1. Semantic Interoperability: The What, Why, Who, and How
Brand Niemann, Senior Enterprise Architect, US EPA, and
Co-chair, Federal Semantic Interoperability Community of Practice (SICoP)
Presentation for the 2007 Metatopia Conference, November 5-7, 2007,
Hosted by Data Management Association of the National Capital Region

2. Context
In SICoP's work on a semantic interoperability data management strategy for the community, the focus has shifted from applying it to EPA, which is done, to the broader community:
1. SICoP delivered a semantic interoperability data management strategy to the Best Practices Committee of the Federal CIOC in June.
2. SICoP applied the semantic interoperability data management strategy to the US EPA in July - September as part of its ongoing work with federal agencies and presented this work at several conferences and had it reviewed and accepted by the Metatopia 2007 Committee for publication and use at future conferences.
3. SICoP is now applying the semantic interoperability data management strategy for the Net-Centric Operations Industry Consortium (NCOIC) with its members to selected agencies (e.g. FAA NextGen, Logistics, USCG, DHS, etc. Slides

3. Context
A New Enterprise Data Management Strategy for the US EPA (chapters in online book):
Part 1*: Overview (August 15, 2007)
Part 2*: Inventory of Data Assets (August 29, 2007)
Part 3*: Integration of Data Tables (September 5, 2007)
Part 4: Spatial Data (September 24, 2007)
Part 5: Land Quality and Water Quality Management Segments (September 25, 2007)
* Second presentation.

4. Context
SICoP delivered Three White Papers to the Best Practices Committee of the Federal CIO Council:
1. Introducing Semantic Technologies and the Vision of the Semantic Web ("DRM of the Future") (Translated into Japanese) (February 16, 2005).
2. Semantic Wave Executive Guide to the Business Value of Semantic Technologies (January 6, 2006).
3. Operationalizing the Semantic Web/Semantic Technologies: A roadmap for agencies on how they can take advantage of semantic technologies and begin to develop Semantic Web implementations (June 18, 2007).

5. Context
SICoP is working on updates to each of those three White Papers as follows:
1. Semantic Interoperability Data Management Strategy: Net-Centric Operations Industry Consortium (NCOIC) and Others (September 2007 Draft)
2. Semantic Wave 2008: Industry Roadmap to Web 3.0, Mills Davis, Project 10X (October 2007 Draft).
3. Semantic Interoperability with Relational Databases (e.g. Data marts and Data warehouses): Solving the Schema Mismatch Problem with Ontology, Lucian Russell, Private Consultant (December 2008 Draft).

6. Overview 1. What 2. Why 3. Who 4. How
Note: These are four of the six Journalism 101 questions. My SICoP Co-chair Mills Davis, will cover the other two: Where and When!

7. 1. What
I know that you believe that you understood what you think I said, but I am not sure you realize that what you heard is not what I meant.
Robert McCloskey, State Department spokesman (attributed).

8. 1. What Semantics = Meaning = Relationships ID
Humans (and therefore our machines) only ever understand anything in so far as it is related to other things ID

9. 1. What Semantics = Meaning = Relationships VA NY ID MD
Humans (and therefore our machines) only ever understand anything in so far as it is related to other things VA NY ID MD

10. 1. What Semantics = Meaning = Relationships EGO ID
Humans (and therefore our machines) only ever understand anything in so far as it is related to other things
SUPEREGO
EGO ID
ANALYSIS

11. 1. What Semantics = Meaning = Relationships CARD ID
Humans (and therefore our machines) only ever understand anything in so far as it is related to other things
LICENSE
CARD ID
BADGE

12. 1. What Interoperability:
1. (NATO and DOD) The ability of systems, units, or forces to provide services to and accept services from other systems, units, or forces and to use the services so exchanged to enable them to operate effectively together.
2. (DOD only) The condition achieved among communications-electronics systems or items of communications-electronics equipment when information or services can be exchanged directly and satisfactorily between them and/or their users. The degree of interoperability and its purpose(s) should be defined when referring to interoperability among specific sets of systems, presumably interconnected with each other through a network. See also the LISI model.

