Semantic Web for the Military User Progress

1. Semantic Web for the Military User Progress Tom Martin Research Management Enterprises tmartinrme@prodigy.net (571) 215-9802

2. Semantic Web Military Applications World Wide Semantic Web W3C/DAML-OIL DAML Program Infrastructure, Tools, Applications, and Language Center for Army Lessons Learned Thesaurus Forcenet/ ESG/Doctrine/LL Web Enabled Navy JBI Foreign Clearance Guidance Other/TBD Intelink Horus Ongoing & Planned Ongoing Specific Projects, Military Applications

3. SWMU II – Nov 12/13 2001 Agenda Attendees Approach Outcome – Working Session Results Joint SWMU/GMUG/EEE Meeting March 25-27, 2002 Background Rationale for Joint Meeting Objectives Approach/Agenda Semantic Web for the Military User Meetings

4. Tuesday, November 12, 2001 AM – Introduction for those who had not attended SWMU-I (June 2001) Ontologies Introduction, Horus Overview, DAML Language, Example Demo IT Talks, & Summary of Last Meeting (SWMU-I) PM – Plenary for all attendees Update of DAML Several short DAML demos – BBN, DRC, and LM AeroText CoABS Grid Military Users Group (GMUG) overview Horus update NWDC updates, Updates from Breakout groups: Intelligence (Joe Rockmore) Doctrine/Lessons Learned (Alice Mulvehill) C2 Applications (Tom Martin) Evening Demo session Wednesday, November 13, 2001 Intel, Doctrine/LL, and C2 Breakouts and Outbriefs SWMU II Agenda

5. Elaine Marsh/NRL Frank Muller/BBN Paul Kogut/Lockheed-Martin Joe Rockmore/Cyladian Mike Dean/BBN Rob Rasch/BCBL-L (Army) Mike Rimmer/NWDC Mark Gorniak/AFRL Ken Whitebread/LMSC/ATL Frank White/SSC Martha Kahn/Global Infotek Hal Hultgren/NWDC Paul Neves/BBN Lee Lacy/DRC Tom Martin/RME Alice Mulvehill/BBN Wayne Perras/NWDC  SWMU II Attendee/Organizations • David  Rager/BBN • David Aha/NRL • Jake Jacobowitz/OC Inc • Sally DeGozzaldi/Joint Staff/J7 • Mike Pratt/OC Inc • Dennis Toomey/Anteon • Ted Baer/Anteon • Bruce Peoples/Raytheon • Mark Werner/NWDC • Chuck A Menges  USMC Doc Div • Phillip Boos/Thomas Associates • Bob Lucas/JCLL at JWFC • Chuck McGrath/OC Inc/JFCOM/JWFC • Kalyan Gupta/ITT Industries/NRL • Mike Dietvorst/USAF Doctrine Center • Marti Hall/DRC Orlando  • Paul Odell/NWDC           

6. Charter How do the ideas of the semantic web specifically apply to intelligence problems? What unique problems does the intelligence community have with respect to using semantic web technology? How can we leverage the work being done in DAML, and specifically the applications to intelligence, to other efforts? Intelligence BreakoutJoe Rockmore - Facilitator

7. Markup Markup Markup Map Map Map Semantic Web Functional Architecture • Browsing • Visualization • Q & A • Etc. Docs User interactions { DAML } KB DBs Analyses Ont dev

8. Intelligence needs to talk about what was, is, and might be (with uncertainty), while C2 plans what to do with resources available, logistics makes resources available, etc. Ontologies need to reflect differences in data and mission Issues of interest to intelligence (primary) Money laundering, geopolitical issues, financial transactions, non-military organizations, drugs, counter-terrorism, etc. Imagery, signals, open source, & analysis of this data Generally higher levels of abstraction than C2, etc. Source info and confidence in source important Temporal and spatial reasoning important Intelligence Ontologies(vice C2, logistics, or others)

