ISSN: 2474-3542 Journal homepage: http://journal.calaijol.org
Represent Changes of Knowledge Organization Systems on the
Semantic Web
Qing Zou
Abstract:
Traditional knowledge organization systems (KOS) including thesauri, classification
schemes, taxonomies, subject heading systems, name authorities, and other lists of terms
and codes have been playing important roles in indexing, information organization, and
retrieval. With the advent of the semantic web, a large number of them have been converted
into Linked Open Data (LOD) datasets. Since the Simple Knowledge Organization
Systems (SKOS) and SKOS eXtension for Labels (SKOS-XL) became formal World Wide
Web Consortium (W3C) recommendations, they have been applied to knowledge
organization systems. In this article, the issues surrounding changes, versioning control,
and evolution of KOS are investigated. From KOS services providers and consumers
perspectives, this study focuses on the representation of changes on the semantic web.
To cite this article:
Zou, Q. (2018). Represent Changes of Knowledge Organization Systems on the Semantic
Web. International Journal of Librarianship, 3(1), 67-77. doi:
https://doi.org/10.23974/ijol.2018.vol3.1.64
To submit your article to this journal:
Go to http://ojs.calaijol.org/index.php/ijol/about/submissions
INTERNATIONAL JOURNAL OF LIBRARIANSHIP, 3(1), 67-77
ISSN:2474-3542
Represent Changes of Knowledge Organization Systems on the
Semantic Web
Qing Zou
Lakehead University, Canada
ABSTRACT
Traditional knowledge organization systems (KOS) including thesauri, classification schemes,
taxonomies, subject heading systems, name authorities, and other lists of terms and codes have
been playing important roles in indexing, information organization, and retrieval. With the advent
of the semantic web, a large number of them have been converted into Linked Open Data (LOD)
datasets. Since the Simple Knowledge Organization Systems (SKOS) and SKOS eXtension for
Labels (SKOS-XL) became formal World Wide Web Consortium (W3C) recommendations, they
have been applied to knowledge organization systems. In this article, the issues surrounding
changes, versioning control, and evolution of KOS are investigated. From KOS services providers
and consumers perspectives, this study focuses on the representation of changes on the semantic
web.
Keywords: KOS, Change Representation, Linked Data, SKOS, SKOS-XL
INTRODUCTION
The Simple Knowledge Organization System (SKOS) provides a common data model for
organizing knowledge organization systems such as thesauri, classification schemes, subject
headings, and taxonomies (W3C, 2012). Since the Simple Knowledge Organization Systems
(SKOS) and SKOS eXtension for Labels (SKOS-XL) became formal World Wide Web
Consortium (W3C) recommendations, they have been applied to knowledge organization systems.
SKOS and SKOS-XL capture the common relations of KOS in a formal and explicit way.
Moreover, it potentially improves the interoperability between KOS. SKOS and SKOS-XL can not
only bring paper format KOSs but electronic format KOSs into an open and highly connected
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68
linked data world.
However, an actively used KOS needs to be regularly updated to reflect the development of
human knowledge. Therefore, changes are inevitable for KOS. Changes need to be properly
managed by KOS services providers and KOS consumers because an out-of-date or poorly
managed KOS may provide obsolete information that may hinder information retrieval. KOS
services providers often actively maintain their KOSs. For example, a thesaurus such as Arts and
Architecture Thesaurus (AAT)1, subject heading systems such as Library of Congress Subject
Headings (LCSH) 2 , Canadian Subject Headings (CSH) 3 and RVM (Répertoire de vedettes-
matière)4 publish revisions regularly. However, KOS consumers have difficulty to keep up with
KOS services providers. For instance, researchers have identified obsolete subject headings in
library automation systems (Buckland, 2012; Chan & Vizine-Goetz, 1997). To actively manage
KOS changes at the consumers' side, KOS changes need to be explicitly expressed and properly
propagated. With more and more KOSs being published on the semantic web, the issue of KOS
changes needs to be investigated in this new context.
