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A New Enterprise Information Architectureand Data Management Strategy for

the U.S. GovernmentPart 8: Emergency Management and Sensors

Brand L. NiemannSenior Enterprise Architect,

US EPA Enterprise Architecture Team, andCo-Chair, Federal Semantic Interoperability Community of Practice

(SICoP)Presentation to Sensor Standards Harmonization WG at NIST

January 15, 2008

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FrameworkComponent Form Need Activity

Standards Document

(XSD) (1)

Conceptual Model (2)

Harmonization (6)

Sensors Hardware Contextual and Data Model (3)

Compliance (7)

Network Data Point of Origin (4)

Annotate (5)

Integration with Non-sensor Data & Query(8)

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Footnotes• (1) Not all sensor standards have XML Schemas, but they are

not real data models anyway.• (2) Definitions of the concepts and their semantic relationships.• (3) The purpose of the sensor and the model of its data output.• (4) SICoP thinks this should be done at the point of origin of the

data – each sensor needs a semantic context, data model and output.

• (5) Others have shown that data can be semantically annotated afterwards to produce applications.

• (6) The concepts across multiple standards are the same, nearly the same, or different.

• (7) Does the sensor (hardware) comply with the sensor standard (document)?

• (8) Is the output of multiple sensors (hardware) semantically interoperable with itself and with non-sensor data and query-able?

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Plan of Action

• Create incentives to get Semantic Web Standards and Technologies into Sensor Standards and Sensors by showing what can be done with the data when that happens:– Launched Semanticommunity.net: Community

Infrastructure Sandbox for 2008, January 7, 2008.– Special Conference on Building Semantic

Interoperability Solutions for Information Sharing and Integration, February 5, 2008, at the CSC Executive Briefing Center, Falls Church, VA.

– Show how the telecommunications industry is doing this at the 2008 Semantic Technology Conference, May 18-22, 2008, San Jose, CA.

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Plan of Action

http://colab.cim3.net/cgi-bin/wiki.pl?SICoPSpecialConference_2008_02_05

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Abstract• The Data Web (aka Semantic Web) will come about in

three basic ways, namely, reuse (repurposing) of existing Web content, middleware to provide RDF Access to Relational Databases and Spreadsheets on the Web, and by connecting devises (e.g. sensors) to the Web that deliver their data directly. Experts predict that the flood of data on the Web to be analyzed will come from devices connected to the Internet. Clearly emergency management and sensor data require an enterprise information architecture and data management strategy and the work of SICoP for the Interagency Sensor Standards Harmonization Working Group and of others needs to be integrated to this end for the Federal Government.

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Abstract• The work of SICoP to support the Interagency Sensor

Standards Harmonization Working Group (SSHWG) has evolved from sensor standard harmonization - to modular ontology - to multiple sensor standards interoperability demonstrations - to doing this within the broader context of a semantic interoperability information architecture and data management strategy. The SICoP Sensor Standards Harmonization Knowledgebase contains examples using multiple approaches, namely: Common Subject Index, Data Model, Most Basic Concepts from Upper Ontologies, Commonality / Variability, Model (or Ontology) In Mind, and Concept Maps. The Knowledgebase is a semantic model built on top of the full text of the multiple standards and is essentially a mashup that supports enhanced search of sensor metadata for harmonization! Specific recommendations are provided to help the SSHWG achieve its goals.

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Contents

• 1. Introduction• 2. Information Architecture and Data

Management Strategy• 3. Examples• 4. Recommendations• 5. References• Appendix I: Demonstrations• Appendix II. Questions and Answers (Specific to

the needs of the Interagency Sensor Standards Harmonization Working Group)

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1. Introduction

• The Semantic Wave 2008: Industry Roadmap to Web 3.0* explains the evolution of the Web in simple terms as:– Web 1.0 connects documents;– Web 2.0 connects people;– Web 3.0 connects knowledge (data);– and Web 4.0 connects intelligence.

*Mills Davis, SICoP Co-chair

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1. Introduction

• The Data Web (aka Semantic Web) will come about in three basic ways, namely, reuse (repurposing) of existing Web content (2), middleware to provide RDF Access to Relational Databases (3) and Spreadsheets (4) on the Web, and by connecting devises (e.g. sensors) to the Web that deliver their data directly.

• This supports the Federal Enterprise Architecture Principle 6 which states that “Information is a national asset (actually a global asset - my words) needed by citizens and leveraged across the government to improve performance” because “A well informed citizenry is necessary to our constitutional democracy. Further, accurate information is critical to effective decision making, improved performance, and accurate reporting.”