9. Understand documents enough to know locations in a document Placename, lat/lon, BE num, UTM, etc. Disambiguation Granularity issues Understand documents enough to know temporal aspects in a document Absolute time in different granularity (date & time to milliseconds vs. season) and representations (Julian date, DTG, etc.) Disambiguation Relative time (before, after, within, overlapping, close to, etc.) Co-reference problems in geolocations and times Significant Issue: Geolocation & Temporal Representation

10. Consumer-based and producer-based markup tools needed Combine automated and manual markup intelligently Markup as part of authoring Culture is analysts (producers) are too busy to do any additional work, such as markup, unless Its very easy to do There is clear value to producers (not just consumers) Someone measures them on the quality/quantity of markup Mid term: mixed initiative, where authoring and knowledge object creation are done in parallel and with either driving the process A long term view: author knowledge objects from the outset; form products from these objects, including English text documents Multilingual opportunities Significant Issue: Markup Tools

11. Tailored push; also pull (“My Intelink”), including changes of sufficient magnitude Subscriptions and data descriptions for matching against subscriptions may be best done using hierarchical ontologies (vice database schemata, which are not sufficiently expressive) Crawlers of value, but may have access control issues (open source an exception) Uncertainty of data (both by source and about source) Inference-based retrieval of information Pedigree critical to maintain (but often raises the security levels) Indexing of markup important for speed of access Timelines for intelligence information. Can be long, if national Can be short, if tactical Significant Issue: Access to Data

12. Tie collection, processing, production together A common markup language will enhance collection, thus optimizing use of intel resources Producers and consumers have different ways of looking at the world; there is not necessarily a mapping between them Can consumers provide tasking to producers, via markup, of requirements on collection? Info data needs from UJTL tasks or other statement of data needs Significant Issue: Collection

13. Will DAML markup allow semantic understanding of information enough to affect releasability processes? Can we do our collection and analysis at SCI and report at lower levels (including collateral , coalition, and unclass)? Significant issue:Security

14. Military and intelligence users that particularly should hear about semantic web: DoD elements: DIA (esp JIVA), NSA Agencies: NRO, NIMA, CIA Service intel agencies: ISCOM, AFIA, ONI, MCIA Unified commands: JIC’s and JAC’s Standards setting and interoperability orgs How do organizations understand what DAML products and approaches could help them? Focused TIE’s with appropriate producers and consumers around specific value propositions Recommendations Need straightforward explanation of what DAML is and its value added (over XML)

15. Doctrine/Lessons Learned:Breakout Session Out-Brief Facilitator: Alice Mulvehill (BBN) Outline • Working Group Name: Doctrine/LL • Purpose • Significant Issues • Recommendations/Plan of Action

16. Some Common Goals • Use DAML to support user groups: • Operations: Decision support • Training • Doctrine: Both producers and consumers • User Processes: • Information (doctrine/lessons) access • Auto-generation of valid/reliable structured information • Just-in-time information delivery (post approval/verification) • Across all levels (strategic, operational, tactical) • Tailored granularity (concept, task, mission) • Usable format • Constraints: • Portable: Does not require net connection • Tools must be easy to use, inexpensive to acquire

17. Significant Issues/Needs • Process: • Tools for searching and inferencing with DAML ontologies • for context-sensitive search for given documents • for document revision and change tracking • for speeding up the markup process • Meta-tag generation • Identifying user’s granularity need (e.g., paragraph vs. task) • Approval of DAML links in doctrine generation • Bandwidth of existing info infrastructure systems, & search implications • Performance Tasks: • Representations for situation collection • Verification and editing • Trend analysis (e.g., from lessons, commonalities among METLs) • Comparative evaluations (e.g., search using DAML markup vs. not) • Product: • Provide portable/local search (e.g., not connected to SIPRNET) • Agent-based tools for exploiting DAMLized LL/doctrine • Meta-tag use

18. Questions • Can PDF files (or their indices) be DAMLized (i.e., is HTML needed)? • 2. Any existing dataspace visualization tools for viewing DAML links? • If so, what are their existing capabilities?