LITERATURE REVIEW
This section is organized into two subsections. Related studies about KOS changes are reviewed
in the first subsection. Studies related to change representation are summarized in the second
subsection.
Changes in KOS
The obsolete problem caused by KOS changes especially in subject heading systems has long been
identified (Ashman, 2006; Buckland, 2012; Chan & Vizine-Goetz, 1997). Changes in KOS are
caused by new topics, names, concepts, and cultural changes (Buckland, 2012). If changes in KOS
are not propagated to applications, the old terms, concepts, and names become obsolete.
Since SKOS has been widely applied in publishing KOS on the semantic web, the capabilities
of handling KOS changes in SKOS have been examined (Tennis, 2005). The two mechanisms (i.e.,
notes and web ontology language (OWL) versioning) for concept schema revision provided by
SKOS do not “account for … refinement, lumping and other transformations of concepts” (Tennis,
2005, p. 276). Although Tennis (2005) proposes an approach to extend SKOS Core to track
vocabularies changes over their lifetime through capturing three different changes including
lumping, refining, and relationship changes, there are no detailed explanations on how the
1 http://www.getty.edu/research/tools/vocabularies/aat/
2 http://id.loc.gov/authorities/subjects.html
3 https://www.bac-lac.gc.ca/eng/services/canadian-subject-headings/Pages/canadian-subject-headings.aspx
4 https://rvmweb.bibl.ulaval.ca/
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69
approach works. For example, regarding relationship changes, it is not clear that the proposed
"skos:wasRelated” will stick to the concept along its lifetime or not. If one concept has associative
relations with two concepts and two association relations are changed to hierarchical relations
more than one time, there will be more than two “skos:wasRelated” of one concept in the KOS.
There is no way to tell the temporal differences between the two “skos:wasRelated”. In addition,
it is not clear what the differences between the proposed “skos:ConceptLump” and “skos:Concept”
and between the proposed “skos:ConceptRefinement” and “skos:Concept”. From the perspectives
of services providers and consumers, the approach may not be applicable.
Tennis (2007) categorized characteristics of scheme changes into three major changes
including “structural change, word-use change and textual change” (p.90). Traditionally, term
records have been used to manage values of thesaurus entries by thesaurus management manuals
and standards (Aitchison, Bawden, & Gilchrist, 2000; National Information Standards
Organization, 2005; Soergel, 1974). Tennis (2007) proposed values records, an expanded version
of term records, for managing changes. However, although the approach was claimed for scheme
versioning in the semantic web, it has not been empirically tested.
Tennis and Sutton (2008) differentiate the abstract concept and "concept instances" to capture
concept evolution in vocabulary development applications. However, this approach is bound to
vocabulary development applications as shown in the iterative workflow described in the article.
No doubt, there are some advantages to link concept instances to their abstract concepts. This
approach also brings in extra work on maintaining abstract concepts. It is not clear how this
approach can couple with situations when any changes happen to abstract concepts including
addition, modification, and deletion.
Change Representation
Change representation is one of the six phases (i.e., change capturing, change representation,
semantics of change, change implementation, change propagation, and change validation) of
ontology evolution in a cyclic loop (Stojanovic, Maedche, Motik, & Stojanovic, 2002). Ontology
can be defined as an “explicit specification of a conceptualization” (Gruber, 1993, p. 199). In a
broader sense, traditional knowledge organization systems include terms list, subject headings,
classification schemes, taxonomies, and thesauri are ontologies. Uschold and Gruninger (2004)
categorized taxonomies and thesauri as “lightweight-ontologies”. Since ontology change refers to
“the generic problem of changing an ontology in response to a certain need” (Flouris, Manakanatas,
Kondylakis, Plexousakis, & Antoniou, 2008, p. 117), studies focusing on ontology evolution,
versioning and change management are relevant to KOS changes.
