Semantic Interoperability Net Centric Perspective Presented to SICo

Semantic Interoperability Net Centric Perspective Presented to SICo. P Team John A. Yanosy Jr. Chair NCOIC SII-WG August 15, 2006 Semantic Interoperability 1

“Many of the problems we have identified can be categorized as “information gaps” – or at least problems with information-related implications, or failures to act decisively because information was sketchy at best. Better information would have been an optimal weapon against Katrina. Information sent to the right people at the right place at the right time. Information moved within agencies, across departments, and between jurisdictions of government as well. Seamlessly. Securely. Efficiently. ” The Final Report of the Select Bipartisan Committee to Investigate the Preparation for and Response to Hurricane Katrina Semantic Interoperability 2

Semantic Interoperability Overview Semantic Interoperability 3

Networking Tension Semantic Interoperability 4

Semantic Interoperability Context Hypothesis- Semantic errors due to mutual misinterpretation cause unintended consequences in system interactions 1 2 System People 3 1 H-H 2 H-S 3 H-W 4 S-S 5 S-W Each has potential for semantic breakdown 4 2 System 5 5 People 3 World Semantic Interoperability 5

Semantic Interoperability Intersection Knowledge Information Actions/Services Goals Communications Context Semantic Interoperability 6

Conceptual Framework of Frameworks Semantic Autonomic Management (? ) Semantic Policy Framework (SWRL? ) Semantic Context Framework (? ) Semantic Information Collaboration Framework (FIPA, ACL) Semantic Framework Content Semantic (OWL, Framework Services Framework (OWL-S) NIEM, (MPEG) Semantic DRM Communication Framework (SOAP) C 2 IEDM) Semantic Interoperability 7

Semantic Frameworks • • • Semantic Net Centric Interoperability Framework – architectural gereral layers and elements enabling mutually consistent interpretation of interactions Semantic Information Framework - layered model defining hierarchical semantic knowledge and structures Semantic Context Framework – situational context model Semantic SOA Framework - layered model web services including Service Discovery Profiles Semantic Metadata, Semantic Service Descriptions, Taxonomic Metadata enabling linking of service dependency relationships, metadata linking service descriptions to domain specific semantic data models, common services supporting capabilities required by all services Command Control Semantic Adaptive Policy Control Framework - semantic framework enabling overall policy constraints on the Semantic Information Framework and the Semantic SOA Framework - provides command control across all layers representing unique constraints by various COIs Semantic Autonomic Management Framework- provides semantic models enabling self management supporting operations (Self Configuration, Self Healing, Self Optimization, Self Security) Semantic Collaboration Framework - Intelligent Agent based Framework that can support adaptive mediation between all of the other frameworks and that provides dynamic collaborative formation of agents Semantic Communication Framework - framework encompassing support for metadata descriptions of message based communications, metadata representation of message content, models relating data elements of messages to Semantic Information Framework semantic data models, models defining semantic intention of message Semantic Media and Content Framework - framework enabling the semantic representation of the nature of the media content type, music, voice, image, etc. in such a way that adaptation can be provided to modify content for end to end and device adapation purposes - many meatdata standards already exist Semantic Interoperability 8

Semantic Interoperability Issues Semantic Interoperability 9

Semantic Incompatibility Issues • COIs, Social, Organizational, Cultural Assumptions and Policies • Domain Knowledge • Ontology Relationships and Harmonization • Logic(s) DL, FOL, Intensional, SWRL • Context Dependency • Semantic Expressibility, • Semantic Web – URI Networking, Discovery • Implementation Technology Semantic Interoperability 10

Varying Semantic Representations Explicit Semantic Web Relevant, Discoverable, Understandable Semantic Knowledge UDDI, Domain, Ontologies C-OWL Context Semantic Knowledge Model & Logic COIN Ontologies, IEEE SUMO Cognitive IFF Organized Hierarchical Classifications Agents, Upper CYC Mediation SWRL OWL-S NCO Domain Vocabulary, Schemas OWL Service & Data RDFS Do. D Tenets XMLschema Taxonomy RDF WSDL Syntax Structure UDDI Dublin Core DOM CYC XML DDMS Foa. F UML TML Untyped Data MIF C 2 IEDM eb. XML Link 16 Wordnet ASCII Context, Upper Ontology Domain Ontology Taxonomies Metadata Semantic Interoperability Across Ontologies X Objects Data Signals Implicit Current Systems Emerging Systems Semantic Interoperability Emerging Networks Net Centric 11