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1. Introduction

• Experts predict that the flood of data on the Web to be analyzed will come from devices connected to the Internet:– “In the next century, planet earth will don an electronic skin. It

will use the Internet as a scaffold to support and transmit its sensations. This skin is already being stitched together. It consists of millions of embedded electronic measuring devices: thermostats, pressure gauges, pollution detectors, cameras, microphones, glucose sensors, EKGs, electroencephalographs. These will probe and monitor cities and endangered species, the atmosphere, our ships, highways and fleets of trucks, our conversations, our bodies--even our dreams.”

• August 1999, Neil Gross, "The earth will don an electronic skin," BusinessWeek.

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1. Introduction

• Clearly emergency management and sensor data require an enterprise information architecture and data management strategy and the work of SICoP for the Interagency Sensor Standards Harmonization Working Group and of others needs to be integrated to this end for the Federal Government.

• The suggested architecture and management strategy are outline in the next section, examples are provided in Section 3, and recommendations in Section 4. The Appendices contains some demonstrations and questions and answers specific to the needs of the Interagency Sensor Standards Harmonization Working Group.

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2. Information Architecture and Data Management Strategy

• The history of SICoP support for the Interagency Sensor Standards Harmonization Working Group hosted by NIST is summarized in Table 1.

• A recent summary of the SSHWG, lead by Kang Lee at NIST, is reflected in this table below and his suggestions for the sensor standards to be harmonized and the possible use of ontology are shown in Figures 1 and 2, respectively.

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2. Information Architecture and Data Management Strategy

Date Name Purpose SICoP Work December 13, 2005 SSH Meeting (10) Initial

Discussions

March 7, 2006 SSHWG (10) Prepare for March 14 Meeting

March 14, 2006 SSHWG (10) Develop Framework

June 21, 2006 SSHWG (10) Plan Future

August 2-3, 2006 Conference (11) Share Interests Wiki Page (12) and Presentation (13)

September 12, 2006 SSHWG (10) Use Cases Presentation (14) & Demonstration (15)

See Slides 11-12 for footnotes.

Table 1. SICoP Participation in the Sensor Standards Harmonization WG at NIST

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2. Information Architecture and Data Management Strategy

Date Name Purpose SICoP Work

November 28, 2006 SSHWG (10) Identify Other Communities

Presentation (16) & Demonstration (15)

February 27, 2007 SSHWG (10) Sensor Metadata Harmonization

Presentation (17) & Demonstration (15)

June 26, 2007 SSHWG (10) Other Communities

Presentation (18) & Demonstration (15)

October 16, 2007 SSHWG (10) Reports & Plugfest

Presentation (19) & Demonstration (15)

January 15, 2008 SSHWG (10) TBA Presentation (20) & Demonstration (15)

See Slides 11-12 for footnotes.

Table 1. SICoP Participation in the Sensor Standards Harmonization WG at NIST

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2. Information Architecture and Data Management Strategy

• Footnotes:– (10) National Institute for Standards and Technology

– http://www.nist.gov• Interagency Sensor Standards Harmonization Working Group

– http://ieee1451.nist.gov/membersonly/ (password required)

– (11) August 2-3, 2006, Net Ready Sensors Workshop, Oak Ridge National Laboratory, Oak Ridge, TN

• http://www.sensornet.gov/net_ready_workshop/index.html– (12) August 3, 2006, Wiki Page

• http://colab.cim3.net/cgi-bin/wiki.pl?NetReadySensorsWorkshop_2006_08_0203– (13) August 3, 2006, Net Ready Sensors Workshop, Oak Ridge National

Laboratory, Oak Ridge, TN• Presentation: SICoP and Proposed Pilot of DRM 2.0 for Net-Ready Sensor Data

– http://colab.cim3.net/file/work/SICoP/2006-08-02/SICoP08022006.ppt

– (14) September 12, 2006, Sensor Standards Harmonization Work Group Meeting (NIST)

• Presentation: Sensor Network Pilots for DRM 2.0– http://colab.cim3.net/file/work/SICoP/2006-09-12/SICoPNIST09122006.ppt

– (15) September 12, 2006, Sensor Standards Harmonization Work Group Meeting (NIST)

• SICoP Semantic Wiki Pilots:– http://web-services.gov/lpBin22/lpext.dll/Folder21/Infobase/2?fn=main-j.htm&f=templates&2.0– http://www.visualknowledge.com/wiki/sensors

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2. Information Architecture and Data Management Strategy

• Footnotes (continued):– (16) November 28, 2006, Sensor Standards Harmonization Work Group Meeting (NIST)

• Presentation: Sensor Network Pilots for DRM 2.0– http://colab.cim3.net/file/work/SICoP/2006-11-28/SICoPNIST11282006.ppt

