Ontology Building and its Application using Hozo

Come to JAPAN for ISWC2016@KOBE!
Tutorial in JIST2014,
Chiang Mai, Thailand, Nov. 9th 2014
Ontology Building and
its Application using Hozo
Kouji KOZAKI
The Institute of Scientific and Industrial Research (I.S.I.R),
Osaka University, Japan
Slides
http://goo.gl/28ck8p
or http://www.hozo.jp/
Tutorial@JIST2014
2014 Nov.9 1

Agenda
 9:00-10:30
 ① How to build ontologies using Hozo
(with hands-on)
 Basic usage of Hozo.
 Basic theories of ontological engineering in Hozo.
(10:30-10:50 Coffee Break)
 10:50-12:00
 ② Some characteristic functions of Hozo
 Dynamic generation of is-a hierarchies
 Ontology Exploration
 ③ Developments of ontology-based application
 An overview of application developments
 Some example applications
2014 Nov.9 Tutorial@JIST2014 2

Self introduction: Kouji KOZAKI
 Brief biography
 2002 Received Ph.D. from Graduate School of Engineering, Osaka
University.
 2002- Assistant Professor, 2008- Associate Professor in ISIR, Osaka
University.
 Specialty
 Ontological Engineering
 Main research topics
 Fundamental theories of ontological engineering

Ontological topics
 Some examples of topics which I work on
 Role theory
 What’s ontological difference among the following concepts?
 Person
 Teacher
 Walker
 Murderer
 Mother
…. Natural type (Basic Concept)
Role (dependent concept)
 Definition of disease
 What’s “disease” ?
 What’s “causal chain” ?
 Is it a object or process ?
2014 Nov.9 Tutorial@JIST2014
4

Self introduction: Kouji KOZAKI
 Brief biography
 2002 Received Ph.D. from Graduate School of Engineering, Osaka University.
 2002- Assistant Professor, 2008- Associate Professor in ISIR, Osaka University.
 Specialty
 Ontological Engineering
 Main research topics
 Fundamental theories of ontological engineering
 Ontology development tool based on the ontological theories
 Ontology development in several domains and ontology-based application
 Hozo(法造) -an environment for ontology building/using- (1996- )
 A software to support ontology（=法） building（=造） and use
 It’s available at http://www.hozo.jp as a free software
 Registered Users：4,600+ (June 2014)
 Java API for application development (HozoCore) is provided.
 Support formats: Original format, RDF(S), OWL.
 Linked Data publishing support is coming soon.

My history on Ontology Building
 2002-2007 Nano technology ontology
 Supported by NEDO(New Energy and Industrial Technology Development Organization)
 2006- Clinical Medical ontology
 Supported by Ministry of Health, Labour and Welfare, Japan
 Cooperated with: Graduate School of Medicine, The University of Tokyo.
 2007-2009 Sustainable Science ontology
 Cooperated with: Research Institute for Sustainability Science, Osaka Univ.
 2007-2010 IBMD(Integrated Bio Medical Database)
 Supported by MEXT through "Integrated Database Project".
 Cooperated with: Tokyo Medical and Dental University, Graduate School of Medicine, Osaka U.
 2008-2012 Protein Experiment Protocol ontology
 Cooperated with: Institute for Protein Research, Osaka Univ.
 2008-2010 Bio Fuel ontology
 Supported by the Ministry of Environment, Japan.
 2009-2012 Disaster Risk ontology
 Cooperated with: NIED (National Research Institute for Earth Science and Disaster Prevention)
 2012- Bio mimetic ontology
JIST2014（Nov.11）
 Supported by JSPS KAKENHI Grant-in-Aid for Scientific Research on Innovative Areas
 2012- Ontology of User Action on Web
 Cooperated with: Consumer first Corp.
 2013- Information Literacy ontology
 Supported by JSPS KAKENHI
JIST2014（Nov.11）

① How to build ontologies using
Hozo
 What is ontology?
 Basic usage of Hozo
 Representation of an ontology
 Basic operation of Hozo
 Basic theories of ontological engineering in
Hozo
 Some tips for ontology buliding
 Role theory

What is an ontology?
 What is an ontology?
[Mizoguchi 03] Tutorial on ontological engineering - Part 1: Introduction to Ontological
Engineering New Generation Computing, OhmSha&Springer, Vol.21, No.4, pp.365-384, 2003
 In philosophy, it means theory of existence.
 From AI point of view,
“explicit specification of conceptualization”
[Gruber 93].
 From knowledge-based systems point of view,
“a theory(system) of concepts/vocabulary used as building
blocks of an information processing system”
[Mizoguchi 95].
 A basic role of an ontology
 It clarifies “how target world are understood” and provides
vocabulary and rules to consistent modeling
8

A compositional definition
of ontology
9
 An ontology consists of concepts, hierarchical (is-a)
organization of them, relations among them (in addition
to is-a and part-of), axioms to formalize the definitions and
relations. .
 Content of Ontology
 “Concept” represented entity in target domain
 “Relationship” between concepts
 Definition of a Concept
 Label（，Description）
 Super/Sub concept
 Part concept
 Attribute
 Axiom
bicycle
physical
object
saddle
handle
front wheel
is-a relation
Whole-part relation
attribute-of relation
entity
size：26×2.3
color： red
gear: 24 steps
・”front wheel” in
conjunction with “handle”
・”front wheel” ≠ “rear wheel”
Other relation
agent functional
occurrent
event

Ontology
Manager
Architecture of Hozo
Ontology Server
Management System
Language
Clients
(other agents)
Ontology
Model
Reference / Install
Tracking
Pane
support
building （modifying） browsing
Onto Studio
(a guide system for
ontology design)
Ontology/Model
Developer
Dependency
Management
Ontology
Editor
Information
of changes
Ontology language of Hozo: XML-based frame language.
It can be exported in OWL , and RDF(S). It also can import OWL partially.

