed. Jonathan Dancy, and Ernest Sosa. Black-
well Companions to Philosophy. Oxford: Blackwell,
268-70.
Banerjee, Shreya, and Anirban Sarkar. 2016. “Ontology-
Driven Approach Towards Domain-Specific System
Design.” International Journal of Metadata, Semantics and
Ontologies 11: 39-60.
Bates, Marcia J. 1987. “Information: The Last Variable.”
In ASIS '87: Proceedings of the 50th ASIS Annual Meet-
ing, Boston, Massachusetts, October 4-8, 1987, ed. Ching-
chih Chen. Proceedings of the ASIS Annual Meeting
24. Medford, N.J.: Learned Information, 6-10.
Bawden, David. 2015. “On not Being a Weak Discipline.”
The Occasional Informationist: Irregular Thoughts on the Infor-
mation Sciences (blog). https://theoccasionalinformation
ist.com/2015/07/06/on-not-being-a-weak-discipline/
Beak, Jihee, Jeanette Glover, Daniel Martínez-Ávila and
Suellen Oliveira Milani. 2013. “International Compara-
tive Domain Analysis in Knowledge Organization Re-
search Topics in Four Countries - Brazil, South Korea,
Spain and the United States.” In Proceedings from North
American Symposium on Knowledge Organization 4, Mil-
waukee, Wisconsin, ed. Richard P. Smiraglia. ISKO-
CUS, 30-9. doi:10.7152/nasko.v4i1.14643
Beghtol, Clare. 1995. “Domain Analysis, Literary War-
rant, and Consensus: The Case of Fiction Studies.”

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
460
Journal of the American Society for Information Science 46:
30-44.
Berlin, Brent. 1992. Ethnobiological Classification: Principles of
Categorization of Plants and Animals in Traditional Societies.
Princeton, NJ: Princeton University Press.
Bondebjerg, Ib. 2001. “Film: Genres and Genre Theory.”
In International Encyclopedia of the Social & Behavioral Sci-
ences, ed. Neil J. Smelser and Paul B. Baltes. Amster-
dam: Elsevier, 5640-46.
Bruce, Murray. 2003. “Foreword: A Brief History of
Classifying Birds.” In Handbook of the Birds of the World,
ed. Josep del Hoyo, Andrew Elliott, Jordi Sargatal, Jo-
se Cabot et al. Vol. 8. Barcelona: Lynx Edicions, 11-
43.
Budtz Pedersen, David, Frederik Stjernfelt, and Claus
Emmeche, eds. 2016. Mapping Frontier Research in the
Humanities. London: Bloomsbury Publishing.
Castanha, Renata, Fábio Rosas, and Maria Cláudia Grácio.
2016. “The Complementarity of Hjørland’s and Ten-
nis’s Proposals to Domain Analysis under Bibliomet-
rics.” In Knowledge Organization for a Sustainable World:
Challenges and Perspectives for Cultural, Scientific, and Techno-
logical Sharing in a Connected Society; Proceedings of the Four-
teenth International ISKO Conference 27-29 September 2016
Rio de Janeiro, Brazil, ed. Chaves Guimarães, José Au-
gusto, Oliveira Milani, Suellen Dodebei, and Vera. Ad-
vances in Knowledge Organization 15. Würzburg: Er-
gon Verlag, 219-26.
Chua, Alton Y. K., and Christopher C. Yang. 2008. “The
Shift Towards Multi-Disciplinarity in Information Sci-
ence.” Journal of the American Society for Information Science
and Technology 59: 2156-70.
Cooke, Nancy J. 1994. “Varieties of Knowledge Elicitation
Techniques.” International Journal of Human-Computer
Studies 41: 801-49.
Dahlberg, Ingetraut. 2006. “Knowledge Organization: A
New Science?” Knowledge Organization 33: 11-9.
Dahlberg, Ingetraut. 2017. “Why a New Universal Classi-
fication System is Needed.” Knowledge Organization 44:
65-71.
