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This paper outlines the advancements made in aligning the Risk Ontology with the Risk Registry. It discusses the need for ontologies to improve risk assessment practices and reduce misunderstandings. The text also covers the evolution of the ontology server, case studies, and future steps for refining the risk ontology.<br>
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Progress on the Risk OntologyComplying with the Risk Registry / Case Studies Nick Bassiliades, Dimitris Vrakas Logic Programming & Intelligent Systems group Dept. of Informatics Aristotle University of Thessaloniki, Greece
Outline • Introduction • Previous ontology version • Risk Registry Schema • New ontology version • Next Steps
Why do we need Ontologies? • All the variables associated with the Risk Assessment Process must be defined in the Risk Ontology(ies) • Inputs / Outputs to 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, etc) • To enable reasoning in a higher level of abstraction (general rules that apply to a group of specific cases)
IRIS Risk Glossary + Case Studies Schema The Ontology Server Case Studies
Outline • Introduction • Previous ontology version • Risk Registry Schema • New ontology version • Next Steps
Previous OntologyObject Properties Relating Riskto Other Concepts
Outline • Introduction • Previous ontology version • Risk Registry Schema • New ontology version • Next Steps
Risk Registry Schema • Different variables / chara-cteristics / attributes of Risk • Properties of class Risk • Different types of Risk • Subclasses of class Risk • Spatio-temporal information for the triggering of a risk occurrence • Explanation on the values that attributes of Risk can take • Determine ranges of properties
Risk Registry Data (1/2) • Case study administrative information • Each line of the table is a different instance/object of the corresponding risk class • Although currently content is just simple text, they have been modeled as objects to capture future deployment of fine-grained domain-specific ontologies • Risk Identification Methodology suggests two more properties: probability and value • Another risk property • Plural suggests 1-to-many relationship … • …but actually risk relationship to factor is 1-to-1 • Multiple Risk instances for each alternative factor • Currently 1-to-1 relationship • Needs to map to fine-grained domain-specificontologies ?? • Needs to be represented as a workflow??
Risk Registry Data (2/2) • There are no examples • Assumed simple text • There are no examples, therefore ideas from previous ontology have been used • A separate object, because it may hold internal properties (distribution, value) • Use of the same name implies a single object with two properties (description, value) • Although singular is used, sample data suggest multiple impacts • However, NOT 1-to-many relationship … • … but several 1-to-1 relationships with risk (multiple instances)
Outline • Introduction • Previous ontology version • Risk Registry Schema • New ontology version • Next Steps
New ontology versionClass Hierarchy Risk Properties • Abstract classes for inheritance purposes • value • hasProbability • Types of Impact • Hierarchy slightly changed from previous Administrative Information • Types of Risk • Previous types dropped
New ontology versionRiskVariables (Factor, Component, Mechanism and Impact)
New ontology versionCreatingOntology Instances from Registry • 4 impacts • Thus 4 instances 1 factor 1 mechanism 3 components
Outline • Introduction • Previous ontology version • Risk Registry Schema • New ontology version • Next Steps
Next StepsRiskOntology Refinement • Work with engineers to improve risk ontology • Follow advancements of case studies • E.g. Impact of one risk may lead to occurrence of another risk • Chained risks (need to be modeled?) • E.g. Maintain groups of risks with similar factors/impacts?
Next StepsHarmonize with Domain Ontologies • Integrate fine-grained domain ontologies • explore how risk variables can break down to more detailed structured descriptions (and not just text) • interrelate risk variables to each other through process workflow (mechanism) • Also, harmonize with integration (DSS) ontologies
Next StepsOntology Population & Querying • Currently data from risk registries have been encoded manually (proof-of-concept) • Suggestion: automate in the future? • Link ontology to a risk registry database (??) • Risk insertion/retrieval in/from database will be enhanced with ontology reasoning capabilities • Suggestion: Build a knowledge portal (??) • Better dissemination of case studies • Better exploitationofthe ontology • Risk Knowledge Management
Thank you! • New Ontology can be found at: http://lpis.csd.auth.gr/ontologies/2010/iris.owl • Previous Ontology can be found at: http://lpis.csd.auth.gr/ontologies/2009/iris.owl