How to get Hozo
 Download
 Hozo is available as a free software at
http://www.hozo.jp .
 Install
 Extract the downloaded ZIP file.
 You need Java Runtime Environment (JRE).
 If it is not installed (that is, you couldn’t run the Hozo
tool), please download and install it from
http://www.java.com/en/download/ .

How to run Hozo
1. You can run Hozo-ontology editor by clicking “oe5.bat” or
“oe5.exe” (for Windows) or “oe5.script” (for Mac OS) in
the extracted folder.
2. When you run the tool, a window for initial settings is
shown. Please input “user name” (arbitrary name) and
press “OK” button.
These settings are
required when you want
to manage your ontology
using project manager.
12

How to open/create an ontology
After a main window of Hozo-Ontology Editor is shown.
Select “File” menu
-> “open File” for open an existing ontology
or -> “new File” for creating a new ontology
“File” menu
“new File” “open File”
*You can also use these button.
13

Hozo-Ontology Editor
:Editing Screen(without project manager)
Browsing Pane
for visualizing / editing an ontology
Navigation Pane
for navigating/searching
concepts in the ontology
Definition Pane
for editing definition of
concepts in the ontology
14

An overview of
ontology representation in Hozo
Node represents
a concept
(=rdfs:Class)
Is‐a link represents
an is‐a relation
(=rdfs:subClassOf)
Role concept
(≒property name )
cardinality
(=owl:card
inality) Class restriction
p/o slot represents
a part‐of relation
(=rdf:Property)
Role holder
(see the latter)
a/o slot represents an
attribute‐of relation
(=rdf:Property)
represents class of
its player
(=owl:allValuesFrom )
Link between slots
represents a relation
between parts/attributes
(=some axiom )
15

Ontology representation (1)
is-a hierarchy
 Node represents a concept
 Is-a link represents is-a relation (sub-class-of)
 e.g. bike is-a two-wheeled vehicle
→bike is a specialized concept of two-wheeled vehicle (lower concept)
→two-wheeled vehicle is a generalized concept of bike (upper concept)
Is-a relationships represent
a hierarchical organization of concepts (is-a hierarchy).
upper
concepts
When a node is clicked,
its upper/lower concepts
are highlighted.
lower
concepts
16

Viewpoints to organize
an is-a hierarchy of ontology
Is-a hierarchy is an important base of an ontology
because it reflects how its target world are understood .
 Ex.1) Only is-a hierarchy  Ex.2） With definitions of concepts
vehicle
－two-wheel-vehicle
－motorbike
－bike
－three-wheel-vehicle
－
…
It is not clear differences of
semantics among concepts
vehicle
－two-wheel-vehicle
→The number of wheel = 2
－motorbike
→power source = engine
－bike
→power source = person
－three-wheel-vehicle
→The number of wheel = 3
－
Their …definitions show clear differences
of semantics among concepts
Definitions of concepts show clearly viewpoints
to organize an is-a hierarchy of ontology.
17

definitions of a concept
 part-of，attribute-of relation
 Slot represents a relationship; p/o：part-of a/o：attribute-of
 It represents definitions of a concept in a machine readable
format.
 Representation of slots
 Role concept name：name of parts/attributes
 Class constraint shows a restriction on which concept (class) can
be the parts/attributes
*It refers other concepts defined in elsewhere.
 Cardinality shows a restrictions on the number of parts/attributes
 n..m →more than n以上and less than m
cardinality
(=owl:card
inality)
p/o slot represents
a part‐of relation
(=rdf:Property)
Role concept
(≒property name )
Class restriction
represents class of
its player
(=owl:allValuesFrom )
18

Characteristics of is-a relation
Inheritance / Specialization
 A lower concept inherits definitions (slots in Hozo) of its upper concepts.
 *Inherited slots are NOT shown on the Browsing pane.
 e.g.) Which slots are inherited from “bike” to “city-cycle” ?
 Inherited slots are sometimes specialized in the lower concepts.
 e.g.) “front-wheel-role” are specialized in “city-cycle”.
 Hozo shows specialized slots in red color.
 When a specialized slot is selected, its upper slots are highlighted.
specialized
Information about
its upper slot
inherits
19

definitions pane (for concept)
 When the user select a concept (node) on the Browsing pane,
Definition pane shows its definitions (slots).
 Super shows the list of upper concepts of the selected concept.
working together
 Inherited slot shows its inherited slots from its upper concepts.
 Documentation shows exploration of it in natural language.
20

A basic way of thinking
for ontology building
 Considering
“what’s in essential (characteristics of concept)”
 Try to be clear
“how target world are understood”
 What are differences among concepts
=to be clear viewpoints to classify (organize) concepts
 What are common characteristics of related concepts

Basic operation (1)
Creating concepts and is-a hierarchy
 Creation of a new concept (node)
 [add Node] Button / Menu
 When a node is selected, new nodes is created as its lower concept .
 Change its concept name (label)
 Select the node and change its label in Definition pane
 Organizing an is-a hierarchy
 Select 2 nodes (upper concept and lower concept) by clicking nodes
with SIFT key
 [add Link] Button / Menu to add is-a link（*please check ”is-a” is
selected in the Link list）
 Created is-a relation are shown as tree in Navigation pane
add Node add Link
Link list (kinds of links)
Tutorial@JIST2014
2014 Nov.9 22

