1. Copyright 2008, The MITRE Corporation Dr. Leo Obrst MITRE Information Semantics Group Information Discovery & Understanding Dept. Command & Control Center Lobrst@mitre.org Identity Management: The Ontology Perspective Expedition Workshop on Exploring Identity Management NIST Interoperability Week April 30, 2008 NIST, Gaithersburg, MD

2. Copyright 2008, The MITRE Corporation Agenda Ontologies Identity Management & Issues Ontologies and Identity Management Conclusion 2

3. Copyright 2008, The MITRE Corporation 3 Tightness of Coupling & Semantic Explicitness Implicit, TIGHT Explicit, Loose Local Far 1 System: Small Set of Developers Systems of Systems Enterprise Community Internet Looseness of Coupling Semantics Explicitness Data Application Same Process Space Same CPU Same OS Same Programming Language Same Local Area Network Same Wide Area Network Client-Server Same Intranet Compiling Linking Agent Programming Web Services: SOAP Distributed Systems OOP Applets, Java Semantic Brokers Middleware Web Peer-to-peer N-Tier Architecture From Synchronous Interaction to Asynchronous Communication Performance = k / Integration_Flexibility Same Address Space Same DBMS Federated DBs Data Warehouses Data Marts Workflow Ontologies Semantic Mappings XML, XML Schema Conceptual Models RDF/S, OWL Web Services: UDDI, WSDL OWL-S Proof, Rules, Modal Policies: SWRL, FOL+ Enterprise Ontologies EAI SOA EA EA Ontologies EA Brokers

4. Copyright 2008, The MITRE Corporation Ontology Elephants There is no single real elephant There must be an upper elephant An elephant is abstract An elephant is very abstract There must be a purpose for an elephant: use cases? An elephant is really very simple An elephant is the result of consensus Open vs. Closed Elephant There are only distributed elephants & their mappings

5. Copyright 2008, The MITRE Corporation 5 Ontology Spectrum: One View 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 Schemas, 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 From less to more expressive

6. Copyright 2008, The MITRE Corporation 6 Ontology Spectrum: Application Logical Theory Thesaurus Taxonomy Conceptual Model Expressivity Categorization, Simple Search & Navigation, Simple Indexing Synonyms, Enhanced Search (Improved Recall) & Navigation, Cross Indexing Application Enterprise Modeling (system, service, data), Question-Answering (Improved Precision), Querying, SW Services Real World Domain Modeling, Semantic Search (using concepts, properties, relations, rules), Machine Interpretability (M2M, M2H semantic interoperability), Automated Reasoning, SW Services Ontology weak strong Concept (referent category) based Term - based More Expressive Semantic Models Enable More Complex Applications

7. Copyright 2008, The MITRE Corporation Identity Management 1 Who is that Person? What is that Thing? Where did that Person or Thing go? When did it occur? How do we know these facts? Are they facts? How do we get better information? Are these two persons, things the same? 7

8. Copyright 2008, The MITRE Corporation Identity Management 2 Identity, Ambiguity, Semantic Precision: –What constitutes identity? –What are the necessary properties of a thing? –How do you semantically disambiguate? Make things more precise? Reference, co-reference: –What’s knowledge? –What’s evidence that could become knowledge? –How do we determine the difference? –What do we do with what we know? Don’t know? Let’s put our ducks in a row 8

9. Copyright 2008, The MITRE Corporation A man went into the 7-11. He walked up the bread aisle to the front counter. There was another man, waiting there. That man placed a five dollar bill on the counter. The clerk was behind the counter stocking the cigarettes. The first man coughed, and when the clerk turned around, the man motioned him over. The clerk looked at the man. The man who had coughed had a gun in his hand. The other man grabbed his money back. John shot him Example from Text: Tracking 3 people: Indefinite, definite nouns, pronouns, names 9 The same situation applies to structured data!

10. Copyright 2008, The MITRE Corporation Mainstream Information Technology cannot deal with these issues SOA, database technology, programming cannot address Ontologies can address these issues –Formal ontological analysis: –Theory of Parts –Theory of Wholes –Theory of Essence and Identity –Theory of Dependence –Theory of Qualities –Theory of Composition and Constitution 10

11. Copyright 2008, The MITRE Corporation Ontologies Increasingly Used in Federal Government More large-scale efforts taking place in government –COI vocabularies and ontologies to support information sharing –Air Force CIO Enterprise Vocabulary Team: develop coherent processes, procedures, education, modeling in OWL Example: Intelligence Community –Realizes this is a large problem –Is strongly addressing problems of ambiguity, coreference –For people, can’t count on names! –Everyone tries to use names like object identifiers: you can’t do that! –Need to know about things too: material, organizations, systems, cargo, components, logistics, events, times, locations, features, relationships, attributes, qualities, etc. 11

12. Copyright 2008, The MITRE Corporation 12 Conclusion Identity Management & Ontologies need each other Thanks!

13. Copyright 2008, The MITRE Corporation 13 Backup

14. Copyright 2008, The MITRE Corporation 14 Axioms, Inference Rules, Theorems, Theory Theory Theorems (1) Theorems are licensed by a valid proof using inference rules such as Modus Ponens (3) Possible other theorems (as yet unproven) Axioms (2) Theorems proven to be true can be added back in, to be acted on subsequently like axioms by inference rules (4) Ever expanding theory

15. Copyright 2008, The MITRE Corporation 15 Ontology Representation Levels Meta-Level to Object-Level Language Ontology (General) Knowledge Base (Particular)

16. Copyright 2008, The MITRE Corporation Data Layer Ontology Instance Repository Layer Ontology Layer Ontology Application Services Layer Application Services Layer User Interface Services Layer Semantic Representation Requirements User (& presentation) Requirements Support for User to Representation Requirements SearchTransact User Roles QueryTransactNavigate Make/Get AliasLook-upContextualizeInfer Manage Integrity DevelopInfer Semantic Representation Storage Requirements Hypothesize Store/PersistTimestampVersionIndex Data Storage Requirements Store/PersistTimestampVersionIndex Decide Infer Ontology Architecture