Dam Christensen, Hans. 2007. “Kunsten at vælge fra: Om
bradfordsk materialevalg og vidensorganiseringens so-
cialitet.” Dansk Biblioteksforskning 3, no.1: 31-43. http://
www.danskbiblioteksforskning.dk/2007/nr1/dam%5F
christensen.pdf
Dam Christensen, Hans. 2014. “The Framing of Scien-
tific Domains: About UNISIST, Domain Analysis and
Art History” Journal of Documentation 70: 261-81.
Dextre Clarke, Stella G. 2016. “Origins and Trajectory of
the Long Thesaurus Debate.” Knowledge Organization
43: 138-44.
Dragusin, Radu, Paula Petcu, Christina Lioma, Birger
Larsen, Henrik L. Jørgensen, Ingemar Cox, Lars K.
Hansen, Peter Ingwersen, and Ole Winther. 2013a.
“FindZebra: A Search Engine for Rare Diseases.” In-
ternational Journal of Medical Informatics 82: 528-538.
doi:10.1016/j.ijmedinf.2013.01.005
Dragusin, Radu, Paula Petcu, Christina Lioma, Birger
Larsen, Henrik L. Jørgensen, Ingemar Cox, Lars K.
Hansen, Peter Ingwersen, and Ole Winther. 2013b.
“Specialised Tools are Neded When Searching the
Web for Rare Disease Diagnoses.” Rare Diseases 1.
doi:10.4161/rdis.25001
Drescher, Jack. 2015. “Out of DSM: Depathologizing
Homosexuality.” Behavioral Sciences 5: 565-75.
Dubitzky, Werner, Olaf Wolkenhauer, Hiroki Yokota, and
Kwang-Hyun Cho, ed. 2013. Encyclopedia of Systems Bi-
ology. New York: Springer.
Egan, Margaret E., and Jesse H. Shera. 1952. “Founda-
tions of a Theory of Bibliography.” Library Quarterly
22, no. 2: 125-37.
Eriksson, Rune. 2010. Klassifikation og indeksering af
skønlitteratur – et teoretisk og historisk perspektiv.
Ph.D. diss., Royal School of Library and Information
Science. http://pure.iva.dk/files/30769518/Eriksson%
5Fhd%5F2010.pdf
Evans, Eric. 2003. Domain-Driven Design: Tackling Complexi-
ty in the Heart of Software. Boston: Addison-Wesley.
Fernie, Eric, ed. 1995. Art History and its Methods: A Criti-
cal Anthology. London: Phaidon Press.
Fidel, Raya. 2012. Human Information Interaction: An Ecologi-
cal Approach to Information Behavior. Cambridge, MA:
MIT Press.
Fjeldså, Jon. 2013. “Avian Classification in Flux.” In
Handbook of the Birds of the World, ed. Josep del Hoyo,
Andrew Elliott, Jordi Sargatal, Jose Cabot et al. vol.
17. Barcelona: Lynx Edicions, 77-146.
Fox, Melodie J. 2012. Review of A Schema for Unifying
Human Science: Interdisciplinary Perspectives on Culture and
Classifying Science: Phenomena, Data, Theory, Method, Prac-
tice by Rick Szostak. Knowledge Organization 39: 300-3.
Fox, Melodie J. 2016. “'Priorities of Arrangement' or a
‘Hierarchy of Oppressions?’: Perspectives on Intersec-
tionality in Knowledge Organization.” Knowledge Organ-
ization 43: 373-83.
Forskningsrådsnämnden [Swedish council for planning
and co-ordination of research]. 1989. Biblioteks- och
informationsvetenskap: förslag inför 90-talet. Rapport
89, no. 4. Stockholm: Forskningsrådsnämnden
Foskett, D. J. 1974. Classification and Indexing in the Social
Sciences, 2nd ed. London: Butterworths.
