© 2010 TASC, Inc. | TASC Proprietary Laura J. Reece, Ph.D. for SOCoP workshop Dec 3, 2010 Standards Activities in Semantics and Ontologies

© 2010 TASC, Inc. | TASC Proprietary 2 If you don't know where you are going, any road will take you there. -Lewis Carroll: Alice’s Adventures in Wonderland, 1865 Courtesy of Disney productions

© 2010 TASC, Inc. | TASC Proprietary Semantics and geospatial standards 3 Major Standards Development Organizations with semantic projects: ISO ISO/IEC OGC Will cover only ISO and ISO/IEC here National projects covered later today OGC projects covered later in a co-presentation

© 2010 TASC, Inc. | TASC Proprietary ISO and ISO/IEC – JTC1 4 International Organization for Standardization (ISO) International Electrotechnical Commission (IEC) ISO has –TC211 (Technical Committee) 211: Geomatics (Geospatial Information Systems) –TC37 (Technical Committee) 37: Terminologies ISO/IEC has JTC1 (Joint Technical Committee) with ISO –SC32 (Standing Committee 32: Data Management and Interchange) –SC38 (Distributed Computing: Web Services, Cloud Computing and Service-Oriented Architecture)

© 2010 TASC, Inc. | TASC Proprietary Scope  Standardization in the field of digital geographic information.  This work aims to establish a structured set of standards for information concerning objects or phenomena that are directly or indirectly associated with a location relative to the Earth.  These standards may specify, for geographic information, methods, tools and services for data management (including definition and description), acquiring, processing, analyzing, accessing, presenting and transferring such data in digital/electronic form between different users, systems and locations.  The work shall link to appropriate standards for information technology and data where possible, and provide a framework for the development of sector-specific applications using geographic data. TC211: Geomatics (Geospatial Information Sys.) 5

© 2010 TASC, Inc. | TASC Proprietary Definition of ontology in the context of TC In the context of ISO/TC 211, an ontology refers to a formal representation of phenomena with an underlying vocabulary including definitions and axioms that make the intended meaning explicit and describe phenomena and their interrelationships that can be used by software applications to support the sharing, reuse, and integration of geographic information with any other information sources within a domain of knowledge as well as between various domains of knowledge. An ontology is represented by classes, relations, properties, attributes, and values. It constitutes a knowledge base that supports reasoning, interpretation, and inference.

© 2010 TASC, Inc. | TASC Proprietary  1) Interoperability across domains;  2) Expose ISO/TC211 standards to other communities that are not aware of the spatial domain;  3) Automatic machine reasoning and inference;  4) From information description to knowledge description;  5) Focus on online access of information and knowledge (as opposed to offline access);  6) Interrelate similar/different concepts (such as different keywords for similar concepts in metadata);  7) Associate (similar/different) concepts between domains Values of ontologies and Semantic Web in the context of ISO/TC 211 7

© 2010 TASC, Inc. | TASC Proprietary  initiated to review the potential and benefit of ontologies and the Semantic Web to reach the objectives of ISO/TC 211 for the interoperability of geographic information.  Two NWIPs have been proposed (Brodeur, CA): –Part 1: a framework for the development of semantics in GI. –Part 2: rules for converting UML models of ISO/TC 211 including the General Feature Model for application schemas into OWL2 Current TC 211 Projects: 8

© 2010 TASC, Inc. | TASC Proprietary Development of top level ontologies which allow ontology mapping between domains Relationships with cross domain vocabularies Joint project with ISO/TC204 related GDF, to derive the road network application schema in an ontology structure Reasoning and inference Spatial operator in ISO19107:2003/ISO :2004, could they be defined and used as part of Semantic Web languages (RDF, RDF-S, and OWL) Semantic operators about the semantic similarity with respect to concepts, definition and use as part of Semantic Web languages (RDF, RDF-S, and OWL) Translation of ISO/TC 211 UML models in a Semantic Web language (ex. OWL) Investigate folksonomies Investigate tools and methodologies for developing ontologies Web services ontology Issues of relevance for ISO/TC 211 9

© 2010 TASC, Inc. | TASC Proprietary  Terminology – ISO19104: Terminology – ISO19135: Procedures for registration of geographic information items – ISO19127: Geodetic codes and parameters – ISO19138: Data quality measures – ISO19146: Cross domain vocabularies  Content description – ISO19109: Rules for application schema – ISO19110: Feature cataloguing methodology – ISO19126: Feature concept dictionaries and registers – ISO19131: Data product specification Related ISO/TC 211 works 10

