towards drafting a risk ontology based on the iris risk glossary summer academy sep 1 st – sep 4...

Towards Drafting a Risk Ontology based on the IRIS Risk Glossary

SUMMER ACADEMY

Sep 1st – Sep 4th 2009

Nick Bassiliades, Dimitris Vrakas Logic Programming & Intelligent Systems group

Dept. of InformaticsAristotle University of Thessaloniki

AutomatedDataAcquisition

CBR System

Monitoring Campaign

Sensor System for SHM

MONITORINGDATABASE

EXTERNAL DATA

KNOWLEDGE BASES

HISTORYDATABASE

SOLVER

GLOBAL DECISION SUPPORT

Internet

OPERATION

WEB INTERFACE

OBJECT DATA

Modeling and SimulationSYSTEM

ENGINEERING

LABORATORY TESTING

RISK ASSESSMENT

STANDARDS

LOCAL DECISION SUPPORT

Sensor

Life Cycle Management

Clean Data

SHM DB

Import

Matrix

PlausibilityCheck

RISK INVENTORY

RISK KNOWLEDGE

RISKHISTORY

AutomatedDataAcquisition

CBR System

Monitoring Campaign

Sensor System for SHM

MONITORINGDATABASE

EXTERNAL DATA

KNOWLEDGE BASES

HISTORYDATABASE

SOLVER

GLOBAL DECISION SUPPORT

Internet

OPERATION

WEB INTERFACE

OBJECT DATA

Modeling and SimulationSYSTEM

ENGINEERING

LABORATORY TESTING

RISK ASSESSMENT

STANDARDS

LOCAL DECISION SUPPORT

Sensor

Life Cycle Management

Clean Data

SHM DB

Import

Matrix

PlausibilityCheck

RISK INVENTORY

RISK KNOWLEDGE

RISKHISTORY

RAT

Risk Factors

Risk Risk Assessment Tool

Risk Identification Methodology

Risk Management

Standard

Risk Components

Risk Attributes

RAT

Risk Factor 1

Risk

Risk Assessment Tool

Risk Identification Methodology

Risk Management

Standard

CBR

MBR

Risk Factor 2

Risk Factor 3

Risk Factor n

…

Why do we need Ontologies?• All the variables associated with the Risk Assessment Process

must be defined in the Risk Ontology(ies)– Inputs to RAT– Outputs of RAT– Past cases or Models– Others

• Why?– To facilitate integration of risk assessment practices from different

domains– To eliminate misunderstandings concerning the use of terms– To allow the use of various ways to describe the same term

(synonyms, translations, e.t.c)– To enable the software to reason in a higher level of abstraction

(general rules that apply to a group of specific cases)

AutomatedDataAcquisition

CBR System

Monitoring Campaign

Sensor System for SHM

MONITORINGDATABASE

EXTERNAL DATA

KNOWLEDGE BASES

HISTORYDATABASE

SOLVER

GLOBAL DECISION SUPPORT

Internet

OPERATION

WEB INTERFACE

OBJECT DATA

Modeling and SimulationSYSTEM

ENGINEERING

LABORATORY TESTING

RISK ASSESSMENT

STANDARDS

LOCAL DECISION SUPPORT

Sensor

Life Cycle Management

Clean Data

SHM DB

Import

Matrix

PlausibilityCheck

RISK INVENTORY

RISK KNOWLEDGE

RISKHISTORY

AutomatedDataAcquisition

CBR System

Monitoring Campaign

Sensor System for SHM

MONITORINGDATABASE

EXTERNAL DATA

KNOWLEDGE BASES

HISTORYDATABASE

SOLVER

GLOBAL DECISION SUPPORT

Internet

OPERATION

WEB INTERFACE

OBJECT DATA

Modeling and SimulationSYSTEM

ENGINEERING

LABORATORY TESTING

RISK ASSESSMENT

STANDARDS

LOCAL DECISION SUPPORT

Sensor

Life Cycle Management

Clean Data

SHM DB

Import

Matrix

PlausibilityCheck

RISK INVENTORY

RISK KNOWLEDGE

RISKHISTORY

Ontology ServerOntology ServerOntology ServerOntology Server

Domain Ontologies

….….

Risk Core Ontology

REASONER

INTERFACE

The Ontology ServerOntology ServerOntology ServerOntology ServerOntology Server

Domain Ontologies

….….

Risk Core Ontology

REASONER

INTERFACE

IRISRisk

Glossary

Definition of Risk

• Risk is a function of probability, exposure and vulnerability. – Often, exposure is incorporated in the assessment

of consequences

• Risk can be considered as having two components – the probability that an event will occur and – the impact (or consequence) associated with that event

Class Hierarchy

Object Properties Relating Risk to Other Concepts

Risk Class Properties

Event Properties

Probability Properties

Consequence Properties

Risk Specializations (1/3)

Risk Specializations (2/3)

• There are special cases of risks requiring additional properties– E.g. acceptable risk has an acceptance level

property

Risk Specializations (3/3)

• There are special cases of risks imposing restrictions on properties of general concepts– E.g. individual risk has a consequences for a single

human

Consequence Specializations

Human Consequences

Individual Human Consequences

Multilingual Capabilities (1/2)

• Concepts in ontology are expressed in English• Use of annotation properties (rdfs:label) in

classes for expressing the concept in multiple languages

Multilingual Capabilities (2/2)

• More than one synonym terms can be expressed using multiple rdfs:label entries

Thank you!

• Ontology can be found at:http://lpis.csd.auth.gr/ontologies/iris.owl