Fry, Jenny. 2006. “Scholarly Research and Information
Practices: A Domain Analytic Approach.” Information
Processing and Management 42: 299-316.
Fry, Jenny, and Talja, Sanna. 2007. “The Intellectual and
Social Organization of Academic Fields and the Shap-

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
461
ing of Digital Resources.” Journal of Information Science
33: 115-33.
Fulani, Lenora. 2000. “Race, Identity and Epistemology.”
In Postmodern Psychologies, Societal Practice and Political Life,
ed. Louis Holzman and John R. Morss. New York:
Routledge, 151-64.
http://lchc.ucsd.edu/mca/Paper/Fulani.pdf
Garvey, William D. and Belver C. Griffith, 1964. “Scien-
tific Information Exchange in Psychology.” Science,
n.s., 146: 1655-1659.
Gnoli, Claudio. 2007. “Ten Long-Term Research Ques-
tions in Knowledge Organization.” Knowledge Organiza-
tion 35: 137-49.
Gnoli, Claudio, and Rick Szostak. 2014. “Universality is
Inescapable.” In 25th ASIS SIG/CR Classification Re-
search Workshop. Advances in Classification Research
Online 25. doi:10.7152/acro.v25i1.14906
Guimarães, José Augusto Chaves, Daniel Martínez-Ávila,
and Bruno Henrique Alves. 2015. “Epistemic Commu-
nities in Knowledge Organization: An Analysis of Re-
search Trends in the Knowledge Organization Journal.”
Paper resented at ISKO UK biennial conference 13th –
14th July 2015, London. http://www.iskouk.org/
content/epistemic-communities-knowledge- organiza
tion-analysis-research-trends-knowledge-organization
Guimarães, José Augusto Chaves, and Natália Bolfarini
Tognoli. 2015. “Provenance as a Domain Analysis
Approach in Archival Knowledge Organization.”
Knowledge Organization 42: 562-9.
Hirschfeld, Lawrence A. and Susan A. Gelman, eds. 1994.
Mapping the Mind: Domain Specificity in Cognition and Cul-
ture. Cambridge: Cambridge University Press.
Hjørland, Birger. 1994. “Nine Principles of Knowledge
Organization.” In Knowledge Organization and Quality
Management: Proceedings of the Third International ISKO
Conference, 20-24 June, 1994, Copenhagen, Denmark, ed.
Hanne Albrechtsen and Susanne Oernager. Advances
in Knowledge Organization 4. Frankfurt/Main: In-
deks Verlag, 91-100.
Hjørland, Birger. 1998a. “Officiel opposition ved Louise
Limbergs disputation 20. Marts 1998 på Göteborgs
Universitet.” Svensk Biblioteksforskning /Swedish Library
Research no. 1: 27-63.
Hjørland, Birger. 1998b. “The Classification of Psycholo-
gy: A Case Study in the Classification of a Knowledge
Field.” Knowledge Organization 25: 162-201.
Hjørland, Birger. 2002a. “Domain Analysis in Infor-
mation Science: Eleven Approaches-Traditional as well
as Innovative.” Journal of Documentation 58: 422-62.
Hjørland, Birger. 2002b. “Epistemology and the Socio-
Cognitive Perspective in Information Science.” Journal
of the American Society for Information Science and Technology
53: 257-70.
Hjørland, Birger. 2002c. “The Special Competency of In-
formation Specialists.” Journal of the American Society for
Information Science and Technology 53: 1275-6.
Hjørland, Birger. 2004. “Domain Analysis: A Socio-
Cognitive Orientation for Information Science Re-
search.” Bulletin of the American Society for Information Sci-
ence and Technology 30, no. 3: 17-21.
Hjørland, Birger. 2008. “Core Classification Theory: A
Reply to Szostak.” Journal of Documentation 64: 333-42.
Hjørland, Birger. 2009. “Concept Theory.” Journal of the
American Society for Information Science and Technology 60:
1519-36.