Semantic Interoperability Problems • • Shared Knowledge - Semantic interpretation of shared information between systems and also between systems and people is interpreted by humans in a collaborative manner when designing and developing systems, but typically the results of these collaborative semantic interpretations are not explicitly represented in the solution, rather they are implicit in the solution. This results in possible semantic misinterpretations for different system implementations that are supposed to have a common semantic interpretation of shared information. Situational Context – Without understanding context of a particular user’s situation, the user bears the burden and complexities of discovering and selecting appropriate system capabilities and desired information. In contrast context knowledge defining the relevant information required for a specific situation and perspective can be used to personalize a system’s response more appropriate to the user in a current situation. It also defines the situation and the domain knowledge important to it. Context theory and context aware applications are being developed to enable adaptation of system behavior to a participant’s context. Closed Semantic Network - assumes implicit semantics achieved through human interpreted specifications and related design activities. Systems within closed environments interoperate reasonably well as long as the operating environment, the expected use of the systems, and the system definitions themselves are consistent over time with little change. If any of these conditions are modified than the original semantic interpretations about system functionality, information exchanged, and expected behaviors have to be reevaluated. Open Semantic Network – allows for heterogeneous semantic environment with capability to extend additional semantic definitions. Problems of ontology harmonization, varying levels of expressibility, different models, different intentions and context Semantic Interoperability 12

Semantic Interoperability Errors Occur Everywhere • • • Client –web services interactions (Client interprets <Sell. Stock> as post offer to sell, while web service interprets as sell at any price. ) App – App operations and data exchanges (App. X interprets <Stock> as symbol of stock, while App Y interprets <Stock> as Curr. Price) Use of API interfaces (API labels passed argument for operation as “Stock”, with no semantic definition, object implementing API interprets “Stock” as quantity of items available in inventory. ) Interpretation of Network protocols by network elements (Each NE interprets the protocol message according to the role it has in a Closed World Network and a shared protocol specification – Semantic intent of messages across Closed World Networks require reinterpretation in gateways) App interpretation of database information (Subtle misinterpretation of database meaning by new App results in inconsistent database state due to inappropriate updates by new app e. g. , Healthcare. Provider updates Patient. Status due to diagnostics, while Finance. Administration updates Patient. Status due to Insurance. Constraints. In this case Patient. Status was originally used for health status, not Insurance status. • • • Web services search – UDDI service profiles have no associated schemas or ontologies, resulting in semantic misinterpretation of keyword searches for services Information search – Without taxonomies of knowledge domain profiles searches will rely on data mining algorithms with too many non-relevant results Information integration and merging across apps, systems and databases – Biggest problem of semantic interoperability since multiple specifications and enterprise purposes are involved, as well different syntax information structures and constraints. Exchanged XML documents – only contains simple or complex data element definitions, no relationships between data elements or constraints about when data element instances can be created WSDL web service specifications - no semantics associated with WSDL service definitions, such that applications would have to be written to each WSDl service vocabulary, even when in the same application domain. Semantic Interoperability 13

Closed Solutions (Implicit Semantics) • Closed solutions are characterized by static aspects with implicit semantic interoperation between like systems due to: – explicit semantics defined in the requirements and design stage, – implementations having weak traceability to requirements and design semantics • Results in brittle and complex semantic interoperability specifications not easily modifiable for interoperation with other systems, nor easily evolvable with changing requirements Semantic Interoperability 14

Open Solutions (Explicit Semantics) • • Open solutions are characterized by dynamic aspects that enable explicit semantic interoperation at multiple levels of interaction between different systems due to: – explicit semantics defined and accessible in all phases – sharing of intensional semantic knowledge about context, intentions, actions, capabilities, commitments and environment – simple universal communications speech acts enabling collaboration between systems – separation of semantic concerns and explicit representations of knowledge and system actions or services – ability to extend the universe of explicit knowledge used by systems as new requirements and capabilities are desired – ability to discover, access, and share explicit knowledge in multiple domains (context, capabilities, environment perspective, commitments, …) – ability to dynamically marshal resources to broker semantics Results in extensible and robust interoperability solutions resulting from dynamic integration of disparate systems within a common semantic interoperability framework Semantic Interoperability 15

