Enable Semantic Interoperability for Decision Support and Risk Management Presented by Dr. David Li Key Contributors: Dr. Ruixin Yang and Dr. John Qu

Values for Semantic Interoperability Improves Heterogeneous Data and Information Management for Decision Support, e.g. Fire Risk Management, etc. Improves Interoperability and Information Exchange What the data/information are intended to mean How they are intended to be used Solve “stovepipe” system integration problem Support common operational picture Support Service-Oriented Architecture (SOA)

George Mason Wildfire Risk Assessment Framework (Semantic Interoperability Is A Key)

Semantic Interoperability Spectrum weak semantics strong semantics Is Disjoint Subclass of with transitivity property Modal Logic Logical Theory Thesaurus Has Narrower Meaning Than Taxonomy Is Sub-Classification of Conceptual Model Is Subclass of DB Schema, XML Schema UML First Order Logic Relational Model, XML ER Extended ER Description Logic DAML+OIL, OWL RDF/S XTM Syntactic Interoperability Structural Interoperability Semantic Interoperability

Semantic Interoperability Spectrum A taxonomy is a way of classifying or categorizing a set of things—specifically, a classification in the form of a hierarchy. A hierarchy is simply a treelike structure. Like a tree, it has a root and branches. Each branching point is called a node. In a taxonomy, the semantics of the relationship between a parent and a child node is relatively underspecified or ill defined. In some cases, the relationship is the subclass of relation; in others, it is the part of relation. In still others, it is simply undefined. A thesaurus is a controlled vocabulary arranged in a known order and structured so that equivalence, homographic, hierarchical, and associative relationships among terms are displayed clearly and identified by standardized relationship indicators. The primary purposes of a thesaurus are to facilitate retrieval of documents and to achieve consistency in the indexing of written or otherwise recorded documents and other items. These relationships can be categorized four ways: Equivalence, Homographic, Hierarchical, Associative. Database models: the relational language (R), the Entity-Relational language and model (ER), and the Extended Entity-Relational model (EER). Object-Oriented models, Unified Modeling Language (UML). An ontology defines the common words and concepts (meanings) used to describe and represent an area of knowledge, and so standardizes the meanings. Ontology include computer usable definitions of basic concepts in the domain and the relationships among them. They encode knowledge in a domain and also knowledge that spans domains. Logical Theories are built on axioms (a range of primitive to complex statements asserted to be true) and inference rules (rules that, given premises/assumptions, provide valid conclusions), which together are used to prove theorems about the domain represented by the ontology-as-logical-theory. The whole set of axioms, inference rules, and theorems together constitute the logical theory.

Semantic Technology Stack/Tree Syntax: Data Structure Semantics Higher Semantics Reasoning/Proof XML XML Schema RDF/RDF Schema OWL Inference Engine Trust Security/Identity Use, Intent Pragmatic Web Intelligent Domain Services, Applications Agents, Brokers, Policies Grid & Semantic Grid Services

OMB Federal Enterprise Architecture (FEA) & Data Reference Model (DRM) FEA DRM Framework: Business Context (Categorization of Data) Data Element/Entity Model (Structure of Data) Information Exchange Model (Exchange of Data)

Semantic Interoperability to Support Service-Oriented Architecture

A Key Enabling Technology for Semantic Interoperability: OWL-S OWL-S has three main components: the service profile for advertising and discovering services; the process model, which gives a detailed description of a service’s operation; and the grounding, which provides details on how to interoperate with a service With OWL-S markup of services, the knowledge necessary for service discovery could be specified as computer interpretable semantic markup, and a service broker or registry as well as ontology enhanced search engine could be used to locate the services matching with the service request. In addition, a service provider could proactively advertise itself in OWL-S with a service broker or a service registry so that requesters can find the services it provides.

An OWL-S Markup Example for Semantic Interoperability

Questions?