13. 1. What
The Levels of Information Systems Interoperability (LISI) model and associated process were developed by MITRE in the late 1990's as a means of assessing the interoperability readiness of a system or set of capabilities. The LISI model is organized into four dimensions: Procedures, Applications, Infrastructure, and Data (PAID), and is no longer used.
The Systems, Capabilities, Operations, Programs and Enterprises (SCOPE) Model for Interoperability Assessment is currently in the final stages of NCOIC of approval among the members of the Technical Council of the organization. Once the consensus on the document has been ratified, the document will be published at this link.

14. 1. What Interoperability (addition by John Yanosy, August 30, 2007):
3. There are many different focus areas of interoperability with their own concerns and approaches for enabling compatible interactions with minimal adjustment, e.g., semantic interoperability, service interoperability, protocol interoperability, physical interoperability, etc. and various combinations such as services with different access protocols that can inhibit compatible interactions comprising successful interoperability.

15. 1. What Semantic interoperability (Recommendation for version 2.0):
The mutually consistent interpretation of shared knowledge between networked entities consistent with a semantic model in a defined context.
Common Lexicon and Acronym Dictionary, Version 1.8.0, April 2005:
The NCOIC Lexicon defines terms and expressions that are relevant to texts published by the NCOIC. This material is offered for dynamic debate, discussion and additional submissions in this online wiki. NCOIC Lexicon Custodian Working Group periodically reviews the wiki, and publishes updates of the condensed catalog, including comments for entries that have been deleted.

16. 1. What DRM 1.0 SICoP Unify DRM 3.0
All Three
Unify
DRM 3.0
Ontologies
Source: Expanding E-Government, Improved Service Delivery for the American People Using Information Technology, December 2005, pp. 2-3.
With annotations by the author.

17. 1. What DRM Version Sound Bite Examples 1.0 Build to Exchange
NEIN (CDX)
NIEM
2.0
Build to Share
LandView 6 (7)
SICoP Pilots
3.0
Build to Reuse
SICoP White Paper 3
EPA Service System

18. 1. What Source: Mills Davis, SICoP Co-Chair:

19. 2. Why
“Today, humanity – or rather the computer industry – dissatisfied with the mere 6,000-odd human languages, has created some 8,000 computer languages. The number of human languages is on the decline, by the way, while the number of computer languages persists in climbing. In a world where everybody claims to want to be able to talk to everybody else, such a multiplicity of languages indicates that there’s definitely a fly in the IT ointment.” Page 75.
Source: Chapter 6: Xplicating XML in “Service Oriented Architecture for Dummies”, Judith Hurwitz, et al., Wiley, 2007, 359 pp.

20. 2. Why
“Oh, and of course, there’s one fact that makes the whole of this set of protocols, languages, and technical gobbledygook (XML) very important. They solve the Babel Problem. This scheme works anywhere for any software written in any program language running on any computer. Insofar as anything can be, it is technology independent.” Page 86.
Source: Chapter 6: Xplicating XML in “Service Oriented Architecture for Dummies”, Judith Hurwitz, et al., Wiley, 2007, 359 pp.

21. 2. Why
Need much more than XML – need RDF and OWL – why created by the W3C – but also need the rich semantics:
SICoP White Paper 3 suggests use of three key tools as trusted reference knowledge sources:
WordNet
Language Computer Corporation
Open Cyc
Also need best-of breed tools like TopBraid Composer to create and reuse (refactor) Ontologies.
Also need Examples which we are providing:
See section 4.

22. 3. Who 3.1 World-Wide Web Consortium Semantic Web Activity
3.2 Open Group Semantic Interoperability WG:
Universal Data Element Framework (UDEF)
3.3 Data Architecture Subcommittee (DAS)
3.4 Intelligence Community Data Management Committee
3.5 NCOIC Semantic Interoperability Framework WG
3.6 DoD Community of Interest
3.7 SICoP

23. 3.1 World-Wide Web Consortium Semantic Web Activity
The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the Resource Description Framework (RDF).