Basic operation (2)
Creating slots(definitions of concepts)
 Creation of a part-of/attribute-of slot
 Select a node and [add Slot](Button/Menu)
 part-of / attribute-of is chosen in the Slot list (kinds of slots)
 Change definitions of a slot
 Select a slot and edit role concept/class constraint/ role
holder them in Definition pane
 *Class constraint
 Undefined concept is shown in 「light yellow」
 You can select it from existing concepts using [Select Class]
Undefined Defined
23

Basic operation (3)
Definitions of a slot
 Definition of a slot
 Kind p/o：part-of a/o：attribute-of
 Role concept name：name of parts/attributes
 Class constraint :a restriction on which concept (class) can be the
parts/attributes
 Choosing from existing concepts(classes)
*”Any” represents the upper concepts of the all concepts
 Data type can be used：Integer, Float, String, Boolean, decimal, date, time
 Cardinality :a restrictions on the number of parts/attributes
Double click
24

Basic operation (4)
Inheritance / Specialization
 Inherited slots are shown by selecting its upper concept
in the upper concept list on definition pane.
 Specialization of a slot
 Choose “specialization…” on the Slot list (kinds of slots) and
[add Slot](Button/Menu)
 Choose a slot to be specialized from list of inherited slots shown on
the new dialog
 Edit definition of the specialized slot
*Please note that definition of
the specialized slot must not be
inconsistent with its uppers slot

Tips for definition of slots
 To be clear difference/commonality among
concepts
 Characteristics common to lower concepts should be defined as slots
of their upper concepts
 To be clear using specialization of slots
 Differences between upper concept and its lower concepts
 Differences between brother concepts (concepts whose upper
concept is the same)
 It tend to be good that an ontology has many specialized
slots (red slot)
 Considering viewpoints for organization are
represented by slots
Concepts are systematized using is-a hierarchy and slots
26

Relationships between slots
 Relationships between slots can be used to represent
more detailed definition of a concept
 e.g.）
In definition of “bike”,
“front-wheel” and
“rear-wheel” must be
“different (instances)”.
 Relationships between slots pre-defined in Hozo
 equal：two numbers are equal
 not-equal： two numbers are different
 larger-than： a number is larger than the other one
 sameAs： must be the same instance
 different： must be different instances
27

Basic operation (4)
Definition of relationship among slots
 Define new relation concept (class)
 “Relation Concept” tab in Browsing pane
 Creating a new concept with slots
 The concept is defined as new “Relation
Concept” and added to [the list of links]
 Add a link among slots
 Select slots by clicking with SHIFT key
 Choose a kind of link and [add Link]
 Check information shown in confirm
dialog and [OK]

What is Role?
John (a person) is a teacher of high school. He got
married five years ago (husband ), and now he is the
father of two children. After school (job) he goes to a
English conversation school (student ).
 How is John conceptualized (recognized) ?
 In any context .............. John is an instance of Person
 In the high school........... John is an instance of Teacher
 In the married couple...... John is an instance of Husband
 In the Family................. John is an instance of Father
 In the English conversation school
..... John is an instance of Student
According to the contexts,
John is recognized as different concepts ( ※→Role).
※

Fundamental scheme of our role model
 Distinction between role concepts and role-holders
“In a school, there are persons who play teacher roles and thereby
becomes teachers”
Role-Holder
Potential Player
Teacher
Teacher
Role Person
playable
Role-Holder
Role Concept
Teacher-1
Teacher
Role-1 John
Context
School
depend on
Class
Instance
Osaka
High School
Context depend on Role Concept playing Role-playing thing
“In Osaka high school, John plays teacher role-1 and thereby
becomes teacher-1”

Fundamental scheme of our role model
 DiCsotnintecxtti on between role concepts and role-holders Potential Player Role Concept
A class of things to be considered as a whole.
A class of things which are able to play
Role concept is defined as a class of concepts
played by something within a context.
It includes entities and relations.
an instance of a role concept .
“In a school, there are persons who play teacher roles and thereby
becomes teachers”
Role-Holder
Potential Player
Teacher
Role Holder
Teacher
Role Person
playable
Player-link Role-Holder
is divided
is divided
Role Concept
Teacher-1
Teacher
Role-1 John
Context
School
depend on
Class
Instance
Osaka
High School
Player
Context depend on playing
Role Concept Role-playing thing
When a person is actually playing a teacher role,
“In Osaka high school, John plays teacher role-1 and thereby
becomes teacher-1”
he/she thereby becomes an individual teacher role-holder

Role Concept, Role Holder, Potential Player
The context which
the role concept
depends on
Role concept
Role holder
Potential Player
(Class Constraint)
Role
concept
Potential Player
(Class Constraint)
Role holder
32

Characteristics of Roles
 Individuals of role concepts
 (a) They cannot exist if individuals of their contexts do
not exist because roles are externally founded[Guarino 92].
 e.g. If Osaka High School does not exist, the instance of the
Teacher role (Teacher role-1) never exists.
 (b) Because roles are dynamic[Masolo 04], the role
concepts have two states: played and un-played.
 (c) A vacancy is conceptualized as an individuals of role
concept which is not played.
 e.g. When John quits the Teacher, the teacher role-1 becomes a
vacancy.
Role-Holder
Teacher-1
Teacher
Role-1 John
Osaka
High School
Role Concept Context depend on playing Role-playing thing