• Demonstrations: See (15)– (17) February 27, 2007, Sensor Standards Harmonization Work Group Meeting (NIST)

• Presentation: Harmonization of Sensor Standards in Semantic Wikis– http://colab.cim3.net/file/work/SICoP/2007-02-27/SICoPSSHWG02272007.ppt

• Demonstrations: See (15)– (18) June 26, 2007, Sensor Standards Harmonization Work Group Meeting (NIST)

• Presentation: Harmonization of Sensor Standards in Semantic Wikis (Modular Approach to SSHWG Ontology)

– http://colab.cim3.net/file/work/SICoP/2007-06-26/SICoPSSHWG06262007.ppt– http://colab.cim3.net/file/work/SICoP/2007-06-26/SICoPSSHWGS6262007.ppt

• Demonstration: See (15) and CBRN Data Model in a Semantic Wiki (March 28, 2007)– http://knoodl.com/

– (19) October 16, 2007, Sensor Standards Harmonization Work Group Meeting (NIST)• Presentations: Harmonization of Sensor Standards in Semantic Wikis (Modular Approach to SSHWG

Ontology) and Proposed Demonstrations.– http://colab.cim3.net/file/work/SICoP/2007-06-26/SICoPSSHWG10162007.ppt– http://colab.cim3.net/file/work/SICoP/2007-06-26/SICoPSSHWGS06262007.ppt– http://colab.cim3.net/file/work/SICoP/2007-10-16/BNiemann08302007.doc

• Demonstrations: See (15)– (20) January 15, 2008, Sensor Standards Harmonization Work Group Meeting (NIST)

• This paper: http://colab.cim3.net/file/work/SICoP/EPADRM3.0/BNiemann01042008.doc• Presentation: http://colab.cim3.net/file/work/SICoP/2008-01-15/SICoP01152008.ppt

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2. Information Architecture and Data Management Strategy

• The work of SICoP to support the Interagency Sensor Standards Harmonization Working Group has evolved from sensor standard harmonization - to modular ontology - to multiple sensor standards interoperability demonstrations - to doing this within the broader context of a semantic interoperability information architecture and data management strategy. This was the same approach taken in an earlier SICoP Pilot that lead to the recent formation of the Integrated Response Services Consortium (IRSC) (8), namely, the actual information and data from a disaster event was organized into an event ontology that made the emergency services of multiple vendors semantically interoperable during a simulation of this event and showed how new sensors (e.g. detection chlorine tanker car train derailment) could significantly improve the first response.

• The SICoP Sensor Standards Harmonization Knowledgebase contains examples using multiple approaches, namely: Common Subject Index (See Figure 3), Data Model (see Figure 4), Most Basic Concepts from Upper Ontologies, Commonality / Variability, Model (or Ontology) In Mind, and Concept Maps. The Knowledgebase is a semantic model built on top of the full text of the multiple standards and is essentially a mashup that supports enhanced search of sensor metadata for harmonization!

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2. Information Architecture and Data Management Strategy

Figure 1. Sensor Standards Harmonization Framework (Kang Lee, NIST)

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2. Information Architecture and Data Management Strategy

Figure 2. Sensor Standards Harmonization Using Ontology? (Kang Lee, NIST)

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2. Information Architecture and Data Management Strategy

Figure 3. Semantic Wiki Knowledgebase of Sensor Standards Harmonization. Harmonization by Common Subject Index

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2. Information Architecture and Data Management Strategy

Figure 4. Semantic Wiki Knowledgebase of Sensor Standards Harmonization. Harmonization by Data Model (CBRN)

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2. Information Architecture and Data Management Strategy

• The Semantic Sensor Web Data Management Strategy states: “Effective automation of sensor data fusion requires ability to translate heterogeneous sensor data into a common format, to register data accurately within a common spatiotemporal reference frame, and to identify and associate cross-modal phenomenal attributes. To accomplish this task, SAVig is extending state-of-the-art sensor data representation languages, SensorML and TransducerML, to integrate semantic associations into sensor models. Semantic descriptions of concepts and associations within sensor data representations will enable entity and event detection and sensor data fusion in multi-level, multi-modal streaming sensor data.

• SICoP also concurs with this approach.

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2. Information Architecture and Data Management Strategy

• The Semantic Sensor Web Data Management Strategy includes several different approaches that are being pursued simultaneously, namely … using Semantic Web annotations and extending the Open Geospatial Consortium (OGC) standards.

• SICoP has gone one step further by recommending in essence that each sensor needs to have its own data model, expressed as an Ontology in the Ontology Web Language (OWL), and deliver its data stream in the Resource Description Language (RDF) markup language.

