SICoP 2011 : Transforming Government through Innovation with Semantic Technologies

1. SICoP 2011: Transforming Government through Innovation with Semantic Technologies SemTech 2011, June 5-9, San Francisco, CA. Conference Presentation: Tuesday, June 7, 2011, 07:30 AM - 08:20 AM. Brand L. Niemann Director and Senior Data Scientist, Semantic Community http://semanticommunity.info/ Mills Davis Founder and Managing Director, Project10X http://www.project10x.com

2. Abstract • We are restarting the Semantic Interoperability Community of Practice (by popular demand) and are working on a series of meetings/workshops in 2011 in collaboration with a numbers of groups and individuals based on three things: • (1) Mapping VivekKundra's 25 point plan to CoPs and individuals; • (2) The new OASIS Technical Committee on Transformational Government; and • (3) Our very successful SICoP meeting in 2009. • See From E-Government to Transformational Government Wiki page and slides. • To seed this activity we have prepared a series of Data Science Products for Social Business Intelligence with Open Government Data Using Semantics that will be demonstrated along with highlights from the meetings we have conducted so far. • The ideas we would like to explore with you include how best we might: • (1) Harvest and package content from the sorts of meetings & demonstrations we have done and are planning for dissemination through media channels -- publications, digital, events, etc.; and • (2) Collaborate together to develop and conduct a series of educational events that would reach the right audiences as well as benefit all parties involved.

3. Background • My Experiences (Editorial for Federal Computer Week in process): • Standardizing “Eformsfor Egov” for Mark Forman with the eGrants Schema and Web Services as Chair of the Federal CIOC’s Web Services Working Group; • Move everybody up in interoperability instead of ‘rip-n-replace’. • Standardizing SOA and Semantic Interoperability for the Federal CIO Council with multiple pilots, ontology, and semantic technologies as Co-chair of the Federal CIOC’s SOA and SICoP Communities of Practice; and • ‘Show me a SOA’ and get the ‘Medici Effect: the model-driven approach and the best and brightest will find one another and collaborate to innovate, facilitated by the technology itself”. • Standardizing cloud computing for VivekKundra and Aneesh Chopra for desktops, Gov 2.0 platforms, data centers, and health data as Director and Senior Data Scientist of the Semantic Community and formerly senior enterprise architect and senior data scientist for the US EPA. • ‘Think outside the box’ and foster open collaboration with open standards in multiple pilots. • I especially want to put the recent Federal CIOC’s reports on NIEM into a broader perspective: • See http://semanticommunity.info/National_Information_Exchange_Model/Assessment_Report

4. Background

5. Agenda • 1. Welcome – Brand Niemann • 2. Recent Events – Brand Niemann • 3. Knowledge – Centric Systems – Mills Davis • 4. Demos: • Semantic Insights – Chuck Rehberg • Be Informed – Video • 5. Questions and Answers –All • Please sign the sheet for our mailing list.

6. 1. Welcome • We are helping the following: • Data.gov and the Federal CIO Council’s Data Architecture Subcommittee • US Health and Human Services Health Data Forum and VIVO • The Open Group TOGAF 9 and UDEF • The OMG Semantic Information Modeling for Federation • The OASIS Technical Committee on Transformational Government • The NIST Federal Cloud Computing Initiative and GovCloud • The SEMIC.EU and CKAN • The 1105 Government Information Group and AOL Government • The Harvard Leadership for a Network World Program

7. 2. Recent Events http://semanticommunity.info/#Events_Calendar

8. 3. Knowledge – Centric Systems • 3.1 Knowledge-centric Paradigm Shift • 3.2 Knowledge-centric Collaboration • 3.3 Business Value of Knowledge-centric Solutions • 3.4 Three Approaches to Knowledge-Centric Services and Solutions: • Citizen-centric Government — Systems That Know • Advanced Analytics — Systems That Learn • Smart Operations — Systems That Reason

9. 3.1 Knowledge-centric Paradigm Shift • A major conceptual advance towards distributed intelligence. A long wave of innovation driving fundamental shifts in technology, culture, and economics. • Separating the “know” from the infrastructure, information, application, & user interface! • See SICoP Special Conference, February , 2009: • http://semanticommunity.info/From_E-Gov_to_Connected_Governance:_the_Role_of_Cloud_Computing,_Web_2.0_and_Web_3.0_Semantic_Technologies_February_17_2009

10. 3.2 Knowledge-centric Collaboration • Each person contributes using forms of knowledge expression they understand such as documents, drawings, pictures, models, software behaviors, user interface designs, etc. — yet all have visibility into all the underlying concepts and relationships. • Combining wikis, semantic content tools, semantic search, ontology-driven applications, and intelligent user interfaces. • Context-aware services, semantic browsing, expert systems, and virtual assistants that complete tasks for you (e.g., Mobile Semantics).

11. 3.3 Business Value of Knowledge-centric Solutions • How does one get value creation? • By modeling knowledge, adding intelligence, and enabling learning. • After 2010, it makes no sense to develop IT systems under the information-centric paradigm. • The value proposition of the knowledge-centric paradigm is too great!

12. 3.3 Business Value of Knowledge-centric Solutions • Value gets created in three ways: • Via reimplementation of current capabilities, to achieve greater efficiency / effectiveness. • Via provision of new (or newly viable) capabilities, to increase mission and/or enterprise value. • Via the exploitation of new knowledge generated as a result of use of knowledge-centric “tools” . • By combining knowledge-intensive services (people) with knowledge-centric processes to deliver knowledge-driven solutions.