Characteristics of Roles
 Disappearance of individuals of role-holders
 Individuals of role-holders disappear in the cases:
 (1) Its player (an individual of player) disappears.
 e.g. John dies
 (2) Its role (an individual of role concept) disappears.
 e.g. the position of the Teacher which John filled disappears
 (3) Its player (an individual of player) quits playing the role.
 e.g. John quits the Teacher
Role-Holder
×（2） Teacher-1
×（3）
×（1）
Teacher
Role-1 John
Osaka
High School
Role Concept Context depend on playing Role-playing thing

Conceptual Framework of a Role
 An individual of a role-holder is composed of individuals of a role
concept and its player.
 e.g. The individual of Teacher is the composite of individuals of a
teacher role and a person.
2014 Nov.9
Role-Holder
Role Concept Teacher
Subject
Name
Age
Teacher
Role
The length of
employment
Height
Player
Weight
Context
depend on
Person
playable
School
Group A
Only the role
concept has
Group B
Inherited from
its class constraint
Group C
Are NOT referred
by the role concept
Tutorial@JIST2014 35
Definitions (slots) of
role-related concepts

Definitions (slots) of role-related concepts
Group B
Inherited from
*shown with “▼” mark
Group A
Only the role concept has
Group C
Are NOT referred by
the role concept
36

Basic operation (5)
Definitions (slots) of role-related concepts
Create specialized slots
to the role concept
Group B
Inherited from
*shown with “▼” mark
Group A
Create new Slot
to the role concept
Only the role concept has
Group C
Inherited slot from
its class constraint are
shown with “▽” mark
Are NOT referred by
the role concept
37

Tips to define role concept
 To be clear context dependency
 Concepts which can not be defined without contexts
(other concept)
 E.g. Teacher, Student, Husband, front-wheel, …
 Concepts which can be defined independent to others
 E.g. Person, Wheel, Stone, …
 Considering where slots are defined
 Common characteristics independent to contexts
should be defined as slots of basic concepts
 Characteristics dependent to some contexts
should be defined as slots of role concepts

A role holder can play a role
 A role Holder can be referred as a class constraint to
define other role concepts
=A role holder can play a role
e.g.) In a school, director role can be played by
only Teacher (role-holder).
Definition of Teacher role and
Teacher (role-holder)
Referring Teacher (role-holder)
as a class constraint
* [RH] represents it is a role-holder
(this mark is added automatically)
39

② Some characteristic functions
of Hozo

JIST2011
5th Dec.2011, Hangzhou, China
Dynamic Is-a Hierarchy Generation
System based on User's Viewpoint
Kouji Kozaki, Keisuke Hirota, and Riichiro Mizoguchi
The Institute of Scientific and Industrial Research,

Motivation: Is-a Hierarchy in Ontology
 Ontology
 It is designed to provide systematized knowledge and machine readable
vocabularies of domains for Semantic Web applications.
 It clearly represents how the target world is captured by people and
systems.
 Is-a hierarchies in an ontology
entity
abstract physical
 They reflect how the ontology captures
set number object action
the essential conceptual structure of the
target world and form the foundation of ontologies.
 In an ontological theory, an is-a hierarchy should be single-inheritance
because the essential property of things cannot exist in multiple.
 E.g. Imagine that objects, processes, attributes, etc.
 The use of multiple-inheritance for organizing things necessarily blurs
what the essential property of things is.

Motivation: Multi-perspectives issue
 Domain experts often want to understand the
target world from their own domain-specific
viewpoint.
 In some domains, there are many ways to
categorize the same kinds of concepts.
infarction
disease
Disease
disease
stenosis
disease
Understanding
from their own
viewpoints
classification by
the symptom
hyperglucemia
disease
Angina diabetes
Myocardial
infarction Stroke
How diseases are named
 named by the major symptom
 diabetes, angina…
 named by the abnormal object
 heart disease, …
 named by the cause of the disease
 Myocardial infarction, stroke
 named by the specific environment
 Altitude sickness, …
disease
 named by the discoverer
 Grave’s disease…
disease
heart
disease
classification by the
abnormal object
brain
disease
blood
disease
Myocardial Angina diabetes
infarction Stroke
Myocardial Stroke
infarction diabetes Angina
Several is-a hierarchies of diseases
according to their viewpoints
One is-a hierarchy of diseases cannot
cope with such a diversity of viewpoints.

Existing approaches
 Acceptance of multiple ontologies
based on the different perspectives
 Multiple-inheritance, Ontology mapping
Problem
 If we define every possible is-a hierarchy
using multiple-inheritances or ontology
mapping, they would be very verbose and
the user’s viewpoints would become implicit.
 Exclusion of the multi-perspective
nature of domains from ontologies
 The OBO Foundry
 A guideline for ontology development stating
that we should build only one ontology in
each domain.
Multiple-inheritance
heart
disease
infarction
disease
Myocardial
infarction
Ontology mapping
infarction
disease
disease
stenosis
disease
hyperglycemia
disease
Angina diabetes
Myocardial
infarction Stroke
disease
heart
disease
brain
disease
blood
disease
Myocardial Angina diabetes
infarction Stroke

Our approach
Multi-perspective issue
Understanding based on User's Viewpoint
from their own
viewpoints
Generation of
is-a hierarchies
Ontology Viewpoints
Disease
We take a user-centric
approach based on
ontological viewpoint
management.
Use single-inheritance

