Data Reference Model Implementation Through Iteration & Testing

1. Data Reference ModelImplementation Through Iteration & Testing ITIT Preliminary Strategy GCN Data to Knowledge Conference October 11, 2005 Mills Davis Managing Director, TopQuadrant, Inc. mdavis@topquadrant.com DRM Implementation Through Iteration and Testing

2. TOPICS • Purpose • Scope of DRM testing • Approach and rationale • Next steps DRM Implementation Through Iteration and Testing

3. Purpose • Establish the readiness of the DRM process for deployment across government: • Clear executable mandate to agencies and departments • Proven education, best practices, and support • Tested capabilities for context, sharing, description, and management • Appropriate tooling and vendor support • Business case for implementation at reasonable cost • Demonstrate value of DRM to public, COIs, agency business lines (programs), agency IT management, OMB (FEA & CPIC), President’s Management Agenda, and for implementing legislative mandates. DRM Implementation Through Iteration and Testing

4. Scope of DRM Testing • Education — understandability of DRM • Information description — data to knowledge • Information sharing — system to system • Information context — accessibility • Management — Legislative, executive, business line, IT, and constituency • Assessment — business value and readiness of DRM • Reporting — progress; findings, conclusions & recommendations DRM Implementation Through Iteration and Testing

5. 1. DRM Education • Purpose — Understandability of the DRM • Scope • Agency educational pilot(s): multi-level, cross-agency, with focus on DRM implementations • Community of Interest & Community of Practice outreach • Industry and educational institution outreach • Educational materials, website, and support • Ongoing feedback and evaluation DRM Implementation Through Iteration and Testing

6. DRM Education Pilot (This data architecture provides the three S’s: Structure, Searchability, and Semantics…) National Infrastructure for Community Statistics Pilot Metamodel Metadata Data Data Stories Model Figures DRM Implementation Through Iteration and Testing

7. DRM Basics DRM Implementation Through Iteration and Testing

8. 2. Information Description • Purpose — Knowledge about data & content • Establish DRM capability to represent and reason over the range of information objects that agencies, COIs, and external entities may share. • Scope • Structured, semi-structured, and unstructured content • Data/content, metadata, models, meta-models, semantic models • Automated, semi-automated, and manual methods of preparing DRM models DRM Implementation Through Iteration and Testing

9. Information Description Relationships and associations Metamodel: Constructs and rules needed for abstraction, generalization, and reasoning. Model: Relationships between data and metadata. Different kinds of modeling enable information integration, process interoperation, and adaptive and autonomous behavior Metadata: Information about the content or data. Metadata identify concepts, attributes, and relationships for machine processing that enable various capabilities. Data: Digital representation of numbers, text, table, graphic, audio, video. Facts or instances for reasoning. Source: Professor Andreas Tolk, August 16, 2005 DRM Implementation Through Iteration and Testing

10. Content and Data • Content is anything written, depicted, filmed, recorded, animated and stored in some media • Digital content is any content whose physical properties can be substituted by computer-processable descriptions (e.g., a CD is a binary description of sound) • Metadata is secondary information about, or added to, the content. DRM Implementation Through Iteration and Testing

11. Knowledge extraction creates metadata that enables concepts and relationships in content to be interpreted by computer. Domain knowledge provides metadata for understanding the meaning of the content from different perspectives. Context of use modeling provides metadata that enables software to organize content to task, interest, or preference. Media resource metadata enables packaging content for presentation across different media. Behavioral knowledge allows the computer to sequence communications, manage dialogs, and orchestrate action. Provenance and rights metadata is key to establishing trust, maintaining security, and enabling commerce. Exchange metadata defines query points, packages,and system resources used for data transfer. Semantic models (semantic-enabled metadata) enables content integration, interoperability, and reasoning over content and data assets. Metadata — making content “smart” DRM Implementation Through Iteration and Testing

12. Semantic models represent meanings, associations, and know-how about the uses of things separately from data and program code. This knowledge representation is called an ontology — a run-time model of information, defined using constructs for: Concepts – classes, things Relationships – properties (object and data) Rules – axioms and constraints Instances of concepts – individuals (data, facts) Like databases ontologies are used by applications at run time (queried and reasoned over). Unlike databases, relationships are first-class constructs. Like object models ontologies describe classes and attributes (properties). Unlike object models, ontologies are set-based and dynamic (can change at run-time). Like business rules they encode rules. Unlike business rules, ontologies organize rules using axioms. Like XML schemas ontologies are native to the web (and are in fact serialized in XML). Unlike XML schemas, ontologies are graphs not trees, and used for reasoning. Semantic Models DRM Implementation Through Iteration and Testing

13. Clinical repositories Geneticknowledge bases Other subdomains SNOMED OMIM … UMLS Biomedical literature MeSH NCBI Taxonomy Model organisms GO Addison's disease, NOS UWDA C0271735 Genome annotations Anatomy Addison's disease C0001403 … 1992 1993 1994 1995 1996 1997 1998 2004 1999 Unified Medical Language System Source: Olivier Bodenreider, National Library of Medicine DRM Implementation Through Iteration and Testing