Hjørland, Birger. 2013a. “Facet analysis: The logical ap-
proach to knowledge organization.” Information pro-
cessing and management 49, no. 2: 545-57.
Hjørland, Birger. 2013b. “Information Science and its
Core Concepts: Levels of Disagreement.” In Theories
of Information, Communication and Knowledge: A Multidisci-
plinary Approach, ed. Fidelia lbekwe-SanJuan and Tom
Dousa. Dordrecht: Springer, 205-35.
Hjørland, Birger. 2013c. “The Classification of Psycholo-
gy: A Case Study in the Classification of a Knowledge
Field.” Knowledge Organization 40: 11-27.
Hjørland, Birger. 2016a. "Informetrics Needs a Founda-
tion in the Theory of Science.” In Theories of Informet-
rics and Scholarly Communication, ed. Cassidy Sugimoto.
Berlin: de Gruyter, 20-46.
Hjørland, Birger. 2016b. “Knowledge Organization.”
Knowledge Organization 43: 475-84.
Hjørland, Birger. 2016c. “The Paradox of Atheoretical
Classification.” Knowledge Organization 43: 313-23.
Hjørland, Birger. 2017a. Review of Theory development in
the information sciences, ed. Diane H. Sonnenwald. Journal
of the Association for Information Science and Technology 68:
1796-1801.
Hjørland, Birger. 2017b. “Classification.” Knowledge Organ-
ization 44: 97-128.
Hjørland, Birger. 2017c. “Subject (Of Documents).”
Knowledge Organization 44: 55-64.
Hjørland, Birger, and Hanne Albrechtsen. 1995. “Toward
a New Horizon in Information Science: Domain
Analysis.” Journal of the American Society for Information
Science 46: 400-25.
Hjørland, Birger, and Jenna Hartel 2003. “Ontological,
Epistemological and Sociological Dimensions of Do-
mains.” Knowledge Organization 30: 239-45.
Holmberg, John Howard. 2013. "Nonmodern Philosophy
and the Ideology of Domain analysis.", Thesis, Royal
School of Library and Information Science.
Hourihan Jansen, Eva. 2016. “Proposal for CoLIS9: Do-
main Analysis; Assumptions and New Techniques for
Articulating Domains.” http://www.webcitation.org/
6pOYA1QrI

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
462
Keilty, Patrick, and Richard P. Smiraglia. 2016. “Gay Male
Nomenclature.” In Knowledge Organization for a Sustaina-
ble World: Challenges and Perspectives for Cultural, Scientific,
and Technological Sharing in a Connected Society: Proceedings
of the Fourteenth International ISKO Conference 27-29 Sep-
tember 2016 Rio de Janeiro, Brazil, ed. José Augusto
Chaves Guimarães, Suellen Oliveira Milani, Vera Do-
debei. Advances in Knowledge Organization 15.
Wurzburg: Ergon, 579-86.
Kelly, Steven and Juha-Pekka Tolvanen. 2008. Domain-
Specific Modeling: Enabling Full Code Generation. Hoboken:
Wiley.
Khalidi, Muhammad Ali. 2013. Natural Categories and Hu-
man Kinds: Classification in the Natural and Social Sciences.
Cambridge: Cambridge University Press.
Kierkegaard, Søren. (1850) 2015. Kierkegaard’s Journals and
Notebooks, vol. 8, Journals NB 21-25, ed. Niels Jørgen
Cappelørn, Alastair Hannay, Bruce H. Kirmmse, Da-
vid D. Possen, Joel D. S. Rasmussen and Vanessa
Rumble. Princeton, N.J.: Princeton University Press.
Kjellman, Ulrika. 2006. Från kungaporträtt till läsketikett: En
domänanalytisk studie över Kungl. bibliotekets bildsamling med
särskild inriktning mot katalogiserings- och indexeringsfrågor.
Skrifter utgivna av Institutionen for ABM vid Uppsala
universitet 2. Uppsala: Uppsala Universitet.
