1 / 64

Semantic Interoperability: The What, Why, Who, and How

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,

sacco
Download Presentation

Semantic Interoperability: The What, Why, Who, and How

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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 55-64.

  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 2006 - 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). • http://www.quotationspage.com/quotes/Robert_McCloskey/

  8. 1. What • Semantics = Meaning = Relationships • 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 • 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 • 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 • 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. • https://www.ncoic.org/wiki/Interoperability

  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. • https://www.ncoic.org/wiki/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. • https://www.ncoic.org/wiki/SemanticInteroperability • 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. • https://www.ncoic.org/wiki/Lexicon

  16. 1. What DRM 1.0 SICoP 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. http://www.whitehouse.gov/omb/budintegration/expanding_egov_2005.pdf With annotations by the author.

  17. 1. What

  18. 1. What Source: Mills Davis, SICoP Co-Chair: http://www.semantic-conference.com/2007/handouts/6-UpBW/T8_Davis_Mills_SingleColor.pdf

  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). • http://www.w3.org/2001/sw/

  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. • http://www.w3.org/2001/sw/

  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! http://www.w3.org/2007/03/layerCake.png

  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 https://www.schafertmd.com/swans/. (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: • http://www.w3.org/2007/06/eGov-dc/agenda.html • October 25-26, 2007, W3C Workshop on RDF Access to Relational Databases, Boston, MA, USA. SICoP Position Paper on Integration of Data Tables: • http://www.w3.org/2007/03/RdfRDB/cfp

  27. 3.2 Open Group Semantic Interoperability WG • Background and Meetings: • http://www.opengroup.org/projects/si/ • Universal Data Element Framework (UDEF): • http://www.opengroup.org/udefinfo/ • 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) http://cio.gov/index.cfm?function=eastatement

  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. • http://www.semantic-conference.com/2007/handouts/2-UpBW/Hay_David_2_2UpBW.pdf

  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: • https://www.dnidata.org • 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: • https://www.ncoic.org/technology/deliverables/scope • http://www.visualknowledge.com/wiki/NCOIC_SIF • Collaborations: • Incremental knowledgebase from each conference call and meeting: • http://colab.cim3.net/file/work/SICoP/2007-07-05/SICoPNCOICSIF.ppt • 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: • http://www.defenselink.mil/cio-nii/coi • 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 http://colab.cim3.net/file/work/SICoP/2007-08-09/SICoP08092007.ppt

  36. 3.6 DoD Community of Interest http://colab.cim3.net/cgi-bin/wiki.pl?SICoPSpecialBriefing_2007_08_09

  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 email 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 2.0 - 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 3 - 5 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 2006 - 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 http://nrrc.mitre.org/NRRC/ikris.htm

  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. • http://www.modelingspaces.org/

  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 See http://web-services.gov

More Related