14. Information Description: Use Cases • Describe different types of sharable information object: • Structured, semi-structured, unstructured data/content • Metadata, models, meta-models, semantic models • Software, database, document, web • Examine manual, semi-automated, and automated methods for creation/collection, registry/discovery, and harmonization of DRM objects. DRM Implementation Through Iteration and Testing

15. 3. Information Sharing • Purpose — Enable system to system information exchange in productive business contexts. • Establish DRM process and DRM-based data services involving a range of information objects in varied use cases addressing business needs. • What matters is information sharing that meets business needs. • Scope • DRM process: collection, registry, harmonization, measurement • DRM-based data services: query point, exchange packet, data points • Business line capabilities that deliver business value and involve DRM-based information sharing DRM Implementation Through Iteration and Testing

16. Collection Registration Harmonization & Standardization Measure DRM Process DRM Implementation Through Iteration and Testing

17. DRM-based Data Services • Test exchanges by type of data sources • Structured data (relational) • Semi-structured and unstructured(“document”) • CRUD operations • Retrieval and Analysis • E.g., each combination of exchange (1 -> 2, 2-> 3, 3 -> 1, etc.) defined. DRM Implementation Through Iteration and Testing

18. Information Sharing: Use Cases • Information sharing to support DRM process • Information sharing to support categories of data service — transactional, analytical, authoring, documents. • Information sharing to exchange metadata, models, metamodels, and semantic models • Information sharing to support exchange of data and content • Information sharing to support E-Gov use cases — G2C, G2B, G2G • Information sharing to support business lines • Information sharing to support COI needs DRM Implementation Through Iteration and Testing

19. 4. Information Context • Purpose — Improve information accessibility • Establish DRM responsiveness to E-Gov Act of 2002 Section 207d requirements for information categorization, accessibility, and interoperability. • Scope — Context continuum includes a spectrum of categorization approaches: • Statistical, linguistic, and semantic technologies • Automated, semi-automated, and manual methods DRM Implementation Through Iteration and Testing

20. Context Continuum Strong Semantics Axiology Some Intelligence, Defense, Security, Health, Science & Business applications share information at these levels Modal Logic Logical Theory First Order Logic Description Logic OWL DRM 1.5 setsthe bar here Semantic Interoperability Conceptual Model UML Increasing Metadata RDF/S Topic Map Structural Interoperability Taxonomy Source: Dr. Leo Obrst, Mitre, Mills Davis, TopQuadrant ER Model DB Schema, XML Schema Thesaurus Syntactic Interoperability Relational Model, XML Many Federal applications do not enable data sharing List Glossary Weak Semantics Controlled Vocabulary Recovery Discovery Intelligence Question Answering Reasoning Increasing Search Capability DRM Implementation Through Iteration and Testing

21. Information Context: Use Cases • Categorize content, web pages, documents, records, data sets, RDBs • Assess manual, semi-automatic, and automatic categorization methods • Validate context (metadata) syntax, structure, and semantics • Gauge cost-effectiveness of different categorization and search methods DRM Implementation Through Iteration and Testing

22. 5. Management • Purpose • Establish that DRM process supports legislative, executive, business line, IT, and constituency-level management requirements. • Scope • Legislative, PMA, and OMB requirements • CPIC integration • Operational EA • Agency business line and IT management line of sight • Budget and performance • Financial management DRM Implementation Through Iteration and Testing

23. Integrating DRM and IT Management DRM Implementation Through Iteration and Testing

24. Management: Use Cases • Legislative, PMA, and OMB requirements • EA evaluation • CPIC • Agency business line and IT management • Budget and performance • Financial management DRM Implementation Through Iteration and Testing

25. 6. Assessment of DRM • Gauge the readiness of the DRM process for deployment across government: • Clear executable mandate to agencies and departments • Proven education, best practices, and support • Tested capabilities for context, sharing, description, and management • Appropriate tooling and vendor support • Business case for implementation at reasonable cost • Assess value of DRM to public, COIs, agency business lines (programs), agency IT management, OMB (FEA & CPIC), President’s Management Agenda, and for implementing legislative mandates. DRM Implementation Through Iteration and Testing

26. 7. ITIT Reporting • Progress — working groups, pilot reviews, and presentations • Education — DRM training materials, evaluations • Agency champions — use cases that promote adoption • Pilot test results — DRM functional & technical efficacy; Problems ID’d, fixed, and lessons learned • Business value — Capabilities benefiting business lines and how DRM supports these • Vendor capabilities — tooling and solutions that take time & cost out of the DRM process • DRM scorecard — gauging readiness for deployment • Recommendations — policy inputs, improvements, next steps DRM Implementation Through Iteration and Testing

27. Next Steps • Call for participation — agency champions • DRM pilot proposals • Management and coordination • Resources and funding DRM Implementation Through Iteration and Testing