Kuhn, Thomas S. 1962. The Structure of Scientific Revolu-
tions. Chicago: University of Chicago Press.
Langridge, D. W. 1976. Classification and Indexing in the Hu-
manities. London: Butterworths.
Larsen, Svend. 2009. “Digital effektivitet i bibliotekerne.”
Danmarks Biblioteker, no. 1: 16-17. http://www.db.dk/
files/DB0109.pdf
Lee, Frederic. 2009. A History of Heterodox Economics: Chal-
lenging the Mainstream in the Twentieth Century. Routledge
Advances in Heterodox Economics 4. London:
Routledge.
Limberg, Louise. 2017. “Synthesizing or diversifying library
and information science. Sketching past achievements,
current happenings and future prospects, with an inter-
est in including or excluding approaches.” Information Re-
search 22, no. 1. http://InformationR.net/ir/22-1/colis/
colis1600.html
Lisboa, Liana Barachisio, Vinicius Cardoso Garciaa, Daniel
Lucrédio, Eduardo Santana de Almeida, Silvio Romero
de Lemos Meira, and Renata Pontin de Mattos Fortes.
2010. “A Systematic Review of Domain Analysis
Tools.” Information and Software Technology 52: 1-13.
López-Huertas, María J. 2015. “Domain Analysis for In-
terdisciplinary Knowledge Domains.” Knowledge Organ-
ization 42: 570-80.
Luyt, Brendan. 2015. “Replacing the Ideology of Infor-
mation by Exploring Domains of Knowledge.” Journal
of Documentation 71: 1289-99.
Lykke-Nielsen, Marianne. 2000. “Domain analysis, an
important part of thesaurus construction.” In 11th
ASIS SIG/CR Classification Research Workshop, ed. Da-
gobert Soergel, Padmini Srinivasan, and Barbara H.
Kwasnik 11: 9-50. doi:10.7152/acro.v11i1.12768
Mai, Jens-Erik. 2005. “Analysis in Indexing: Document
and Domain Centered Approaches.” Information pro-
cessing and management 41: 599-611.
Mai, Jens-Erik. 2008. “Actors, Domains, and Constraints
in the Design and Construction of Controlled Vocab-
ularies.” Knowledge Organization 35: 16-29.
Mai, Jens-Erik. 2010. “Classification in a Social World:
Bias and Trust.” Journal of Documentation 66: 627-42.
Marteleto, Regina Maria, and Lidiane dos Santos Car-
valho. 2015. “Health as a Knowledge Domain and So-
cial Field: Dialogues with Birger Hjørland and Pierre
Bourdieu.” Knowledge Organization 42: 581-90.
Martínez-Ávila, Daniel, José Augusto Chaves Guimarães,
and Isadora Victorino Evangelista. 2017. “Epistemic
Communities in Knowledge Organization: An Analysis
of the NASKO Meetings Proceedings.” In Proceedings
from North American Symposium on Knowledge Organization
6, Urbana-Champaign, Illinois. ISKO-CUS. http://
www.iskocus.org/NASKO2017papers/NASKO2017_
paper_11.pdf
Mattsson, Kurt. 2016. ”Cognitive work analysis i design
af kontrollerede vokabularer.” Thesis, Royal School of
Library and Information Science.
Millett, Scott and Nick Tune. 2015. Patterns, Principles and
Practices of Domain-Driven Design. Indianapolis: Wiley.
Mills, Jack. 2004. “Faceted Classification and Logical Di-
vision in Information Retrieval.” Library Trends 52:
541-70.
Mote, L. J. B. 1962. “Reasons for the Variation of Infor-
mation Needs of Scientists.” Journal of Documentation
18: 169-75.
