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