Our approach: Dynamic is-a Hierarchy
Generation according to User’s Viewpoint
infarction
disease
disease
stenosis
disease
classification by
the symptom
hyperglycemia
disease
Angina diabetes Myocardial
infarction Stroke
perspective A
「focus on symptoms」
abnormal state
infarction stenosis hyperglycemia
parts of human body
heart brain blood
various is-a hierarchies
based on individual perspectives
disease
heart
disease
classification by the
abnormal object
brain
disease
blood
disease
Myocardial Stroke diabetes
infarction Angina
perspective B
「focus on abnormal objects」
(2) Reorganizing some
conceptual structures from
the ontology on the fly as
visualizations to cope with
various viewpoints.
disease
Myocardial Stroke
infarction diabetes Angina
(1) Fixing the conceptual structure of an
ontology using single-inheritance based
on ontological theories

Our approach: Dynamic is-a Hierarchy
Generation according to User’s Viewpoint
Multi-perspective issue
Understanding based on User's Viewpoint
from their own
viewpoints
Generation of
is-a hierarchies
Ontology Viewpoints
Disease
We take a user-centric
approach based on
ontological viewpoint
management.
Use single-inheritance
We propose a framework for dynamic is-a hierarchy generation
according to the interests of the user and implement the framework as an
extended function of “Hozo-our ontology development tool”.

Framework for
Dynamic is-a Hierarchy Generation
The same conceptual structure
48
Reorganization
Transcriptional
hierarchy
Transcription of a base
hierarchical stricture
X Target concept
Original
is-a hierarchy
X
A
Aspect
Is-a hierarchy
Definition of the
target concept
Base hierarchy
Generated is-a hierarchy
A
P-is-a hierarchy
A
Generated
is-a hierarchy
refer to
Viewpoint
It generates is-a hierarchies by reorganizing the conceptual structures of
the target concepts selected by a user according to the user’s viewpoint.

p-is-a hierarchy
Inheritance: a special case
is-a
p-X = a generic concept
representing all parts of X
↓
Any part of X is-a p-X
Parts of heart
p-is-a hierarchy
p-heart
p-heart
valve wall
p-artrium
p-pulmonary
part-of

Application of Dynamic Is-a
Generation to a Medical Ontology
The original is-a hierarchy of “disease” The generated is-a hierarchy
We applied dynamic is-a hierarchy generation
system to a medical ontology which we are
developing in a project supported by Japanese
government.

DEMO
 Dynamic is-a Hierarchy Generation

ESWC2011
30th May 2011, Heraklion, Greece
Understanding an Ontology
through Divergent Exploration
Kouji Kozaki, Takeru Hirota, and Riichiro Mizoguchi
The Institute of Scientific and Industrial Research,

A method to obtain meaningful
combinations using ontology exploration
They can use the maps as
viewpoints (combinations) to
get data from multiple DBs.
They explore the ontology
according to their viewpoint
and generate conceptual
maps as the result.
These maps represent
understanding from the their
own viewpoints.
An ontology presents an
explicit essential understanding
of the target world.
It provides a base knowledge
to be shared among the users.
53

(Divergent)
Ontology exploration tool
1) Exploration of multi‐perspective conceptual chains
2) Visualizations of conceptual chains
Exploration of an ontology
“Hozo” – Ontology Editor
Visualizations as
conceptual maps from
different view points
Multi-perspective conceptual chains
represent the explorer’s understanding of
ontology from the specific viewpoint. Conceptual maps

Referring to
another concept
Node represents
a concept
(=rdfs:Class)
slot represents
a relationship
(=rdf:Property)
Is-a (sub-class-of)
relationshp
55

Option settings for
exploration
Selected relationships Kinds of aspects
are traced and shown as
links in conceptual map
property
names
constriction
tracing classes
Aspect dialog
Conceptual map visualizer
57

58
Explore the focused
(selected) path.

Functions for ontology exploration
Manual exploration
 Exploration using the aspect dialog:
 Divergent exploration from one concept using the aspect
dialog for each step
 Search path:
Machine exploration
 Exploration of paths from stating point and ending points.
 The tool allows users to post-hoc editing for extracting
only interesting portions of the map.
 Change view:
 The tool has a function to highlight specified paths of
conceptual chains on the generated map according to given
viewpoints.
 Comparison of maps:
 The system can compare generated maps and show the
common conceptual chains both of the maps.
59

Ending point (1)
Selecting of ending points
Ending point (3)
Search Path
Finding all possible
paths from stating
point to ending points
Starting point
Ending point (2)
60

Search Path
Selected ending points
61

What does the result mean?
Selected ending points
Problem
Possible combination of them
Kinds of method to solve the problem
62

DEMO

③ Developments of
ontology-based application
 An overview of application developments.
 Using Hozo Core (Hozo-API)
 Using Exported ontologies in RDF/OWL formats
 Using Hozo Core
 Hozo OAT（Ontology Application Toolkit）
 Dynamic is-a generation
 Disease Ontology (Disease Chain) Editor
 Using RDF export
 Disease Ontology (Disease Chain) Viewer
 Ontology Explorer –LOD version-
 Using OWL export
 Abnormal State Ontology Search System

Hozo Core / Hozo OAT
 Hozo Core
 Java API for ontologies developed using Hozo
 Hozo OAT（Ontology Application Toolkit）
 GUI library to develop ontology-based applications using
Hozo ontologies and Hozo Core
 Java client version
 provides basic GUIs to develop Java client applications using Hozo
ontologies
 Web system version
 provides basic GUI modules to develop web-based applications
using Hozo ontologies

Hozo OAT-Java client version-GUI(1)
Is-a hierarchy
browsing
Visualizing
Definitions of
a concept
Selecting a concept
from is-a hierarchy

Hozo OAT-Java client version-GUI(2)
Search for an ontology
(Simple version)
Search for an ontology
(Detailed version)

法造OAT-Web版-
http://hozoviewer.ei.sanken.osaka-u.ac.jp/HozoWebXML/

Dynamic is-a generation developed
using Hozo Core and OAT
Viewpoint setting dialog
Is-a hierarchy viewer
Hozo OAT
Hozo OAT
Dynamic is-a hierarchy generation module
HozoCore
Hozo ontology OWL ontology
Hozo-ontology editor
We implemented a prototype of dynamic is-a hierarchy generation
system as an extended function of Hozo and a web-service.
It supports ontologies in OWL or Hozo format.