Mustafa El Hadi, Widad. 2015. “Cultural Interoperability
and Knowledge Organization Systems.” In Organização
do conhecimento e diversidade cultural, ed. Isadora Victorino
Evangelista, Gilberto Gomes Candido, Rafael Apare-
cido Moron Semidao, Rafael Cacciolari Dalessandro,
and Suellen Oliveira Milani. Estudos avançados em or-
ganização do conhecimento 3. Marillia: Sociedade Bra-
sileira de Organização do Conhecimento, 575-606.
http://isko-brasil.org.br/wp-content/uploads/2015/
09/Organiza%C3%A7%C3%A3o-do-Conhecimento-e-
Diversidade-Cultural-ISKO-BRASIL-2015.pdf
Naikar, Neelam. 2013. Work Domain Analysis: Concepts,
Guidelines, and Cases. Boca Raton: CRC Press.
Nascimento, Denise Morado, and Regina Maria Marteleto.
2008. “Social Field, Domains of Knowledge and In-
formational Practice.” Journal of Documentation 64: 397-
412.

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
463
Neighbors, James M. 1980. "Software Construction Us-
ing Components." PhD diss., University of California,
Irvine.
Parrochia, Daniel and Pierre Neuville. 2013. Towards a
General Theory of Classifications. Bäsel: Birkhaüser.
Pietras, Monika, and Lyn Robinson. 2012. “Three Views
of the ‘Musical Work’: Bibliographical Control in the
Music Domain.” Library Review 61: 551-60.
Prieto-Díaz, Rubén. 1990. “Domain Analysis: An Intro-
duction.” ACM SIG Soft Software Engineering Notes 15,
no. 2: 47-54.
Prieto-Diaz, Rubén. 1991. “Implementing Faceted Classi-
fication for Software Reuse.” Communications of the
ACM 34, no. 5: 88-97.
Prieto-Diaz, Rubén. 1992. “Applying Faceted Classifica-
tion to Domain Analysis.” In ASIS '92: Proceedings of
the 55th ASIS Annual Meeting, Pittsburg, PA, October 26-
29, 1992, ed. Debora Shaw. Medford, NJ: Learned In-
formation, 316.
Raghavan, K. S., K. H. Apoorva, and Aarti Jivrajani.
2015. “Information Retrieval as a Domain: Visualiza-
tions Based on Two Data Sets.” Knowledge Organization
42: 591-601.
Rasmussen, Jens, Annelise Mark Pejtersen and L. P.
Goodstein, 1994. Cognitive Systems Engineering. Wiley Se-
ries in Systems Engineering. New York: Wiley.
Robertson, Stephen. 2008. “The State of Information
Retrieval.” Paper presented at Agenda for Information
Retrieval ISKO-UK Open Meetings 26th June 2008
London, Presentation and audio recording. http://
www.iskouk.org/content/state-information-retrieval-
researchers-view
Roos, Annikki, and Turid Hedlund. 2016. “Using the
Domain Analytical Approach in the Study of Infor-
mation Practices in Biomedicine.” Journal of Documenta-
tion 72: 961-86.
Saracevic, Tefko. 1975. “Relevance: A Review of and a
Framework for the Thinking on the Notion in Infor-
mation Science.” Journal of the American Society for Infor-
mation Science 26: 321-43.
Saracevic, Tefko. 1992. “Information Science: Origin, Evo-
lution and Relations.” In Conceptions of Library and Infor-
mation Science: Historical, Empirical and Theoretical Perspec-
tives; Proceedings of the International Conference Held for the
Celebration of 20th Anniversary of the Department of Infor-
mation Studies, University of Tampere, Finland, 26-28 August
1991, ed. Pertti Vakkari and Blaise Cronin. London:
Taylor Graham, 5-27. http://www.citi.columbia.edu/
B8210/read1/saracevic_information_science_origin.pdf
Shapere, Dudley. 1977. “Scientific Theories and their
Domains.” In The Structure of Scientific Theories, ed.
Frederick Suppe. 2nd ed. Urbana: University of Illi-
nois Press, 518-65.