19. Make requested DAML tools available • e.g., Ontology generators, auto-markup tools, DAML editors • Create inferencing tools for use with DAML markup • Advertise DAML tutorial (i.e., the walk-thru example) • Request DAML tool summary at next meeting • Build ontologies for METLs (DRC) • Demonstrate the utility of DAML for applying doctrine/LL in decision support systems (Several groups) • Provide PDF mission folder examples (with indices) for experimentation re: just-in-time index generation (C. McGrath) • Test ontology creation & markup tools (M. Dietvorst w/ D. Rager) • Provide intro descriptions & system requirements of available DAML tools (A. Mulvehill) • Provide feedback/assessments to Alice on DAML tools (all) Recommendations/Plan of Action

20. Objectives Explore Command and Control Applications for DAML developments, both long and short term What are ways in which we can best explore the value of DAML for C2 functions C2 ApplicationsFacilitator – Tom Martin

21. DAML in Expeditionary Sensor Grid(ESG) for Data and Information Fusion • ESG - A sensor grid architecture that integrates sensors, networks, decision aids, warriors and supporting systems into a highly adaptive comprehensive system that operates from the surface to space and from sea to land. • Widely varying heterogeneity, thousands of sensors and sources - coalition, legacy and emerging systems and sensors • Fusion will require many more operators than practical and automation of fusion will depend on software agents • DAML Contribution • Referenced metadata regarding sensor characteristics, performance and reliability (pedigree), and decision-needs context for multiple heterogeneous sensors/sources/systems enabling high level automated (agent-based) fusion. • FY 02 ESG Enabling Experiments • Assess DAML markup utility for enhancement of fusion • Explore bandwidth overhead and scalability issues.

22. DAML in Sensor Fusion Semantic Resources Time Series Sensor Fusion Processor Sensor d specification Algorithm description… C2 Fusion Sensor c specification Algorithm description… Sensor b specification Algorithm description… Sa` Classification Confidence Localization Tracks + Event Data Sa` Sa` Sb` Sc Sd Se Szz ……... Sa` Heterogeneous Sensors Event Time/Freq, Intensity, Shape Features, Sensor Data Fixed Data Structure XML DAML Sensor Processing Stream using fixed structure, XML, and DAML

23. DAML in Sensor Fusion DATA AND INFORMATION FUSION (Client and Services?) Semantic Resources Visualization, Management Sensor c specification Pedigree Algorithm description “Unit definition” Decision Context … High Sensor b specification Pedigree Algorithm description “Unit definition” Decision Context … Impacts Sensor a specification Pedigree Algorithm description “Unit definition” Decision Context … Situation Level 3 Impact Situations Level 2 Situation Refinement Event Time/Freq, Intensity, Shape Features, Sensor Data INFERENCE LEVEL Object Base ? Level 4 Resource Refinement Level 1 Existence of object Classification Confidence Localization Tracks + Event Data DAML Object Refinement Objects ? Level 0 Signal Data Refinement Low Szz … Sc Sd Se …... Sb` HUMINT Fixed Data Structure, XML Open Source Time Series Heterogeneous Sensors and Sources Sensor Processing Stream using fixed structure, XML, and DAML

24. XML = 10x hard code DAML = 2x XML Jini/Java breakpoint By the way

25. Recommendations/Actions

26. For ESG, smart agent needed for dynamic communications management to do reasoning about the network – to support the smart agent operation, need: Comms ontology from Operational Level to Tactical Level (see next slide) Identify boundaries of sensor nets, etc. Communications

27. Ontology from Operational Level (CJTF) to tactical level (weapons on target) for supporting modeling of sensor/ communications/ information management needs Benefits to ESG Experiment design System Concept Testing Once refined, system design, and construction Ties to many many other needs Intelligence, Leverage of Doctrine/TTP/Lessons Learned/Training work Ontology Development

28. Experimentation (General) For both Communications and Fusion applications, refine the CoABS Grid DAML interfaces for Utility for Dynamic Communications Sensor Management Sensor Fusion DAML for Fusion EEE Experimentation Explore the Depth of where DAML markup makes the most sense Explore Jini/Java (I.e., Grid) object translation to DAML Research Assess DAML tools for the multiple layers from the physical to the information management Bandwidth tradeoffs, etc. Modeling DAML/assessing utility in the mobile environment Experimentation