13. 3.4 Three Approaches to Knowledge-Centric Services and Solutions • Citizen-centric Government — Systems That Know • Advanced Analytics — Systems That Learn • Smart Operations — Systems That Reason Note: * SICoP has done or is doing pilots in most of these. See http://semanticommunity.info/Federal_Semantic_Interoperability_Community_of_Practice and http://semanticommunity.info/From_E-Government_to_Transformational_Government

14. 4. Semantic Insights • As CTO at Trigent Software and Chief Scientist at Semantic Insights, Chuck Rehberg has developed patented high performance rules engine technology and advanced natural language processing technologies that empower a new generation of semantic research solutions. • Chuck has more than twenty five years in the high-tech industry, developing leading-edge solutions in the areas of Artificial Intelligence, Semantic Technologies , analysis and large –scale configuration software.

15. 4. Semantic Insights 4.1 Objectives of Pilot Phase II (Semantic Insights) 4.2 Background 4.3 Application: Tools and Examples 4.4 Live Demonstration 4.5 If we have time: • Some things to know before using SIRA • Some things to stimulate your imagination

16. 4.1 Objectives of Pilot Phase II • Provide a real-time semantic research and reporting tool for the conference proceedings and related information • Support three user scenarios: • 1105 Readers search (1105 content) • 1105 Authors and Editors search (1105 content and others) • 1105 Conference Attendees search (this pilot content) • Create/generate domain-specific Ontologies and Dictionaries • Demonstrate how these improve real-time semantic research results of conference proceedings and related information • Present the findings at the next KM conference

17. 4.2 Background Who are we? “Semantic Insights” is the R&D division of Trigent Software, Inc. www.semanticinsights.com What is our Mission? Automate research tasks (faster, better, cheaper) Why Semantics? Semantics allows us to reduce to the “meaning level” (“separate the know from the show”) Why us? Intelligence, Technology, Passion and Delivery

18. 4.2 The Semantic Insights Research Assistant (SIRA) • Our Mission: • The SIRA technology was developed to automate research tasks requiring natural language, domain-knowledge, understanding and reasoning. • SIRA-based products must be easy-to-use requiring little or no training beyond what the user already understands. • Mission Status: • We have developed PriArt, an embodiment of the SIRA technology that automates the understanding and reading of natural language text (initially English), gathers specific information of interest and produces a variety of useful reports. • Other SIRA embodiments have been conceived and prototyped. • Today SIRA can: • Semantically understand a statement of your interest expressed in Natural Language • Read through a vast number of documents • Identify semantic relevant information of interest in Natural Language text • Report the findings in useful ways including Natural Language text

19. 4.2 Our Mission…with a little more Precision The SIRA technology was developed to automate research tasks requiring natural language, domain-knowledge, understanding and reasoning. • By “research tasks” we mean, “information gathering tasks that currently require humans with domain-knowledge, Natural Language skills or otherwise would take considerable time” • By “domain-knowledge” we mean, “background information that is necessary to understand a given natural language text” • By “understanding” we mean, “the ability to create a meaning map that relates experiences (e.g. natural language text) to semantic items in an Ontology” • By “reasoning” we mean, “the ability to further process the meaning map to generate derived experiences”

20. 4.2 The Semantic Advantage • The Natural Language Challenge • In natural language there are many ways to say the same thing. • When reading documents you need to be able to recognize when semantically equivalent text • The text you read may have little (or nothing) in common with the words or structure of the original research statement. • At SIRA core is an Ontology • SIRA’s Ontology acts like a dictionary of “semantic items” (concepts, relationships, instances, generalizations, specializations, etc.). • However, the Ontology goes beyond the expressiveness of dictionaries by explicitly stating how the semantic items are related. • The Semantic Advantage • One power of the Ontology comes from providing a single logical expression for the many ways of saying the same thing.

21. 4.3 Application: Tools and Examples • PriArt: A Semantic Research Assistant (Web) • Examples presented: Autism report, high school assignment, homeland security, patent infringement • SIRA Development Center (Desktop) • Used to develop and manage World Knowledge • Ontologies, Dictionaries, Testing and Training • Live Demonstration of Ontology and Dictionary creation and curation • Language Lab*: Define Language and Genre (Web) • Syntax, Grammar and Meaning Maps *Note: The Language Lab is not presented in this talk

22. 4.3 Introducing the PriArt

23. 4.3 What you need to know about PriArt • PriArt is an on-line Research tool that creates: • Research reports containing information relevant to your research • A bibliography with hyperlinks to sited documents • Here’s the quick start guide: • Login • Create an Investigation • Enter name of your Investigation • Enter a description of your investigation • Select the kind of report you want • Select where you want PriArt to read • Submit the research • Review the results

24. 4. Knowledge-Centric Systems in the Cloud: Be Informed Web Interface Screen Captures from Short Video

25. 4. Knowledge-Centric Systems in the Cloud: Be Informed Ontology Model Interface Screen Captures from Short Video

26. 5. Questions and Answers • Brand Niemann: • http://semanticommunity.info • bniemann@cox.net • Mills Davis: • http://www.project10x.com • mdavis@project10x.com