Shapere, Dudley. 1984. Reason and the Search for Knowledge:
Investigations in the Philosophy of Science. Boston studies in
the philosophy of science 78. Dordrecht: D. Reidel.
Shera, Jesse H. 1965. “The training of the chemical li-
brarian: A challenge and an opportunity.” In Libraries
and the organization of knowledge. London: Crosby Lock-
wood, 185-96.
Slife, Brent D. and Richard N. Williams. 1995. What's Be-
hind the Research? Discovering Hidden Assumptions in the
Behavioral Sciences. London: SAGE Publications.
Smiraglia, Richard P. 2012. “Epistemology of Domain
Analysis.” In Cultural Frames of Knowledge, ed. Richard P.
Smiraglia and Hur-Li Lee, Würzburg: Ergon Verlag,
111-24.
Smiraglia, Richard P. 2014. The Elements of Knowledge Or-
ganization. Cham: Springer.
Smiraglia, Richard P. 2015. Domain Analysis for Knowledge
Organization: Tools for Ontology Extraction. Chandos in-
formation professional series. Oxford: Chandos Pub-
lishing.
Smith, Catherine Arnott. 2005. “An Evolution of Ex-
perts: MEDLINE in the Library School.” Jour nal of the
Medical Library Association 93: 53-60.
Søndergaard, Trine Fjordback, Jack Andersen, and Birger
Hjørland. 2003. “Documents and the Communication
of Scientific and Scholarly Information: Revising and
Updating the UNISIST Model.” Journal of Documenta-
tion 59: 278-320.
Sonnenwald, Diane H., ed. 2016. Theory Development in the
Information Sciences. Information 1. Austin: University
of Texas Press.
Stam, Robert. 2000. Film Theory: An Introduction. Malden,
MA: Blackwell Publishers.
Szostak Rick. 2008. “Classification, Interdisciplinarity,
and the Study of Science.” Journal of Documentation 64:
319-32.
Szostak, Rick. 2010. “Universal and Domain-Specific
Classifications from an Interdisciplinary Perspective.”
In Paradigms and Conceptual Systems in Knowledge Organiza-
tion: Proceedings of the Eleventh International ISKO Confer-
ence, 23-26 February 2010, Rome, Italy, ed. Claudio Gnoli
and Fulvio Mazzochi. Advances in Knowledge Organ-
ization 12. Würzburg: Ergon, 71-77.
Szostak, Rick. 2011. “Complex Concepts into Basic Con-
cepts.” Journal of the American Society for Information Sci-
ence and Technology 62: 2247-65.
Szostak, Rick. 2013. “Speaking Truth to Power in Classi-
fication: Response to Fox’s Review of My Work; KO
39: 4, 300.” Knowledge Organization 40: 76-7.
Szostak, Rick, Claudio Gnoli and Maria J. López-Huertas.
2016. Interdisciplinary Knowledge Organization. Cham:
Springer.

Knowl. Org. 44(2017)No.6
Reviews of Concepts in Knowledge Organization
464
Tairas, Robert, Marjan Mernik and Jeff Gray. 2008. “Using
Ontologies in the Domain Analysis of Domain-Specific
Languages.” In: Proceedings of the 1st International Workshop
on Transforming and Weaving Ontologies in Model Driven En-
gineering 2008. CEUR Workshop Proceedings 395. Aa-
chen: CEUR. http://ceur-ws.org/Vol-395/paper02.pdf
Talja, Sanna. 2005. “The Domain Analytic Approach to
Scholar’s Information Practice.” In Theories of Infor-
mation Behavior, ed. Karen E. Fisher, Sanda Erdelez and
Lynne McKechnie. ASIST monograph series. Med-
ford, NJ: Information Today, 123-27.
Talja, Sanna, and Hanni Maula. 2003. “Reasons for the
Use and Non-Use of Electronic Journals and Data-
bases: A Domain Analytic Study in Four Scholarly
Disciplines”. Journal of Documentation 59: 673-91.
