Semantics in E-Government

1. Semantics in E-Government Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

2. Dimensions of Interoperability & Integration Our interest lies here Community Enterprise 6 Levels of Interoperability System Semantic Application Syntactic Component Structural Object Data 3 Kinds of Integration 0% 100% Interoperability Scale

3. The Smart Data Enterprise Developer's Perspective on Data: To the application developer, the data evolution timeline is viewed through the correlation of programming paradigms with the relation of data and code. From: Designing the Smart-Data Enterprise, Get prepared for the 10 ways that semantic computing will impact enterprise IT, by Michael C. Daconta, Posted November 28, 2003, Enterprise Architect Magazine.

4. The Smart Data Enterprise This Figure show. The Smart Data Continuum: Data has progressed through four stages of increasing intelligence. (Reprinted with permission from The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management [John Wiley & Sons, 2003]. From: Designing the Smart-Data Enterprise, Get prepared for the 10 ways that semantic computing will impact enterprise IT, by Michael C. Daconta, Posted November 28, 2003, Enterprise Architect Magazine.

5. Semantic web • “an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” • Two features: machine readable; ontology basis • Ontology • In theory - specification of a conceptualization • In practical - a description of some domain knowledge. • Web service • Reusable computational resources

6. Semantic web services • Semantic web technologies applied to web services. • Combine flexibility, reusability, and universal access of WSs with the power of semantic markup and reasoning • A promising infrastructure for next generation e-Government services • Addressing integration and interoperability

7. Why Semantic Web Technologies: Making a Case for the Government- • Goals Semantic Interoperability and Better Information Sharing • More Effective Information Management • More Intelligent Search • Smarter Decision-Making

8. BUSINESS CONTEXT Subject Area Super Type BUSINESS DATA FLOW Information Exchange Package DATA ELEMENT Data Object Data Property Data Representation The Current DRM Model • A model for discovery of information: • Context and classification. • To determine available packages and elements. • A model for exchange of information: • Information packages, built from common data elements. • Sharing mechanism. • A model for representation of information: • Data elements defined in standard way. ISO 11179

9. Expanding the DRM Model MetaMatrix Model DRM Model • MetaMatrix vision: • Generic classification to tag metadata with context: • vs. 2-level context. • Packages built from complex datatypes and deployable for exchange or data access: • vs. exchange-only packaging of ISO 11179 data elements. • Formal datatype model: • vs. more conceptual ISO 11179 model. • Formal reference information to add semantic value to data definitions: • vs. nothing. CLASSIFICATION BUSINESS CONTEXT Subject Area Context Category Super Type PACKAGE BUSINESS DATA FLOW Virtual Database Exchange Package Info Exch Package INSTANCE Virtual Transform Physical TYPE DATA ELEMENT Schema/Association Complex Datatype Data Object ISO 11179 Abstract Datatype Data Property Simple Datatype Data Representation REFERENCE Glossary Thesaurus Bibliography

10. eGovernment Drivers

11. eGovernment Drivers

12. eGovernment Drivers

13. (1) Tree of Knowledge Technologies Content Management Languages Semantic Technology Languages Process Knowledge Languages AI Knowledge Representation Software Modeling Languages Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

14. (1) The Semantic Technology “Layer Cake” Source: Dieter Fensel Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

15. Semantic Technologies and Web Services Semantic Web Services Enterprise Ontology and Web Services Registry Dynamic Resources Semantic Web Services Web Services Static Resources WWW Semantic Web Interoperable Syntax Interoperable Semantics Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

16. Taxonomy Goals for enterprise taxonomies Regardless of end goals, look to a future where taxonomies interoperate (domains connect) Expect new stakeholders to take an interest… … but have their own viewpoints Technology Recommendation: RDF(S) From Tim Berners-Lee, ISWC 2003 Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

17. OR animal sheep horse animal ewe ram mare stallion sheep horse swaledale cheviot dales pony arabian horse What is a Taxonomy? • A taxonomy is a model of knowledge organized as a hierarchical arrangement (tree structure) of concepts: • parent nodes denote more general ideas than their children. [A] [B] Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

18. holy place building shrine Office-block cinema pub church synagogue mosque Types of Taxonomy • A taxonomy can be: • A classification hierarchy, eg: Natural Taxonomy: • Unique Beginner (plant) -> Life-Form (bush) -> Generic (rose) -> Specific (hybrid tea) -> Varietal (Peace) • A part hierarchy (Meronomy) • A category hierarchy • Taxonomies can intersect – intersection means there are different relationships at work: Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

19. Taxonomy Development Framework:A five-step method for taxonomy development 1 2 3 4 5 Focus • What is the taxonomy for? • What business challenges will it overcome? • What results will it achieve? • How to measure stakeholder benefit? Analysis • What is the context for the taxonomy? • What are the types & sources of knowledge? • How does knowledge map to processes? Design • What types of taxonomy concepts are needed? • What to do first? • What system capabilities are needed? • What will be the impact? • Is the taxonomy design correct, complete and consistent? Construct • Have we enough content mapped? • How to connect taxonomies to content? • How to integrate with IT systems? Deploy • How do we ensure there will be feedback for assessment? • Have we accomplished set objectives? • What should be done next? Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt

20. RDF and Ontology Components Key Ontology Components RDF* Triple Components depiction *The company* **sells batteries**. Image knows Person birthdate: date Gender: char Predicate** Object published Subject* Resource Predicate** works for Literal is-A leads * Resource Description Framework Leader Organization =URI =Literal Source: The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management, Wiley Technology Publishing, June 2003. =Property or Association Reference: http://ontolog.cim3.net/file/resource/presentation/Harmonizing_Semantics_in_eGovernment--BrandNiemann_20040422.ppt