Disease Ontology (Disease Chain)
Editor
Is-a hierarchy
of disease
Visual editor for
definition of disease
(causal chain in the
disease)
Definition of disease
in the ontology

Applications using exported ontologies
in RDF/OWL formats
 Ontology export function of Hozo
 It is important for interoperability of developed ontologies
 Because Hozo ontologies has different semantics with
RDF(S) / OWL, we provides several kinds of export
formats.
 Exporting formats
 (simple) RDF : for publishing an ontology as LOD (coming soon!)
 OWL[A] : simple version → Considering new version
 OWL[B] : middle version → Considering new version using OWL2
 OWL[C] : detailed version → will be integrated to new OWL[B]
 Case studies
 Publishing a disease ontology in Linked Data
 Developing some web system using the exported ontologies

JIST2013，Nov. 29, 2013,
Seoul，Korea
Publishing a Disease Ontologies
as Linked Data
Kouji Kozaki*1, Yuki Yamagata*1, Takeshi Imai*2,
Kazuhiko Ohe*3 and Riichiro Mizoguchi*4
*1Osaka University *2The University of Tokyo Hospital
*3The University of Tokyo
*4Japan Advanced Institute of Science and Technology

Motivation
 Publishing Linked （Open） Data
 Publishing open data as linked data is a significant trend.
 One feature of linked data is the instance-centric approach,
which assumes that considerable linked instances can result in
valuable knowledge.
 Ontology
 In the context of linked data, ontologies offer a common
vocabulary and schema for RDF graphs.
 However, from an ontological engineering viewpoint, some
ontologies offer systematized knowledge, developed under
close cooperation between domain experts and ontology
engineers.
 Such ontologies could be a valuable knowledge base for
advanced information systems even if it doesn’t have instances.

Research Goal
 Publishing ontologies as Linked Data
 An ontology in RDF formats such as OWL, RDFS, SKOS
etc. can be published as it is as linked data
 OWL is not always convenient to use other
applications because of the complicated graph
structures.
 RDFS and SKOS does not support enough semantics
for some ontologies.
 Research goal
 To consider appropriate methods and RDF model to
publish an ontology as Linked Open Data（LOD）for
facilitating efficient use of it.
 As a case study, we focus on a disease ontology which
are developed in our Japanese Medical Ontology project.

A Framework for System Development
based on the Medial Ontology
 Applications based on the medical ontology
 Developed as Additional Functions of “Hozo”
 Dynamic generations of Is-a
hierarchies[Kozaki 11]
 Exporting ontologies in other
formats (e.g. OWL)
→Exported ontologies are used
in other systems
 Developed using “Hozo-API”
 Client based systems
Disease chain
editing tool
 Disease chain editing tool
 Causal chain exploration tool
 Anatomical Connection exploration tool
 Web based systems
 Ontology viewer on Web
 Medical knowledge navigator [Kou 10]
 Disease chain LOD:
Publishing the disease ontology as Linked Open Data
Causal chain
exploration tool
Medical knowledge
navigator

Kinds of causal chain
in the disease ontology
Definition of Disease：A disease is a dependent continuant constituted of
one or more causal chains of (abnormal) states appearing in a human body.
The kinds oｆ causal chain in the disease ontology
・General Disease Chains are all possible causal chains of (abnormal) states in a
human body. They are referred to by all disease definitions.
・Core Causal Chain is a causal chain that is shown in all patients of the disease.
・Derived Causal Chains of a disease are causal chains obtained by tracing general
disease chains upstream (imply possible causes) or downstream (imply possible
symptoms) from the core causal chain.
General Disease Chains
Tutorial@JIST2014
…
…
…
Derived
Causal Chains
… …
Sub-classes of a disease
are defined by extending
ranges focusing …
causal
chains
Core Causal Chain
Causal
relation
Abnormal state
2014 Nov.9 76

An example of causal chain
constituted diabetes.
…
Diabetes‐related
Blindness
loss of sight
…
Legends
possible causes and effects
Elevated level
of glucose in
the blood
…
Abnormal state (nodes)
Causal Relationship
Core causal chain of a disease
(each color represents a disease)
… … …
Type I diabetes
Destruction of
pancreatic
beta cells
Lack of insulin I
in the blood
Long-term steroid
treatment
Is-a relation between diseases
using chain-inclusion relationship
between core causal chains
Steroid diabetes
Diabetes
…
…
…
Deficiency
of insulin
…
…
77

Defining core causal chains
/derived causal chains
Clinicians described definitions of disease using a visual
editing tool for causal chains of diseases.
The core causal chain
of the disease which
are currently selected
＝They are not included in the
definition (core causal chain) of
the disease but
typically observed in its patients.
Causal chains inherited from upper
class of the selected disease
Derived Causal
Chains
Ex) Definition of
“angina pectoris（狭心症）”
78