24. 3.1 World-Wide Web Consortium Semantic Web Activity
In February 2004, The World Wide Web Consortium released the Resource Description Framework (RDF) and the OWL Web Ontology Language (OWL) as W3C Recommendations. RDF is used to represent information and to exchange knowledge in the Web. OWL is used to publish and share sets of terms called ontologies, supporting advanced Web search, software agents and knowledge management. You may want to look at the collection of SW Case Studies and Use Cases to see how organizations are using these technologies today.

25. 3.1 World-Wide Web Consortium Semantic Web Activity
Note that RDF has moved into the
XML space and been expanded
with query and rules!

26. 3.1 World-Wide Web Consortium Semantic Web Activity
April 7-8, 2005, Semantic Web Applications for National Security (SWANS) Conference:
DARPA DAML Program and SICoP. Proceedings Available at (Also counted as Third Semantic Technology for E-Government Conference).
June 18-19, 2007, Toward More Transparent Government: Workshop on eGovernment and the Web, United States National Academy of Sciences, Washington DC, USA. Jointly sponsored by the World Wide Web Consortium (W3C) and the Web Science Research Initiative (WSRI). SICoP Position Paper and Session Chair:
October 25-26, 2007, W3C Workshop on RDF Access to Relational Databases, Boston, MA, USA. SICoP Position Paper on Integration of Data Tables:

27. 3.2 Open Group Semantic Interoperability WG
Background and Meetings:
Universal Data Element Framework (UDEF):
Collaborations:
Disaster Response Pilot Demonstrates Web Services and Semantic Naming Technology, Page 32 GSA Newsletter on Disaster Management, March 31, 2006
Convergence of Semantic Naming and Identification Technologies?, Joint Conference, April 27-28, 2006.
SOA Ontology, Collaborative Expedition Workshop, January 23, 2007.

28. 3.2 Open Group Semantic Interoperability WG
February 15, 2006, SICoP Provides Keynotes and Presentations at the Lockheed Martin 11th Annual Information Technology Trends Conference and Gives Special Recognition to Ron Schuldt, Lockheed Martin and Chair of The Open Group UDEF Forum, for the "Disaster Response Pilot Demonstrating Semantic Naming Technology for Web Services". Lockheed Announces New Semantic Technologies Integrated Program Environment (IPE).

29. 3.3 Data Architecture Subcommittee (DAS)
Data Architecture Subcommittee Action Plan
SICoP Activities
Comments
Data Quality Profile
Data Modeling and OWL: Two Ways to Structure Data
See next two slides
DRM 2.0 Implementation Guide
White Paper 3: DRM 3.0 and Web 3.0
Knowledgebases
Person Harmonization, Etc.
Vocabulary Management in Semantic Wikis
See SICoP Special Conferences 1-3

30. 3.3 Data Architecture Subcommittee (DAS)
Data Modeling and OWL: Two Ways to Structure Data, David Hay, Essential Strategies, Inc.:
Objectives of a Data Model:
Capture the semantics of an organization.
Communicate these to the business without requiring technical skills.
Provide an architecture to use as the basis for database design and system design.
Now: Provides the basis for designing Service Oriented Architectures.

31. 3.3 Data Architecture Subcommittee (DAS)
Data Modeling and OWL: Two Ways to Structure Data, David Hay, Essential Strategies, Inc. (continued):
Synopsis:
Both data modeling and ontology languages represent the structure of business data (ontologies).
Data modeling represent data being collected, and filters according to the rules.
Ontology languages represent data being used, with ability to have computer make inferences.
Comment from Lucian Russell (SICoP White Paper 3 Author):
So ontology can improve data quality in legacy systems! David Hay agreed.

32. 3.4 Intelligence Community Data Management Committee
Background and Meetings:
Collaborations:
First: June 25, 2003, Invitation to present "Web Services: The State of the Art in the Federal Government“.
Most Recent: March 7, 2007, SICoP Suggestions to the Intelligence Community Data Management Committee Meeting.

33. 3.5 NCOIC Semantic Interoperability Framework WG
Background and Meetings:
Collaborations:
Incremental knowledgebase from each conference call and meeting:
NCOIC Systems, Capabilities, Operations, Programs, and Enterprises (SCOPE) Model for Interoperability Assessment Knowledgebase Pilot:
Added Semantic Arts “Semantics: A Guide to the Jargon”.