Ontology Changes have been categorized into 1) atomic (basic) change; and 2) composite
changes (Javed, Abgaz, & Pahl, 2013). Noy, Chugh, Liu, and Musen (2006) introduced a Change
and Annotation Ontology (CHAO) to explicitly express the changes between different versions of
ontologies. A change history ontology is used to represent changes (Khattak, Batool, Pervez, Khan,
& Lee, 2013). A layered change history log has been introduced to log ontology changes (Javed,
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70
2013).
Taking into consideration of syntactic and semantics of ontologies, Zeginis, Tzitzikas, and
Christophides (2011) proposed “delta functions” to compare RDFs. A temporal logic approach is
used to manage and reason in different versions of an ontology (Huang & Stuckenschmidt, 2005).
Palma, Corcho, & Haase (2009) proposed OWL 2 change ontology for managing changes
following a temporal ordering.
Types of KOS changes have been identified. Changes happened in a thesaurus fall into six
categories: “amendment of existing terms, status of existing terms, deletion or demotion of existing
terms, addition of new, or deletion of old relationships, addition of new terms, amendment of
existing structure” (Aitchison et al., 2000, p. 170). Changes can be categorized into three general
groups including “structural change, word-use change and textual change” (Tennis, 2007, p. 90).
With more and more KOS published on the semantic web, KOS changes need to be discussed in
this new context.
In summary, change representation in ontology needs to take features of ontologies into
consideration. Since KOSs and ontologies are different, some methods (such as reasoning) used in
ontologies cannot apply to KOSs. In this study, methods such as change log and temporal order
are utilized in the investigation of KOS changes.
OBJECTIVE OF THE STUDY
This study aims to explore how to represent KOS changes on the semantic web.
METHODOLOGY
In order to address the issue, this study takes a three steps approach: 1) formally define changes in
KOS, 2) to model change sets; 3) to apply the change sets model to use cases which are taken from
Tennis’s Studies.
Changes Representation
In the context of the semantic web, Resource Description Framework (RDF) is the fundamental
tool and model for representing resources (Manola & Miller, 2004). Knowledge organization
systems can be encoded in RDF statements using SKOS and SKOS-XL. KOS changes can be
defined as any modification of a KOS.
Definition 1. A knowledge organization system is a set of concepts interrelated by
relationships. A KOS K can be denoted as:
K = (C, A, R)
Where C is a set of concepts, A is a set of attributes, and R is a set of relations. For each concept
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ci C, A(ci)= {a1, a2, …, am }, and R(ci) = { r1, r2, …, rn}.
In other words, a KOS can be considered as a set of RDF triples of form <subject, predicate, object>
with semantics defined in RDF, SKOS and SKOS-XL, if the KOS only uses SKOS and SKOS-
XL, RDF.