A Universal Semantic Interoperability Framework Semantic Interoperability 16

Universal Semantic Interoperability Model ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Domain Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 17

Transformation from Implicit to Explicit Semantic Interoperability Full Semantic interoperability is enabled by embedding and sharing explict semantic representations of agent, system and environment goals, context, intentions, actions, available services, domain knowledge, and speech acts Semantic Interoperability 18

Semantic Interoperibility Model • SIOPM = <SM, WFF>, set of semantic models and well formed expressions entailed by each model • SM = <SM 1, …, SMn>, set of semantic models used by agents 1, …, n • SM = <D, G, V, I, L, A, wff>, semantic model tuple D = Domain and individuals in domain G = Grammar defining syntax of well formed expressions, wff V = domain vocabulary for domain I = Interpretation function mapping domain vocabulary terms to domain individuals L = Logic defining rules of reference and entailment for wff A = Axioms predefined in model SM |= wff , wff entailed by Model M, ( |= Entailment operator) Semantic Interoperability 19

Semantic Interoperibility Model • Mutual Semantic Entailment Between Pairs of Agents Ai and Aj – Mi Mj |= wff Mutual Semantic Entailment • Non-Mutual Semantic Entailment Between Pairs of Agents Ai and Aj – Mi Mj • (Mi|= wff) (Mj|= wff) – Mi Mj • Mi Mj | wff Semantic Interoperability 20

Semantic Interoperability Intersection Knowledge Information Actions/Services Goals Communications Context Semantic Interoperability 21

Semantic Interoperability Principles • Interoperability between systems and agents is purposeful and informed by goals, contexts, and shared semantic domain knowledge models (whether explicit or implied). – actual world modifications are achieved through intentional actions. – sharing of semantic environment knowledge provides a ‘situated real world’ perception to enable better decisions about what actions or services are required to achieve goals (mapping of sensed data to perception concepts) • Goals guide selection of intentions and execution of actions • An extensible network of semantic services with explicit semantic representations enables interoperability independent of platforms and technology implementations, and provides a foundation for intentional actions within a purposeful, cognitive interoperable framework • Communications occurs within few universal intentional categories (Speech Acts – request knowledge, commit to action, request action, … ) • Context defines relevant domain knowledge for a specific situation Semantic Interoperability • Useful Knowledge is organized in semantic domain models 22

Cognitive Semantic Interoperability Model ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Domain Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 23

Agent Cognitive Semantic Model Goals (Objectives, Guidance) Context (Situational Knowledge, Constraints) Semantic Knowledge Intensional Logical Reasoning Intentions (Tasks, Workflows, Services) (Decisions, Inferences) Perceptions Communicating Speech Acts Environment Data, Sensors Atomic Actions Communicating Speech Acts Semantic Interoperability World Modifying Actions 24

Implicit Semantic Knowledge Goals Collaboration, Role Never explicitly defined in system, only implicitly by requirements Goals COGNITIVE Context Knowledge Intention Never explicitly defined in system, only implicitly by Perspective, Situation requirements Implicit semantic models by system designer, at most explicit data element Shared Knowledge structure. Usually defined by very few app specific msg types, Committment not universal Request, Context Knowledge Intention REACTIVE Speech Acts Purposeful Communications Typically implemented via app specific protocols, not universal Semantic Interoperability Speech Acts 25

Explicit Services and Universal Speech Acts, No Explicit Semantics ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 26

Explicit Semantic Knowledge, Services, and Speech Acts ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 27

Explicit Context Knowledge ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 28

Explicit Goal Knowledge ENVIRONMENT Collaboration, Role Goals COGNITIVE Intentions, Services Request, Committment REACTIVE Purposeful Communications Speech Acts ENVIRONMENT Semantic Interoperability Knowledge Intentions, Services Reasoning Knowledge Shared Knowledge Context Reasoning World Modifying Actions Reasoning Perception Perspective, Situation Reasoning Context Perception World Modifying Actions Speech Acts ENVIRONMENT 29