34. 3.5 NCOIC Semantic Interoperability Framework WG

35. 3.6 DoD Community of Interest
Background and Quarterly Meetings:
See next slide.
SICoP Special Briefing, August 9, 2007:
SICoP Overview: Brand Niemann, Co-Chair
SICoP White Paper 1 and GSA Activities: Rick Murphy, GSA
SICoP White Paper 2: Mills Davis, Co-Chair
SICoP White Paper 3: Lucian Russell, Consultant
Framework for Achieving and Managing Interoperability: Denise Bedford, World Bank
Semantic Wiki and New OS/NII Project: Michael Lang
NCIOC Semantic Interoperability WG: Todd Schneider, Raytheon

36. 3.6 DoD Community of Interest

37. 3.6 DoD Community of Interest
SICoP provided a set of briefing slides for the August 9th meeting (Sections 1-4).
SICoP addressed the issues raised in the August 9th briefing by supplementing the slides on August 13th with notes (Section 5).
SICoP had an extensive discussion which the SICoP Co-chairs compiled and distilled in the Summary Points on August 23rd (see next three slides).

38. 3.6 DoD Community of Interest
The leadership of the DoD CoI (Mike Todd) and SICoP (Brand Niemann) worked together on the FEA/OMB DRM The DoD CoI was featured as a best practice for information sharing in a CoI and SICoP led the DRM 2.0 Implementation Through Testing and Iteration Work Group.
The DoD CoI and SICoP continue to interact in the DoD CoI Quarterly Meetings and through those with joint membership like Jim Schoening who leads the SICoP Cross-Domain Semantic Interoperability WG (CDSI WG) that produced a white paper that was discussed in the press and gave rise to the August 9th briefing for Mr. Krieger and his MITRE staff.

39. 3.6 DoD Community of Interest
DoD is using semantic technologies and standards, and the recent DoD CoI Quarterly Meeting on July 31st featured two presentations of that (David Hanz, SRI, and Mary Parmelle, MITRE).
The SICoP members participating in the August 9th briefing came away with a range of impressions of the DoD CoI leadership from (1) DoD and the IC are about years behind where we are and we're pulling away fast, to (2) we need to take the time to understand their use case for semantic technology and focus our discussion on how semantic technology can be used to support their mission. All the SICoP participants came away with the desire to work on how to "get DoD leadership moving in the right direction" at the upcoming NCOIC Plenary and WG Meetings September 17-21st, and the Metatopia Conference, November 5-7th.

40. 3.6 DoD Community of Interest
The SICoP and NCIOC SIF WG activities are about adding value to and reusing the DoD and DoD CoI net-centric information sharing work, not about critcizing, disrupting, or replacing it - we are two communities trying to better understand each other and help one another to achieve a common purpose - semantic interoperability in information sharing.
SICoP would like to see the DoD CoI Leadership and MITRE staff review and comment on the individual SICoP member presentations on August 9th, and especially the white papers from GSA, and give SICoP members the opportunity to present our work in the DoD CoI Quarterly meetings and/or invite the DoD CoI members to the SICoP and SOA CoP meetings.

41. 3.7 SICoP
SICoP was charted under the Best Practices Committee of the Federal CIO Council in March 2003 and has delivered three white papers and produced eleven conferences.
SICoP led the OMB/FEA DRM 2.0 Implementation Team.
SICoP has given Special Recognitions (35) that document the progress along the Spectrum of Reasoning and Applications.
SICoP actively participates in DoD CoI, W3C, Semantic Technology, NCOIC, etc. work groups and conferences.