Defining general disease chains
It is obviously difficult to define all general causal chains in
advance, because it is impossible to know all possible states in
the human body and the causal relation-ships among them.
We define the general disease chains by generalizing
core/derived causal chains defined by clinicians in
bottom-up approach.
The kinds oｆ causal chain in the disease ontology
・General Disease Chains are all possible causal chains of (abnormal) states in a
human body. They are referred to by all disease definitions.
・Core Causal Chain is a causal chain that is shown in all patients of the disease.
・Derived Causal Chains of a disease are causal chains obtained by tracing general
We can get general disease chains that represent all
causal chains in which clinicians are interested when
they consider all defined diseases.
disease chains upstream (imply possible causes) or downstream (imply possible
symptoms) from the core causal chain.
We can get not only derived causal chains, defined by the
clinician directly, but also causal chains, derived by tracing
the general disease chains through all clinical areas.
．．．．
79

Current state of the disease
ontology (2013/03/11)
Clinical Area The number of
Abnormal states
The number of
Diseases
Allergy and Rheumatoid 1,195 87
Cardiovascular Medicine 3,052 546
Diabetes and Metabolic Diseases 1,989 445
Orthopedic Surgery 1,883 198
Nephrology and Endocrinology 1,706 198
Neurology 2,960 396
Digestive Medicine 1,125 233
Respiratory Medicine 1,739 788
Ophthalmology 1,306 561
Hematology and Oncology 354 415
Dermatology 908 1,086
Pediatrics 2,334 879
Otorhinolaryngology 1,118 470
Total 21,669 6,302

Visualization and exploration of
general causal chains
From 13 medical divisions
All 21,000 abnormal states
can be visualized with
possible causal relationships

Implementing the Disease Ontology
Core Causal
Chain
Disease
Derived
Causal Chain
Abnormal
state
Kinds of
causal chain
Core chain
Core chain
Derived chain
Kinds of
causal chain
Kinds of
causal chain
82
Causal
relationship
Causal
relationship
Abnorma
l state
Abnormal
state
We developed the disease
ontology using Hozo.
A disease are represented
by combination of
abnormal states with
causal relationships and
kinds of chain.

Purpose to publish ontology as
Linked Data
 Purpose to publish ontology as Linked Data
 To provide common vocabulary and schema for
instances (RDF graphs)
 To define semantics for reasoning
 To use systematized knowledge base (knowledge
infrastructure)
 Ontology representation language
 RDFS: simple schema language for ontologies which do
not have many complicated class definitions.
 SKOS: data model for sharing a common vocabulary
such as thesauri, taxonomies etc.
 OWL: many semantics to represent detailed class
definitions (for reasoning)

coronary_
stenosis
hasCause
owl:allValuesFrom
owl:onProperty
rdfs:subClassOf
owl:Restriction
rdfs:type
Abnormal
_State
rdfs:subClassOf
owl:onProperty hasResult
myocardial
_ischemia
rdfs:subClassOf
Blank nodes
owl:allValuesFrom
chest_pain
rdfs:type
OWL representation of
a general causal chain
Abnormal state Causal relation
coronary
stenosis
myocardial
ischemia chest pain
SPARQL to get a cause of “myocardial ischemia”
PREFIX dont: <http://www.hozo.jp/ontology/DiseaseOntology#>
select ?o
where { dont:myocardial_ischemia rdfs:subClassOf ?e
?e owl:allValuesFrom ?o
?e owl:onProperty dont:hasCause
?e rdf:type owl:Restriction }
This query is
not intuitive.

OWL representation of
a definition of disease
An example of OWL representation of a definition of disease
coronary
stenosis
myocardial
ischemia
chest pain
Derived
causal chain
Core causal
chain
When we want to get a
definition of disease, we
need more complicated
SPARQL queries.
We designed an original RDF model to publish the disease
ontology as linked data, because we thought a simple RDF
model was more efficient than a complicated OWL model.

RDF data model for
the Disease Chain LOD
 We extracted information
about causal chains of
diseases from the disease
ontology and concerted
them into RDF formats
as a linked data.
 All classes in the ontology
also are represented as
instances (RDF resources)
for convenience of
queries.
 We designed the RDF model so
that the users can obtain
necessary information about
disease chains through simple
SPARQL more intuitively than OWL
representation.
Core causal chain
of “Disease A”
Abnormal
State 1
Derived Causal Chain
of “Disease A”
Abnormal
State 2
Abnormal
State 3
Abnormal
State 4
Legends
Abnormal
State 5
Abnormal
state
Causal
relationships
Abnormal
State 6
Derived Causal Chain
of “Disease B”
Core causal chain of “Disease B”

A comparison of SPARQL queries
 Ex) A SPARQL queries to get a cause of “myocardial ischemia”
In the case of OWL representation
PREFIX dont: <http://www.hozo.jp/ontology/DiseaseOntology#>
select ?o
where {dont:myocardial_ischemia rdfs:subClassOf ?e
?e owl:allValuesFrom ?o
?e owl:onProperty dont:hasCause
?e rdf:type owl:Restriction }
In the case of the proposed model
PREFIX dont:
<http://www.hozo.jp/ontology/DiseaseOntology#>
select ?o
where {dont: myocardial_ischemia dont:hasCause ?o }
coronary
stenosis
myocardial
ischemia chest pain
Abnormal
_State
rdfs:subClassOf
coronary
stenosis
To get a all cause of “myocardial ischemia”
where {dont: myocardial_ischemia dont:hasCause* ?o }
coronary_
stenosis
coronary_
stenosis
hasCause
hasCause
owl:allValuesFrom
owl:onProperty
rdfs:subClassOf
myocardial
_ischemia
myocardial
_ischemia owl:Restriction
Restriction
rdfs:type
rdfs:type
owl:onProperty hasResult
rdfs:subClassOf
owl:allValuesFrom
chest_pain
hasResult
hasResult
myocardial
ischemia
chest pain
hasCause
hasCause

Example queries
to get abnormal states
 (a1) Get all abnormal states.
select ?abn
where { ?abn rdf:type dont:Abnormal_State }
 (a2) Get all cause of abnormal state <abn_id>.
select ?o
where {<abn_id> dont:hasCause* ?o }
 (a3) Get general disease chain which includes
abnormal state <abn_id>.
select ?o
where { {<abn_id> dont:hasCause* ?o}
UNION
{<abn_id> dont:hasPosibleCause* ?o} }
* “dont:” represents a prefix of the Disease Chain LOD
**<abn_id> represents id of a selected abnormal state.