NCOIC Integrated Ontology Semantic Interoperability 30

NCOIC Integrated Knowledge Base – An NCOIC Ontology • • Create an integrated NCOIC knowledge Base that can be used by customers and member companies Create an NCOIC ontology that can be constructed from FT and WG ontologies to unify the NCOIC work products – Provide a map of Network Centric Operation aspects – Incorporate NCOIC Lexicon – Capture descriptive knowledge about NCO aspects • Map current NCOIC efforts against NCOIC ontology – To provide a context for research efforts and discussion – To identify shortcomings and candidate areas for research • • • Enable evaluation of Customer Requirements and force initiatives against Net Centric Aspects and NCOIC work products Identify Specify Interoperability patterns, their structural solutions and their relationship to NCOIC work products Enable characterization of each solution using NCO evaluative and descriptive models Create manageable and scalable NCOIC ontology that can evolve Expand to capture and influence Customer requirements specifications Capture the operational space Semantic Interoperability 31

NCOIC SII WG Work Product Knowledge base • Each WG Product has a document and associated Ontology to enable incorporation into a larger model • SII WG Product Concepts – SII Integrated Ontology enable dependent relationships to be made between: • • NCO Tenets, Reference Models, NCO SCOPE Model and its Descriptive Dimensions Interoperability Causes Interoperability Patterns – Focus on Service and Information PFCs Customer Requirements and Capabilities Open Standards Able to be component part of NCOIC Level Integrated Knowledge Base and Ontology Semantic Interoperability 32

Approach Govt and Member Companies, Prod Vendors Tools (Industry, Vendor, Govt. ) NCOIC Integrated KB and Ontologies Customers - ETE Capabilities Architects - Patterns -SCOPE Model - Interop Problems Engineers - PFCs - Profiles Vendors - COTs/Gots FT & WGs Semantic Interoperability 33

NCOIC Product Map (SII WG Perspective) NCOIC Lexicon NCOIC Integrated Ontology Customer Reqts -DAR, CADM, DAP -Do. DAF to DRL -JCIDS -PIM -NCOW RM -Capital Planning -PPBE -Acquisition -BCIDS -Net Ready KPPs -KIPs -DISRonline. Profiles Cust Reqts Ontology IA NCOIC Integrated Knowledge Base Open Standards Ontology Mobility NCAT SII Integrated Ontology Knowledge Base Interoperability Causes Document Interop Ontology NCOIC SCOPE Document SCOPE Ontology SII WG Interoperability Patterns PFCs -Information Exchange, Semantics -Services, Mediation -Msg Content Transformation -Collaboration, Workflow -Discovery, Context Awareness -Autonomicity, Management NCO Tenets Ontology PFC Ontology NCO Interop Pattern Ontology NCO Tenet Ontology Semantic Interoperability 34

Integrated NCOIC Product Map (Proposal) NCOIC Lexicon NCOIC Integrated Ontology Customer Reqts -DAR, CADM, DAP -Do. DAF to DRL -JCIDS -PIM -NCOW RM -Capital Planning -PPBE -Acquisition -BCIDS -Net Ready KPPs -KIPs -DISRonline. Profiles Cust Reqts Ontology NCAT Open Standards Ontology Building Blocks Ontology Interoperability Patterns PFCs -Information Exchange, Semantics -Services, Mediation -Msg Content Transformation -Collaboration, Workflow -Discovery, Context Awareness -Autonomicity, Management IA Interop Ontology Open Standards NCOIC Integrated Knowledge Base Mobility Interoperability Causes Document Building Blocks NCOIC SCOPE Document SCOPE Ontology NCO Tenets Ontology NCO Tenet Ontology Semantic Interoperability PFC Ontology NCO Interop Pattern Ontology Interactions between WGs And FTs not defined here 35

Recommendations • Unify the NCOIC knowledge and products using the NCOIC KB and Ontologies – Align with similar customer efforts in KB – Foundation for collaborative engineering • Establish a group to manage the NCOIC Ontology and KB – Each WG has one focal person for input and vetting – currently being done by SII WG • Training for Semantic Information Capture • Tools and commercial hosting platforms for NCOIC ontology (Infrastructure Recommendation) – Assist NCOIC marketing efforts – Assist engineering efforts – Budget (plan to follow) Semantic Interoperability 36

Emergency Disaster Response Information Coordination Semantics Semantic Interoperability 37

“Many of the problems we have identified can be categorized as “information gaps” – or at least problems with information-related implications, or failures to act decisively because information was sketchy at best. Better information would have been an optimal weapon against Katrina. Information sent to the right people at the right place at the right time. Information moved within agencies, across departments, and between jurisdictions of government as well. Seamlessly. Securely. Efficiently. ” The Final Report of the Select Bipartisan Committee to Investigate the Preparation for and Response to Hurricane Katrina Semantic Interoperability 38