42. 3.7 SICoP SICoP Has Three White Papers:
Introducing Semantic Technologies and the Vision of the Semantic Web:
W3C Semantic Web and DARPA DAML Program/SICoP Semantic Web Applications for National Security (SWANS) Conference April 2005 (40 exhibits)
Semantic Wave Executive Guide to the Business Value of Semantic Technologies:
2006 Semantic Technology Conference. Updated at 2007 Conference.
Operationalizing the Semantic Web/Semantic Technologies: A roadmap for agencies on how they can take advantage of semantic technologies and begin to develop Semantic Web implementations (recently released for public review):
Advanced Intelligence Community R&D Meets the Semantic Web (ARDA AQUAINT Program).
See IKRIS

43. 4. How 4.1 Model Driven Architecture and Ontology Development
4.2 Knowledgebases for the Government Domain
4.3 Building DRM 3.0 and Web 3.0 Knowledgebases: Where Do the Semantics Come From?
4.4 EPA Data Architecture for DRM 3.0 / Web 3.0 Wiki Page and Knowledgebases

44. 4.1Model Driven Architecture and Ontology Development
Dragan Gasevic, Dragan Djuric, and Vladan Devedzic, Model Driven Architecture and Ontology Development, Springer, 2006:
I. Basics: Existing technologies, tools, and standards including the Semantic Web.
II. The Model Driven Architecture and Ontologies: OMG's new ODM (Ontology Definition Metamodel) Initiative.
III. Applications: Practical aspects of developing ontologies using MDA-based languages.
Web Site: Many ontologies, UML and other MDA-based models, and the transformations between them.

45. 4.1 Model Driven Architecture and Ontology Development
Abstract: Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artifacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these.

46. 4.1 Model Driven Architecture and Ontology Development
Defining a formal domain ontology is a useful and often necessary step in almost any software project. But certain commonly used words have multiple meanings – all equally valid – but which, if not differentiated adequately, leads to much confusion (e.g. use Princeton WordNet).
So describe the high-level structure of your software in the most expressive manner possible, but realize that different minds will still see the same thing (concepts) differently.

47. 4.1 Model Driven Architecture and Ontology Development
The book describes a practical strategy for realizing key elements of the Semantic Web and clearly demonstrates that the core technologies required for constructing the Semantic Web are available and are moving forward inexorably.
Development of ontologies is still hard work. Ontologies have a price that must be paid for the benefits.

48. 4.1 Model Driven Architecture and Ontology Development
An initiative from the software engineering community called Model Driven Development (MDD) is being developed in parallel with the Semantic Web:
First develop a model of the system under study and then transform it into the real thing (e.g. an executable software entity).
For example, start from an ontology, transfer it to a UML platform-neutral domain model, and then generate a Java implementation.
There are lots of similarities in Artificial Intelligence (in this case Knowledge engineering) and Software Engineering (in this case the MDA) approaches and their lifecycle could be parallel.

49. 4.1 Model Driven Architecture and Ontology Development
Knowledge is the understanding of a subject area:
Concepts and facts;
Relations among them; and
How to combine them to solve problems.
Organizing knowledge in a structured way (usually with XML) and using those knowledgebases to solve problems efficiently requires:
Acquisition;
Storage; and
Retrieval.
Ontological knowledge is the categories in the domain and the terms that people use to talk about them.

50. 4.2 Knowledgebases for the Government Domain
Month 2007
Organization
Presentation
January
National Academies Transportation Research Board 86th Annual Meeting
Ontology Tutorial
February
NIST Sensor Standards Harmonization WG
Harmonization in a Semantic Wiki
March
CBRN Data Model in a Semantic Wiki
April
TWPDES Person and NIEM
SICoP Special Conference 2
May
2007 Semantic Technology Conference
Proceedings
See

51. 4.2 Knowledgebases for the Government Domain
Month 2007
Organization
Presentation
June
NSF Nanoinformatics Workshop
Pilot and Semantic Wiki
July
NCOIC SIF WG
SCOPE and Guide to Jargon
August
U.S. EPA
Metatopia 2007
September
W3C Workshop on RDF Access to Relational Databases
Proposed Position Paper
October
SOA CoP
Semantics for SOA Panel
See

52. 4. Language Computer Corporation 5. Open Cyc 6. TopBraid Composer
4.3 Building DRM 3.0 and Web 3.0 Knowledgebases: Where Do the Semantics Come From?
1. Preface
2. SICoP White Paper 3
3. WordNet
4. Language Computer Corporation
5. Open Cyc
6. TopBraid Composer
7. Example: An Information Sharing Environment for the US EPA: The Semantics and Line of Sight of the Organization

53. 4. 4 EPA Data Architecture for DRM 3. 0 / Web 3
4.4 EPA Data Architecture for DRM 3.0 / Web 3.0 Wiki Page and Knowledgebases

54. Summary
1. What: Human-to-Human, Electronic Messages, and Knowledge Reasoning.
Work at on all three levels!
2. Why: Tower of Babel Problem.
3. Who: Collaboration with Those Working On The Problem.
4. How: Ontology Development for Model-Driven Architecture on Use Cases.
Do for the Documents, Models, and Behaviors (Mills Davis) in Your Own Organization (Brand Niemann).