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2. Information Architecture and Data Management Strategy

• The purpose of this new information architecture and management strategy is to:– structure unstructured government information;– make government databases visible to search engine

crawlers and users;– consolidate government information to make it easier

to use; and to– provide semantic metadata and linking in support of

DRM* 3.0 and Web 3.0 knowledgebase applications.

Federal Enterprise Architecture’s Data Reference Model.

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2. Information Architecture and Data Management Strategy

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.pdfwith annotations by the author.

DRM 1.0 SICoP

Ontologies

All Three

DRM 3.0 Unify

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2. Information Architecture and Data Management Strategy

http://colab.cim3.net/cgi-bin/wiki.pl?EPADataArchitectureforDRM3Web3

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3. Examples

• Examples of sensor standard harmonization, modular ontology development, multiple sensor standards interoperability demonstrations, the broader context of a semantic interoperability information architecture and data management strategy were compiled for the Interagency Sensor Standards Harmonization Working Group (see Appendix I).

• Initial discussions with Spatial Ontology Community of Practice (SOCoP) and the OGC revealed the need to first harmonize Google’s KML and OGC’s GML, but further investigation found these two standards have little overlap (also see Appendix I).

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3. Examples• The contents of Figures 1 and 2 contain the core data elements for

a Sensor Standards Harmonization data model and following “Data Modeling and OWL: Two Ways to Structure Data” the objectives of a data model are to:– A. Capture the semantics of an organization.– B. Communicate these to the business without requiring technical skills.– C. Provide an architecture to use as the basis for database design and

system design.• Then:

– D. This provides the basis for designing Service Oriented Architectures.– E. Both data modeling and ontology languages represent the structure

of business data (ontologies).– F. Data modeling represent data being collected, and filters according to

the rules.– G. Ontology languages represent data being used, with the ability to

have computer make inferences.– H. So ontology can improve data quality in legacy systems as well!

Note: The later is the subject of an upcoming SICoP Special Conference, February 5, 2008. See next slide.

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3. Examples

http://colab.cim3.net/cgi-bin/wiki.pl?SICoPSpecialConference_2008_02_05

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4. Recommendations

• This New Enterprise Information Architecture and Data Management Strategy for the U.S. Government explains and illustrates the terms Reduce, Reuse, and Recycle and is based on:– The premise of reusing the data and information

rather than changing the data systems themselves:– Putting the business and technical rules, logic, etc.

into the data itself using markup languages.– The concepts and standards of the Semantic Web:

Also called the Data Web or Web 3.0.

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4. Recommendations

• The most important tenets of the reuse are:– Bring the data and the metadata back together.– Bring the structured and unstructured data and

information back together.– Bring the data and information description and context

back together.

• The new enterprise information architecture and data management strategy supports all three orders of orders and the four functionalities of the DRM 3.0 / Web 3.0.

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4. Recommendations• This knowledgebase pilot supports the four

functionalities of the DRM 3.0 / Web 3.0, namely:– (a) Data and Metadata: Full text of documents, standards,

meeting notes, etc.;– (b) Harmonization: Different ways in which the same words are

used;– (c) Enhanced Search: Across all content and showing context

(e.g. words around the term or concepts); and– (d) Mashups: A website or application that combines content

from more than one source into an integrated experience (repurposing, reuse).

• This knowledgebase pilot also supports the three orders of order as follows:– (a) we organize the knowledgebases themselves;– (b) we add structured semantic metadata to each

knowledgebase; and– (c) the knowledgebases have taxonomies/ontologies that

support semantic linking and searching.

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4. Recommendations

• The answers to recent questions from the Interagency Sensor Standards Harmonization Working Group provide the basis for some of the recommendations (see Appendix II).

• Furthermore, it is recommended that SICoP and others continue to collaborate with the SSHWG to accomplish the following practical steps:– Develop a modular data model (ontology) based on

• (a) Figures 1 and 2,• (b) the semantics in the Semantic Wiki Knowledgebase, and• (c) state-of-the-art ontology development principles, in a

spreadsheet, like was done for the CBRN Data Model and then– import it into a Semantic Wiki (Knoodl), and build a semantic

SOA application to demonstration semantic interoperability across multiple sensors and sensor data.

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5. References

• January 15, 2008, Net-Ready Sensor Standards Harmonization Meeting at NIST: Ontologies for Selected Standards and Sensors. A New Enterprise Data Management Strategy for the U.S. Government - Part 8: Emergency Management and Sensors Paper and Slides. New collaboration with the Semantic Sensor Web, Amit Sheth, LexisNexis Ohio Eminent Scholar, Wright State University. See Sensor Data Management: Short and Long.

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Appendices

• Appendix I: Demonstrations

• Appendix II. Questions and Answers (Specific to the needs of the Interagency Sensor Standards Harmonization Working Group)