© 2010 TASC, Inc. | TASC Proprietary  Schemas – ISO19103: Conceptual schema language – ISO19107: Spatial schema – ISO19108: Temporal schema – ISO19115/-2/19: Metadata – ISO19123: Schema for coverage geometry and functions – ISO : Simple feature access - Common architecture  Location-based services – ISO19133: Tracking and navigation – ISO19134: Multimodal routing and navigation – ISO19141: Moving features  Spatial referencing (Coordinate reference systems, geographic identifiers)  Data quality principles  Classification systems  Common format (Encoding) – ISO19118 Encoding (rules) – ISO19136 GML – ISO19139 Metadata – XML Schema implementation Related ISO/TC 211 works 11

© 2010 TASC, Inc. | TASC Proprietary ISO TC 37 12

© 2010 TASC, Inc. | TASC Proprietary JTC1/SC32 Data Management and Interchange 13 WG1 eBusiness WG2 Metadata WG3 DB Languages WG4 SQL Multimedia & Application Pkgs

© 2010 TASC, Inc. | TASC Proprietary Standards for data management within and among local and distributed information systems environments. SC32 provides enabling technologies to promote harmonization [of] data management facilities across sector-specific areas. Specifically, SC32 standards include:  reference models and frameworks for the coordination of existing and emerging standards;  definition of data domains, data types and data structures, and their associated semantics;  languages, services and protocols for persistent storage, concurrent access, concurrent update and interchange of data;  methods, languages, services and protocols to structure, organize and register metadata and other information resources associated with sharing and interoperability, including electronic commerce. SC32 Scope statement: 14

© 2010 TASC, Inc. | TASC Proprietary  Parts 1-6 Metadata registry (MDR)  Common Logic  Parts 1-10, Metamodel Framework for interoperability (MFI) including registration of ontologies; a multipart standard that includes the following parts:  · Part 1: Reference model  · Part 2: Core model (merged with basic mapping from part 4 to become Part 10)  · Part 3: Metamodel for ontology registration  · Part 4: Metamodel for model mapping (split between Parts 10 and 11)  · Part 5: Metamodel for process model registration  · Part 6: Registration procedures  · Part 7: Metamodel for service registration  · Part 8: Metamodel for role and goal registration  · Part 9: On Demand Model Selection (ODMS) [Technical Report]  · Part 10: Core model and basic mapping  · Part 11: Structured model registering (Technical report) WG2 Projects of interest 15

© 2010 TASC, Inc. | TASC Proprietary  Standardization for interoperable Distributed Application Platforms and Services including:  Web Services, [WG1]  Service Oriented Architecture (SOA), [WG2] and  Cloud Computing (Study Group convened 2010) SC38 Scope statement: 16

© 2010 TASC, Inc. | TASC Proprietary  Terms of Reference:  i. Provide a taxonomy, terminology and value proposition for Cloud Computing. ii. Assess the current state of standardization in Cloud Computing within JTC 1 and in other SDOs and consortia beginning with document JTC 1 N iii. Document standardization market/business/user requirements and the challenges to be addressed. iv. Liaise and collaborate with relevant SDOs and consortia related to Cloud Computing. v. Hold open meetings to gather requirements as needed from a wide range of interested organizations. vi. Provide a report of activities and recommendations to SC 38 SC38: Study Group on Cloud Computing (SGCC) 17

© 2010 TASC, Inc. | TASC Proprietary Roadmap for Cloud-Client Interoperation Stds 18 System manuals Data dictionaries Data Integration ISO/IEC E3 XML & related standards Networking Software System Integration Semantics services (SSOA) Complex semantics Interoperability management Data Standards Semantic Web Ontology - MetaModels Interoperability management Terminologies, ontologies Data Management/ Data Administration Internet, WWW Local net Semantic Computing ISO/IEC for RGPS ISO/IEC CloudComputing Cloud “Data Center ” ISO , 19146

© 2010 TASC, Inc. | TASC Proprietary Next

© 2010 TASC, Inc. | TASC Proprietary WG 2 Standards Address Metadata and Semantics Management Continuum 20 limited semantics fuller semantics Concepts and relations expressed in an ontology representation language that provides formal semantics (i.e., specifies logical inferences). Formal Ontology Taxonomy/Thesaurus Terms (possibly with definitions) & relations between terms Glossary Terms associated with definitions (concepts) Conceptual Model Concepts and relations among them in a modeling language ER/UML OWL, Common Logic Increasing semantics expressivity Terms

© 2010 TASC, Inc. | TASC Proprietary Getting the information that we need, when we need it, without afflicting the excellent minds of humans with toil and drudgery The litany for data, information and knowledge:  Too much or too little, irrelevant, not authoritative, out of date  Unknown quality, not trustable, lacks provenance, no certainty measures  Difficult to find, difficult to access, difficult to use  Meaning not clear, relationship to other information not clear  Data creators do not have the same understanding of the data as end users  Recorded data loses much real world meaning, context, relationships  Much of the meaning of data is buried in the processes used to manipulate the data (e.g., in computer code)  Need improvements in efficiency and effectiveness GOALS 21