Teich, Elke, Stefania Degaetano-Ortlieb, Peter Fan-
khauser, Hannah Kermes, and Ekaterina Lapshinova-
Koltunski. 2016. “Linguistic Construal of Disciplinari-
ty: A Data-Mining Approach Using Register Features.”
Journal of the Association for Information Science and Tech-
nology 67: 1668-78.
Tengström, Emin. 1993. “Biblioteks- och informations-
vetenskapen - ett fler- eller tvärvetenskapligt område?”
Svensk Biblioteksforskning 4, no. 1: 9-20.
Tennis, Joseph T. 2003. “Two Axes of Domains for Do-
main Analysis.” Knowledge Organization 30: 191-95.
Tennis, Joseph T. 2012. “What Does a Domain Analysis
Look Like in Form, Function, and Genre?” Brazilian
Journal of Information Science 6, no. 1: 3-14. http://
www2.marilia.unesp.br/revistas/index.php/bjis/article/
view/3026/2300
Toulmin, Stephen. (1972) 1977. Human Understanding: The
Collective Use and Evolution of Concepts. Paperback re-
print, Princeton: Princeton University Press.
van Venrooij, Alex and Vaughn Schmutz. 2015.
“Classifications in Popular Music.” In International En-
cyclopedia of the Social & Behavioral Sciences, ed. James D.
Wright. 2nd ed. Amsterdam: Elsevier, 3: 799-804.
Vernon, Vaughn. 2013. Implementing Domain-Driven Design.
Upper Saddle River, NJ: Addison-Wesley.
Vernon, Vaughn. 2016. Domain-Driven Design Distilled. Bos-
ton: Addison-Wesley.
Vicente, Kim J. 1999. Cognitive Work Analysis: Towards Safe,
Productive, and Healthy Computer-Based Work. Mahwah,
NJ: Lawrence Erlbaum Associates.
Vickery, Brian Campbell. 1960. Faceted Classification: A
Guide to the Construction and Use of Special Schemes. Lon-
don: ASLIB.
Vickery, Brian Campbell. 1975. Classification and Indexing in
Science. 3rd ed. London: Butterworths.
Wallerstein, Immanuel, ed. 1996. Open the Social Sciences:
Report of the Gulbenkian Commission on the Restructuring of
the Social Sciences. Mestizo Spaces. Stanford: Stanford
University Press.
Walter, Tobias, Fernando Silva Parrieiras, and Steffen
Staab. 2014. “An Ontology Based Framework for
Domain Specific Modeling.” Software and Systems Model-
ing 13: 83–108.
Watson, John B. 1928. Psychological Care of Infant and Child.
Family in America. New York: W. W. Norton.
Webb, William H., Alan R Beals, and Carl Milton White,
eds. 1986. Sources of Information in the Social Sciences: A
Guide to the Literature. 3rd ed. Chicago: American Li-
brary Association.
Weber, Nicholas M., Karen S. Baker, Andrea K. Thomer,
Tiffany C. Chao, and Carole L. Palmer. 2012. “Value
and Context in Data Use: Domain Analysis Revisited.”
Proceedings of the American Society for Information Science
and Technology 49: 1-10. doi:10.1002/meet.14504901168
Wesolek, Andrew. 2012. “Wittgensteinian Support for
Domain Analysis in Classification.” Library Philosophy
and Practice 795. http://digitalcommons.unl.edu/libphil
prac/795
Whitley, Richard. 2000. The Intellectual and Social Organiza-
tion of the Sciences, 2nd ed. Oxford: Clarendon Press.
WordNet 2.0, s.v.domain.
Zandonade, Tarcisio. 2004. “Social Epistemology from
Jesse Shera to Steve Fuller.” Library Trends 52: 810-32.
Ørom, Anders. 2003. “Knowledge Organization in the
Domain of Art Studies – History, Transition and Con-
ceptual Changes.” Knowledge Organization 30: 128-43.