The IRIS Risk Knowledge Portal

The IRIS Risk Knowledge Portal http://irisportal.csd.auth.gr GeorgiosMeditskos, Nick Bassiliades Logic Programming & Intelligent Systems group Dept. of Informatics Aristotle University of Thessaloniki, Greece

Outline • Introduction • The Risk Ontology • The Risk Knowledge Portal • Architecture • Functionality • Implementation • Demonstration • Next Steps

The Role of Semantics in IRIS • All the variables associated with the Risk Assessment Process are represented in terms of a Risk Ontology • An upper-level schema that describes terms, relationships and restrictions of risk identification and assessment • It is a formal representation of the IRIS Risk Glossary that is used for defining Risk Case Studies (Risk Identification)

Benefits of Semantics • Formal vocabulary of terms publicly available for use by different organizations • integration of risk assessment practices from different domains • Derivation of implicit/hidden relationships through reasoning • semantic integration and consistency checking using state-of-the-art ontology reasoners • Ability to “link” risk terms with existing semantic descriptions in the Web of Data • building a network of semantically interconnected concepts (Linked Data)

The Role of the Risk Knowledge Portal • To better manage and disseminate the case studies of the risk registry • Simplifies the definition and management of risk knowledge • form-based editing vs. Microsoft Excel worksheets • easier representation of risk relationships • Searching/browsing capabilities based on semantic relationships • To make the underlying risk registry public • A common web reference for risk management • Continuous updating/refinement of risk knowledge • To provide basic social features for the active contribution of users to the risk definition/refinement process • comments, discussions, etc. • Future -> Integrator for Risk Assessment

Ontology Requirements • Should be able to represent all the needed terms, relationships and restrictions of the domain • e.g. case studies, risk cases, risk variables and their relationships • Should be simple • a complex ontology affects reasoning and querying performance • an important requirement in our case since there is a need for online (real-time) reasoning tasks

The Ontology • OWL 2 RL Language • 27 classes • 31 properties • A revision of a previous risk ontology (2010) • modified to meet the requirements of the portal http://irisportal.csd.auth.gr/ontology/iris.owl

Top-level Class Hierarchy

Case Study • There are no subclasses • Properties • acronym • editor • hasRiskCases() • version • versionDate

Risk Case • Properties • appearsInCaseStudy() • code • consistsOf (Risks) () • hasFactors() • hasComponents() • hasMechanisms() • hasImpacts() • editor

Risk • Properties • belongsTo(Risk Case) () • hasComponent() • hasFactor () • hasImpact () • hasMechanism () • rickClass(Category)

Risk Variable • Properties • isVariableOf(Risk) () • with subproperties • isFactorOf • isImpactOf • isComponentOf • isMechanismOf

Category • There are no subclasses • Specific–only instances (owl:oneOf) • It is used in order to define instances relevant to categories

Basic Ontology Restrictions • A Case Study may have zero or more Risk Cases • Each Risk Case belongs to a single Case Study • A Risk Case has one or more Risks • Each Risk belongs to a single Risk Case • A Risk has one or more Risk Variables (Factors, Components, Mechanisms, Impacts) • A Risk Variable may belong to multiple Risks

Architecture • Risk Knowledge Portal • Web application (.NET 4 Web Forms)

Risk Ontology Service • A WSDL Web Service (in JAVA) that supports operations for querying and updating the risk ontology • Front-end • receives SOAP messages from the IRIS Portal • Back-end • it communicates with Sesame (the triple store) and OWLIM Lite (rule-based ontology reasoner)

Overview • User accounts • role-based authentication • Risk Ontology Management • Faceted Browsing/Filtering/Searching • Favorites

User Roles • Three role-based security levels • Users: • limited access • they are allowed to search, browse/navigate the risk ontology • able to comment, share ideas and participate in discussions with other users(not implemented yet) • Knowledge Engineers: • have all the privileges of Users • they are also capable of posting new case studies and risk cases or updating the ones that they have submitted • they are not allowed to modify posts of other users • Administrators: • have all the privileges of Users and Knowledge Engineers • they are also capable of modifying the entire risk ontology • they are responsible for the management of the user accounts (not implemented yet)

Posting New Risks • Two types of post • New Case Studies • New Risk Cases • with their risk variables • In order to post a Risk Case, the Case Study should already exist • each Risk Case must belong to a single Case Study

Faceted Searching/Browsing • Users are able to search and browse • Case Studies • Risk Case • Risk Variable • For each type, different facets/filters may be defined • e.g. give me all the Case Studies that are associated (indirectly) with a specific Risk Variable • A dynamic SPARQL query is generated

Favorites • Users can add Case Studies, Risk Cases, Risks and Risk Variables to their favorites • easy access • keep track of updates and activities

Repository Queries • Dynamically generated SPARQL 1.1 queries based on users activity • searching, filtering, browsing the ontology • Queries are submitted via the Risk Ontology Service to OWLIM • it supports non-trivial inference with tens of millions of statements

Sample SPARQL Query 1 Retrieve all Case Studies SELECT DISTINCT ?ID ?Acronym ?Description ?Editor ?Version ?VersionDate WHERE { ?ID rdf:typeiris:CaseStudy; iris:acronym ?Acronym; iris:description ?Description; iris:version ?Version; iris:versionDate ?VersionDate; iris:editor ?Editor. }

Sample SPARQL Query 2 Retrieve all Case Studies that are related to the “blades deflections” variable SELECT DISTINCT ?CaseStudy ?Acronym ?Description ?Editor ?Version ?VersionDate WHERE { ?CaseStudyrdf:typeiris:CaseStudy; iris:acronym?Acronym; iris:description?Description; iris:version?Version; iris:date?date; iris:versionDate?VersionDate; iris:editor?Editor. ?CaseStudyiris:hasRiskCases ?RiskCase0. ?RiskCase0 iris:hasVariables iris:component622427b2-a64a-4e0a-83e4-83c4b309b618. } variable id

Updates • Currently OWLIM does not support the SPARQL 1.1 UPDATE construct • is used to update the ontology via SPARQL • Will be available in the next release • We use the native OWLIM API for adding and removing triples

Custom Rules • Ability to enhance the reasoning results with custom inferences • OWLIM supports the definition of rules using a triple-based rule language • Both OWL entailments and custom rules are translated into JAVA byte-code

Custom Rule Example Id: AssociateRiskCaseAndComponents x <rdf:type> <iris:RiskCase> x <iris:consistsOf> r r <iris:hasComponent> c ------------------------------- x <iris:hasComponents> c

Summary of Technologies • Portal • ASP.NET 4 Web forms • jQuery (Ajax-based communication) • SQL SERVER 2008 R2 (for the social features) • Risk Ontology Service • JAVA 6 • Sesame (triple store) • OWLIM Lite 4 (reasoner) • SPARQL 1.1 • Apache Tomcat

Risk Assessment Calculation • Portal will become the integrator of various risk assessment tools • The following calculations are required to assess overall risk probability • “summation” of the probability of occurrence of the components • “summation” of the probability of occurrence of risk variables occurrence, i.e. factors, components, mechanisms, and impacts

Risk Assessment • The ontology will evolve in order to “host” data for probabilities and various other numerical data values • Will be re-inserted from older ontology versions • Specialized custom rules will be used to summate the values provided by the users or other tools • Special APIs will be used to communicate with these other tools (e.g. Matlab) • Database will hold past risk assessment cases if needed

More Social Features • User profiles • Comments • Connections among users

The IRIS Risk Knowledge Portal