Coordination Problems • Lack of organized information focusing on coordination activities and status: – Resources – Participants – Incident resolution • No Common Operating Picture relating evolving overall coordination situation. • Inability to plan specific coordination activities for different disaster scenarios Semantic Interoperability 39

Information and Communication Problems • • • Focus on data elements rather than model structure and domain Messages only related to each other by message ID; i. e. patterns of coordination not readily apparent Semantic descriptions of data elements in message schemas inadequate No standards used to represent higher levels of semantic expressiveness in data model, e. g. RDF, OWL Architecture does not specify how information sharing takes place among responders in any dynamic or adaptive manner No directory structure exists within DMIS to enable service discovery Semantic Interoperability 40

Project • Research and Development of Emergency Disaster Response Information Coordination Semantic (ED-RICS) framework to improve emergency response coordination • Focus on semantic architectural model that creates common operating picture (COP) of evolving emergency response coordination situation • Represent COP as set of discrete semantic coordination patterns (SCP) derived from XML emergency messages • Ontology based network coordination situation analysis identifying coordination anomalies, completion states, resource commitments, and incident focus problems • Technologies include: – – – EDXL and CAP alert message standards DHS NRP scenarios Protégé 2000 ontology tool with OWL plugin Domain ontologies with non-programmatic concept inferences Web services Concepts from knowledge representation and descriptive logic Semantic Interoperability 41

DHS-NRP Scenario Analysis • • • • Scenario 1: Nuclear Detonation – 10 -Kiloton Improvised Nuclear Device Scenario 2: Biological Attack – Aerosol Anthrax Scenario 3: Biological Disease Outbreak – Pandemic Influenza Scenario 4: Biological Attack – Plague Scenario 5: Chemical Attack – Blister Agent Scenario 6: Chemical Attack – Toxic Industrial Chemicals Scenario 7: Chemical Attack – Nerve Agent Scenario 8: Chemical Attack – Chlorine Tank Explosion Scenario 10: Natural Disaster – Major Hurricane Scenario 11: Radiological Attack – Radiological Dispersal Devices Scenario 12: Explosives Attack – Bombing Using Improvised Explosive Devices Scenario 13: Biological Attack – Food Contamination Scenario 14: Biological Attack – Foreign Animal Disease (Foot and Mouth Disease) Semantic Interoperability 42

Semantic Interoperability 43

Current Emergency Disaster Response Information Interoperability Network Disaster. Management. Interoperability. Services Service(DMIS) Services Emergency. Provider. Access. Directory(EPAD) SOAP, WSDL, HTTP Messages Emergency Data Exchange Language - EDXL Common Alerting Protocol - CAP Data Model National Information Exchange Model (NIEM) Semantic Interoperability 44

Emergency Messaging Languages • CAP: emergency messaging standard used to alert responders and public in general of emergency situations as they occur. • EDXL-RM: messaging standard used to convey information regarding emergency specific resources. • EDXL-DE: emergency messaging standard used as container for CAP and EDXL-RM messages. EDXL-DE may also contain emergency data not otherwise included in CAP or EDXL-RM messages. Semantic Interoperability 45

ED-RICS Capabilities Provides universal shared information analysis through creation of common operating picture (COP) of all coordination activities, including: • Committed resources • Responder locations with respect to incident area • Coordination activity completion status • Anomaly analysis, such as overcommitted resources, etc. • Interactive execution environment between knowledge framework and responders, response managers, messaging systems, databases, and other personnel and systems Semantic Interoperability 46

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Coordination Intersection Information Activities ED-RICS Messages Resources Semantic Interoperability 49

Emergency Disaster Response Services and Information Framework Semantic Web Services Data Models Emergency Situational Information Service New • Plan Management • Status Monitoring • Situation Analysis • Anomalies Identification Semantic Data Model for Emergency Disaster Planning, Monitoring, Analysis EDXL-DE OWL CAP OWL Current EDXL-RM OWL (DMIS) NIEM (EPADS) Emergency Data Exchange Language - EDXL SOAP, WSDL, HTTP Common Alerting Protocol - CAP Semantic Interoperability 50