Definition 2. Operator + is an addition operation and +c is an operation to add a concept, +a(c)
is an operation to add an attribute to concept c, and +r(c) is an operation to add a relation to
concept c. More specifically, the three operations are denoted as follows:
Kold = (Cold , A old , R old) and Knew = (Cnew , A new , R new)
Kold +c = Knew , c∈Cnew Cold)
Kold +a(c) = Knew , c∈ Coldc∈Cnewa(c)∈Anew Aold)
Kold +r(c) = Knew , c∈ Coldc∈Cnewr(c)∈Rnew Rold)
Definition 3. Operator - is a deletion operation and -c is an operation to delete a concept, -a(c)
is an operation to delete an attribute of concept c, and -r(c) is an operation to delete a relation
of concept c. More specifically, the three operations are denoted as follows:
Kold = (Cold , A old , R old) and Knew = (Cnew , A new , R new)
Kold -c = Knew , c∈ Cold Cnew)
Kold -a(c) = Knew , c∈ Coldc∈Cnewa(c)∈ Aold Anew)
Kold -r(c) = Knew , c∈ Coldc∈Cnewr(c)∈ Rold Rnew)
Definition 4. Given two knowledge organization systems Kold = (Cold , A old , R old) and
Knew = (Cnew , A new , R new), the changes are ∆( Kold ->Knew) = ∆C and
∆C = Cnew - Cold = { Cnew (cCold)},
∆A =Cnew | A(c) A new Aold) },
∆R =Cnew | R(c) R new Rold) }
Two basic operations add and delete are defined above. In terms of changes in KOS, Tennis (2007)
identified structural change, word-use change and textual change. More specifically, KOS changes
include concept splitting and lumping (Tennis, 2005). Take the example used in Tennis (2005), the
changes can be represented using the definitions:
Table 1. Change example 1
DC2002 Terms
(a) Applications
(b) Web services
skos:Concept “Applications”
skos:Concept “Web services”
DC2003 Metadata Thesaurus
(a) Applications
NT Web services
skos:Concept “Applications”
skos:narrower “Web services”
skos:Concept “Web services”
The change in Table 1 can be considered as one relation addition operation. The concept
“Applications” has a “skos:narrower” relation with the concept “Web services” after the change:
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∆= ∆R=R(Concept(“Applications”)) = “skos:narrower” and
“skos:narrower(Concept(“Application”)) -> Concept(“Web services”)
The change can be represented by Turtle (a terse RDF triple language (Beckett, Berners-Lee,
Prud’hommeaux, & Carothers, 2014)) as follows:
changelog:operation01 a ch:RelationAdd ;
ch:hasTimeStamp “2018-03-01 15:34:45+5” ;
ch:subject skos:Concept “Application” ;
ch:relation “skos:narrower”;
ch:target skos:Concept “Web services” .
Changes are a set of operations. Therefore, a general model was built on Changeset (Tunnicliffe
& Davis, 2009), change log history (Khattak, Latif, & Lee, 2013), and layered change log (Javed
et al., 2013).
Figure 1. A KOS change set model
In this model, a change set contains a set of change operations. A change set represents a series of
KOS changes. KOS concepts, attributes, and relations participant in KOS changes and are changed
by change operations.
To express KOS changes, an ontology5 was developed based on the model. At the core of this
ontology, changes are formally defined. Figure 2 shows that the hierarchical structure of the
AtomicChange class.
5 http://nkos.info/ontology/cs.owl
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Figure 2. The AtomicChange class and subclasses
The example 1 is complete with the following statements that link the operation to a change set
using the developed ontology. Suppose that "ch" is the prefix for the ontology. The following is in
a Turtle format:
changelog: ChangeSet01 a ch:ChangeSet
ch:hasChangeBeginTime “2017-12-01 15:34:45+5”;
ch:hasChangeEndTime “2017-12-01 15:35:00+5”.
ch:operator changelog:agent01 ;
ch:hasOperation changelog:operation01.
changelog:operation01 a ch:RelationAdd ;
ch:hasTimeStamp “2018-03-01 15:34:45+5” ;
ch:subject skos:Concept “Application” ;
ch:relation “skos:narrower”;
ch:target skos:Concept “Web services” .
The statements indicate when the change starts and ends, who is the operator, and to which
operation it links. In this example, the operation (changelog:operation01) is a RelationAdd
operation that includes subject, relation, and target.
The second example is listed in Table 2 (Tennis, 2005). In the example, two concepts lumped
together.