Example queries
to get definitions of disease(1)
 (d1) Get all disease.
select ?dis
where {?dis rdf:type dont:Disease}
 (d2) Get all super diseases of disease <dis_id>.
select ?o
where {<dis_id> dont:subDiseaseOf* ?o }
 (d3) Get core causal chains of disease <dis_id>.
select ?o
where {<dis_id> dont:hasCoreState ?o}
 (d4) Get core derived chains of disease <dis_id>.
select ?o
where {<dis_id> dont:hasDerivedState ?o}

Example queries
to get definitions of disease(2)
 (d5) Get all causal chains which appear in definitions of
disease <dis_id> as a list of abnormal state.
select ?o
where { <dis_id> dont:subDiseaseOf* ?dis .
←(d2)Get all super disease
←(d3)Get core causal chain
←(d4)Get derived causal chain
{?dis dont:hasCoreState ?o }
UNION{?dis dont:hasDerivedState ?o}}
 (d6) Get all causal chains which appear in definitions of
disease <dis_id> as list of causal relationships.
select DISTINCT ?abn1 ?p ?abn2
where { <dis_id> dont:subDiseaseOf* ?dis .
?abn1 ?p ?abn2 .
{?dis dont:hasCoreState ?abn1}
UNION {?dis dont:hasDerivedState ?abn1}
{?dis dont:hasCoreState ?abn2}
UNION {?dis dont:hasDerivedState ?abn2}}

Current state of
the Disease Chain LOD
 Summary of the dataset
 We extracted definitions of 2,103 diseases and
13,910 abnormal states in six major clinical areas from
the disease ontology (on May 11, 2013) and published
as the Disease Chain LOD.
 The dataset contained 71,573 triples.
 System for the Disease Chain
 SPARQL endpoint
 A supporting function to help beginners input queries
 A simple visualization of RDF graphs
 Disease Chain LOD Viewer
 Search function by name of disease/abnormal state
 Visualization of disease chain
The web site http://lodc.med-ontology.jp/

SPARQL Endpoint
(c)The user can also browse
connected triples by clicking
rectangles that represent the objects.
(a)The user can make simple
SPARQL queries by selecting a
property and an object from lists.
(b) When the user selects a resource
shown as a query result, triples
connected the resource are visualized.

The Disease Chain Viewer
Causal chains of a disease selected form the
class hierarchy or search results are visualized.
The system collect all information needed for visualizing the
selected disease chain through SPARQL queries.
And, the result is shown within seconds.
This system works on PCs, tablets and smart phones which
support HTML5.

Prototype application with
Linking to other LOD
•When the user browses a disease chain, it obtains related information about the
selected disease and abnormal state form two other web services.
•One is DBpedia (Japanese /English). The other is BodyParts3D
(http://lifesciencedb.jp/bp3d/) which provide 3D images of anatomies.

Demo:
the Disease Chain Viewer
 The demo system are available at
 http://lodc.med-ontology.jp/

Generalization of the approach for
publishing ontology as LOD
 Ontology Explorer –LOD version-
 To design a simple RDF format to use ontology exploration
 Development of web applications using an
exported ontology in OWL
 A case study -Abnormal State Ontology Search System

Ontology Explorer –LOD version-
Developed using a simple RDF
exported from Hozo
Show related Info.
on DBpedia and Wikipedia
Show the selected path
Explore next paths
See. Presentation JIST2014 main conference
Session 5A: Search and Querying [Nov.11th]

Abnormal State Ontology
Search System
Is-a hierarchy
browsing
Search concepts Definition of the selected concept
in the ontology
Developed using an OWL ontology (simple version)
exported from Hozo

Concluding remarks
 Summary
 How to build ontologies using Hozo
 Basic usage of Hozo.
 Basic theories of ontological engineering in Hozo.
 Some characteristic functions of Hozo
 Developments of ontology-based application using
 An overview of application developments
 Future plan
 We are developing new version of Hozo focusing;
 Interoperability with Linked (Open) Data technologies such as
RDF/OWL2 exprorts, SPARQL …
 Development of ontology-based applications
 The latest version with RDF/OWL2 export will be published
SOON

Acknowledgements
 A part of this work was supported by JSPS KAKENHI Grant
Numbers 24120002 and 22240011.
 A part of research on medical ontology is supported by the
Ministry of Health, Labor and Welfare, Japan, through its
“Research and development of medical knowledge base
databases for medical information systems” and by the
Japan Society for the Promotion of Science (JSPS) through
its “Funding Program for World-Leading Innovative R&D on
Science and Technology (FIRST Program)”.
 I’m also grateful to all collaborator of each study.

Acknowledgement
Thank you for your attention!
2014 Nov.9
Hozo Support Site：
http://www.hozo.jp/
Contact:
kozaki@ei.sanken.oaka-u.ac.jp
Tutorial@JIST2014 101

Ontology Building and its Application using Hozo

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