55. Postscripts September 14, 2007:
Demo of the Knoodl Semantic Wiki this past week:
See “The Essential Role of Data Architecture in Business Architecture & SOA”, William Mancuso, President, Information Management Solutions Consultants and SOA Lead for Business Transformation Agency, at the BrainStorm DC Conference, September 10-13, Uses the Knoodl Semantic Wiki!

56. Postscripts The BrainStorm DC Conference, September 10-13, 2007:
Sponsored by the BMPInstitute.Org and the SOAInstutute.Org and includes five conferences in one event:
Business Process Management Conference
Business Architecture Conference
Service-Oriented Architecture Conference
Business Rules Symposium
Organizational Performance Symposium

57. Postscripts
NATO Consultation, Command and Control Agency, Semantic Interoperability Executive Summary, Version 1.4, August 2007:
Focus on Mediation, Discovery, and Ontology Services.
Very similar to the SICoP HITOP (Health Information Technology Ontology Project) that is using semantic mediation between medical information systems (immediate solution) and ontology building (longer-term solution).
The NCOIC Problem (John Yanosy):
Semantically harmonize the context across the multiple documents of multiple NCOIC WGs that we have been hoping the Semantic Wikis would address and that I tried to address in my recent SCOPE document pilot.
Moresophy addresses this problem:
See

58. Postscripts
Enterprise Architecture Framework Version 1.0, August 2007, Prepared by the Program Manager, Information Sharing Environment:
Section Observations and Issues: A long-term strategy should consider formal semantic representations for the CTISS data and metadata elements to provide a stable foundation supporting precise common meanings, accurate translations, semantic search, semantics-based information extraction and integration, and effective analysis of shared information. Evaluation studies and prototypes are needed to pave the way for a semantic technology implementation roadmap that will provide the ISE and its stakeholders the benefits of semantic capabilities. For example, the Web Ontology Language (OWL) and Resource Description Framework Schema are beginning to be adopted as standards as the World Wide Web evolves into the Semantic Web. Creation of a prototype that evaluates the use of OWL for data exchange in the ISE should be considered.
CTISS: Common Terrorism Information Sharing Standards

59. Postscripts
NCOIC Plenary and Working Group Sessions, September 17-20, 2007:
Semantic Interoperability Framework WG Challenge: “Get the NCOIC to Semantic Interoperability”:
(1) Conference Matrix:
As-Is and the To-Be
(2) NCOIC Structures:
Organization, Frameworks, Deliverables, and Kavi Content
(3) NCOIC Ontologies:
Documents, Models, and Behaviors

60. (1) Conference Matrix Date Session To Be 9/17/07 NIF SOA DoD CIO
9/18/07
Events & SOA
Semantic SOA
SI Data
Strategy
9/19/07 SF
Knowledge-bases
FAA
9/20/07
SIF
SCOPE

61. (1) Conference Matrix Semantic Plan to do ?? Technical Vignettes
Cross-Domain
Interoperability
Levels of Interoperability (European Framework)
Semantic
Plan to do ??
Technical
Vignettes
Organ-izational
CIO Summit
Confer-ences
FAA NextGen
Logistics
Mobility
Etc.
Lines of Business

62. (2.3) Technical Roadmap
NCOIC Technical Roadmap, September 12, 2007

63. (2.4) Kavi Content Advisory Council (29 members, 47 documents)
Executive Council (57 members, 284 documents)
General Document Repository (24 members, 513 documents)
Technical Council (85 members, 659 documents)
Technical Team (804 members, 624 documents)
Semantic Interoperability Framework WG (88 members, 153 documents)
Etc.

64. (3) NCOIC Ontologies