Table 2. Change example 2
DC2002 Terms
(a) Metadata harvesting
(b) Open Archives Initiative
skos:Concept “Metadata harvesting”
skos:Concept “Open Archives Initiative”
DC2003 Metadata Thesaurus skos:Concept “Open Archives Initiative Protocol
for Metadata Harvesting”
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(a) Open Archives Initiative Protocol for
Metadata Harvesting
With the change set model, the change can be represented in Turtle format as follows:
changelog: ChangeSet02 a ch:ChangeSet; // A Change Set
ch:hasReason “reason 2”;
ch:hasChangeBeginTime “2017-12-02 15:34:45+5”;
ch:hasChangeEndTime “2017-12-02 15:35:00+5”.
ch:hasOperation changelog:orderedOperations.
changelog:conceptDelete01 a ch:ConceptDelete ; // A change operation
ch:operator changelog:agent01 ;
ch:subject skos:Concept “Metadata harvesting” .
changelog:conceptDelete02 a ch:ConceptDelete ; // A change operation
ch:hasTimeStamp “2017-12-02 15:34:45+5” ;
ch:operator changelog:agent01 ;
ch:subject skos:Concept “Open Archives Initiative” .
changelog:conceptAdd02 a ch:ConceptAdd ; // A change operation
ch:hasTimeStamp “2017-12-02 15:34:46+5” ;
ch:operator changelog:agent01 ;
ch:subject skos:Concept “Open Archives Initiative Protocol for Metadata Harvesting” .
changelog:orderedOperations
ch:hasOrderedOperationList changlog:operationList02.
changelog:operationList02 a ch:OpertionList;
ch:hasContents changelog:conceptDelete01;
ch:hasNext changelog:opertionList03.
changelog:operationList03 a ch:OpertionList;
ch:hasContents changelog:conceptDelete03;
ch:hasNext changelog:opertionList04.
changelog:operationList04 a ch:OpertionList;
ch:hasContents changelog:conceptAdd02;
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ch:hasNext changelog:endOpertionList.
changelog: endOpertionList a ch:EmptyList.
In this example, there are three operations that should be executed in order. An ordered operation
list is defined. The refinement changes in Tennis (2007, p.15) is listed as follows:
Table 3. Change example 3
DC2003 Metadata Thesaurus
(a) Cultural heritage
[no other concepts]
skos:Concept “Cultural heritage”
DC2004 Metadata Thesaurus
(a) Cultural heritage
NT Sekisui-zu
skos:Concept “Sekisui-zu”
skos:Concept “Cultural heritage”
skos:narrower skos:Concept “Sekisui-zu”
The change can be represented as a ConceptAdd and RelationAdd operations. For
the sake of simplicity, the detailed statements are not listed here. However, they are
similar to the examples above.
In the ontology, there are only add and delete operations. A modification
operation can be expressed by one delete and add operations.
DISCUSSION AND CONCLUSION
The goal of this study is to represent KOS changes. Definitions are given to express KOS
changes. In addition, a change set model was proposed along with types of changes. As a result,
an ontology for representing KOS changes was proposed. This study took the examples from
other studies as use cases. Through the examples, it is clear that KOS changes can be expressed
by the proposed approach.
Using this approach, KOS changes are explicitly expressed. The explicitly RDF statements
can be queried by using SPARQL Protocol and RDF Query Language (SPARQL). Moreover,
changes can be separated from the KOS that makes easier to manage KOS and changes.
Formally expressed changes and the separation of changes with KOS make it possible to deal
with KOS changes on the semantic web.
Five groups of stakeholders (i.e., LOD Dataset producer group, vocabulary producer group,
researcher group, web site/tool developer group, and KOS service provider group) of KOS have
been identified (Zeng & Mayr, 2018, p. 5). KOS changes need to propagate not only from
Zou / International Journal of Librarianship, 3(1)
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producer groups to KOS consumers end but within producer groups. For example, a LOD
dataset producer may use more than one KOSs as indicated by Zeng and Mayr (2018). This
study is the first step to connect KOS producer groups to consumer groups. The following steps
including generating change sets and change propagation from KOS sources to applications need
to be investigated. The ultimate goal is to keep KOS current at the application level through
change sets without downloading the full KOS every time.
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About the author
Qing Zou is a digital initiatives librarian at Lakehead University Library, Canada. His research
interests include Linked Data, integrated library systems, digital libraries, and digital archives.