The document discusses knowledge organization systems (KOS) and how the Simple Knowledge Organization System (SKOS) bridges KOS and the Semantic Web. It provides examples of KOS like taxonomies and thesauruses and explains how they are used differently than ontologies. SKOS is defined as an RDF vocabulary for representing KOS online in a machine-readable way and became a W3C standard in 2009.

1. Knowledge Organization
Systems
Rajendra Akerkar
WNRI, Norway
R. Akerkar 1

2. SKOS
 a model and vocabulary that is used to
y
bridge the world of knowledge
organization systems (KOS) and the
g y ( )
Semantic Web
 understanding SKOS will enhance your
g y
understanding about ontology
R. Akerkar 2

3. KOS
 a set of elements, often structured and
controlled,
controlled that can be used for describing
objects, indexing objects, browsing collections,
etc.
 KOSs are commonly found in cultural heritage
institutions such as libraries and museums.
 They can also be used in other scientific areas,
examples include biology and chemistry,
p gy y
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4. KOS examples
 Taxonomy
◦ referring to the classification of things or
concepts, as well the schemes underlying such
a classification.
 Thesaurus
◦ Thesaurus can be understood as an extension
to taxonomy: allowing subjects to be arranged
in hi
i a hierarchy and in addition, it adds the
h d i ddi i i dd h
ability to allow other statements be made
about the subjects
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5.  They can make search more robust (instead of simple
keywords matching, related words, for example, can
k d t hi l t d d f l
also be considered).
 They can help to build more intelligent browsing
interfaces (following the hierarchical structure, and
explore broader/narrower terms, etc.).
terms etc )
 They can help us to formally organize our knowledge
for a given domain, therefore promote reuse of the
knowledge, and also facilitate data interoperability.
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6.  KOSs are used for knowledge g
organization, whilst ontologies are used
for knowledge representation.
g p
 KOSs are semantically much less rigorous
than ontologies, and no formal reasoning
g , g
can be conducted by just having KOSs.
◦ For example, ontologies can specify a is-a relationship, while in
thesauri, the hierarchical relation can represent anything from is-
a to part-of, depending on the interpretations rooted from the
domain and application.
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7.  The Semantic relation is fairly weak.
 An ontology is a rich expression of semantic
relations
 While a term list, free or controlled, is a natural
arrangement of word forms.
g
BUT there is a kind of semantic relation between
hierarchical li
hi hi l lists and relationship li
d l i hi lists that they
h h
are both considered Subject-based classification
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8.  It is any form of content classification that
y
groups objects b th subjects th are about.
bj t by the bj t they b t
This can take many forms, and is generally
combined with other techniques in order to
create a complete solution.
 Metadata is generally defined as "data about
data," which is of course a very broad definition.
y
 In content management and information
architecture, metadata generally means
"information about objects" ("objects" here used
information objects ( objects
as defined above), that is, information about a
document, an image, a reusable content
module, and so on.
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9.  The relation between subject-based classification and
subject based
metadata is that metadata properties or fields that directly
describe what the objects are about by listing discrete
subjects use a subject-based classification.
j j
 Note that there is a difference between describing the
objects being classified and describing the subjects used
to classify these objects
 Metadata describes objects One of the ways in which it
objects.
does that, is by connecting objects to the subjects they are
about.
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10.  Controlled vocabulary it is a closed list of named
y
subjects, which can be used for classification. In
library science this is sometimes known as an
indexing language. The constituents of a controlled
g g g
vocabulary are usually known as terms.
 At
term i a particular name f a particular concept.
is ti l for ti l t
(This is pretty much the same as the common-sense notion of a
keyword).
 Same concept may have multiple names, and also
that the same term may name multiple concepts
concepts.
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11.  Taxonomy is a subject-based classification that
y j
arranges the terms in the controlled vocabulary into a
hierarchy without doing anything further, though in
real life you will find the term "taxonomy" applied to
y y pp
more complex structures as well.
 Why is Taxonomy f ?
Wh i T for?
The benefit of this approach is that it allows related
terms to be grouped together and categorized in
ways that make it easier to find the correct term to
use whether for searching or to describe an object.
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12.  Taxonomy y helps
p users by
y describing
g the
subjects.
 Metadata only relates objects to subjects,
whereas here we have arranged the subjects in
a hierarchy.
 So a taxonomy describes the subjects being
used for classification, but is not itself metadata;
it can be used in metadata, however.
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13.  In this diagram, the blue lines are the metadata,
g , ,
while the black lines that make up the
taxonomy is part of the subject-based
classification scheme.
Figure. Using the taxonomy in metadata
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14.  The distinction derives from the blue lines being
statements about the paper, but the black line
p p ,
between "topic maps" and "knowledge
representation" is not a statement about the
p p ;
paper; it's a statement about "topic maps". One
p p
consequence of this is that if we have another
paper about "topic maps" we do not need to
repeat that "topic maps"
p p p
belong under "knowledge
representation".
Figure. Using the taxonomy in metadata
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15. A number of important pieces of information about the concepts
are not being captured in the above taxonomy as:
 The fact that "XML Topic Maps" is synonymous with "XTM".
XML Maps XTM .
 The difference between "XTM" and "topic maps". (Many users
use these interchangeably, but they do not mean the same
thing.)
 The fact that "topic navigation maps" is synonymous with "topic
topic maps topic
maps", but should no longer be used.
 The relationship between topic maps and subject-based
classification and topic maps and
the semantic web.
 The relationship between XTM and
XML and HyTM and SGML.
 The similiarity between HyTM and
XTM,
XTM and their difference from TMQL
and TMCL, as well as the similarity
between TMQL and XQuery.
Figure . Using the taxonomy in metadata
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16. Taxonomy as we defined it here cannot handle
these problems, though it should be noted that
many systems referred to as taxonomies to
some extent can, as they extend the basic
model defined here.
Figure 2. Using the taxonomy in metadata
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17.  Taxonomies
In a taxonomy the means for subject description consist of
essentially one relationship: the broader/narrower
relationship used to build the hierarchy. The set of terms
being described is of course open, but the language used to
describe them is closed, since it consists only of a single
y g
relationship.
l ti hi
 Thesauri
Thesauri extend this with the RT and UF/USE relationships,
and the SN property, which allow them to better describe
the terms. A i th l
th t Again the language i closed, since thi i th
is l d i this is the
entire vocabulary at disposal for describing the terms
 Ontology
In fact, thesauri could in theory be considered ontology
where there is only one type called "term" one property
type, "term", property,
called "scope note", and three relationships (BT/NT,
USE/UF, and RT). In practice thesauri are not considered
ontologies because their descriptive power is far too weak,
p
precisely because of this limited vocabulary.
y y
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18. What Is SKOS?
 Simple knowledge organization systems,
p g g y
◦ is an RDF vocabulary for representing KOSs, such as
taxonomies, thesauri, classification schemes, and
subject heading lists.
bj t h di li t
◦ can be published on the Web and they can be
machine readable and exchanged between software
g
applications.
◦ SKOS is developed by W3C Semantic Web
Development W ki Group (SWDWG) and h an
D l Working G d has
official Web site: http://www.w3.org/2004/02/skos/
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19. SKOS
 It has become a W3C standard on 18
August 2009
 Note t at t e URIs in SKOS vocabulary
ote that the U s S OS vocabu a y
all have the following lead strings:
 http://www w3 org/2004/02/skos/core#
http://www.w3.org/2004/02/skos/core#
 By convention, this URI prefix string is
associated with namespace prefix skos:
and is typically used in different
sterilization formats with the prefix skos
skos.
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20. Example
 SKOS Core Constructs
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