29. Joint SWMU/GMUG/EEEMarch 25-25, 2002SPAWAR Systems Center, San Diego, CA A new approach to the Agent Based Computing Outreach to Transition Partners

30. Vision of Future Warfare Fit to ESG/Interest of Navy in Agent Based Computing Agent-Based and DARPA Fusion Technology Roles CoABS Grid Semantic Web/DAML DDB/DTT Each Program at a turning point Changes of the Military Environment Changes of Management and Organization Joint SWMU/GMUG/EEE March 25-27, 2002Background

31. Unprecedented Opportunity Fruition of DARPA Technologies Role of NWDC in ESG Experimentation FY 01 Accomplishments with CoABS Grid Interoperability Dynamic Reconfigurability Security FY 02 Plans Distributed Multiple “Real” vs. Virtual Sensors Teaming with JBI and possibly AATD Fusion efforts – DDB/AIM and DAML Joint Meeting Rationale Many of Same Participants for all Three Meetings Sharing with Those Greatest Stressing the Technologies Opportunity Joint Work on Future Joint SWMU/GMUG/EEERationale for Joint Meeting

32. Review ESG Enabling Experiment Plans Expose non-EEE Participants to key use of ABC NWDC Explore Added Opportunities for Co-evolve Emerging Technologies with New Concepts and Doctrine Adjust/Refine EEE Plans Accordingly A Forum for Sharing Grid and Semantic Web Experiences Review of Key Lessons Learned Challenges, Problems, Work-arounds Feed Back to Developers and Program Managers Explore Potential for Key ABC and Fusion Technologies to Contribute to ESG/JBI in Future Identify Potential DARPA Initiatives to Address Unsolved Technology Issues Result in actionable Plan of Action and Milestones to meet those objectives above Joint SWMU/GMUG/EEEObjectives

33. Joint meeting for all three groups Sequence Objectives and Sponsor Views ONR/NWDC Objectives DARPA – CoABS, DAML, DDB/AIM Users Reviews EEE Plans and Progress, and Grid Lessons Learned DAML Issues, NWDC Lessons Learned/Doctrine CALL Horus, AATD, CECOM, AFRL/JBI Working Groups Joint SWMU/GMUG/EEEApproach

34. 4 Focus Areas Connectivity, Interoperability, and Security (SSC and JBI Lead) Sensors, Fusion, and Representation Using DARPA Technologies (SSC Lead) Highlight DARPA Projects CoABS Grid, DAML, and DDB/AIM Agents for C2 (NWDC Lead) Ontologies for Military Use – Representation, C2, Fusion, Military Lessons Learned, Doctrine, Intelligence (NWDC Lead) Objectives Focus – Issues, Problems, Lessons Learned, Opportunities Objective, POA&M with with responsibilities, milestones, and due dates assigned Interrelated, not stove-piped approaches and solutions Joint SWMU/GMUG/EEEWorking Group Process

35. Joint SWMU/GMUG/EEEOverall Process Connectivity, Interoperability, &Security Connectivity… Sensors, Sensors, Sensors, Sensors, Fusion, Fusion, Fusion, Fusion, Objectives Sensors, … Objectives Objectives Objectives Final Briefs, Sponsor Closeout and Representation Interim Interim Interim Interim and Representation and Representation and Representation & User Review Kickoff Kickoff Kickoff Briefing Briefing* Briefing Briefing Agents in … Agents Agents Agents Agents In Command In Command In Command In Command Plenary and Control and Control and Control and Control Ontologies … Plenary Ontologies Ontologies Ontologies Ontologies Working Groups Plenary For For For For Military Use Military Use Military Use Military Use *Cross-Pollination Opportunity Working Groups

36. Joint SWMU/GMUG/EEE - Working Group Process – Interim Briefing – Cross Pollination • Connectivity, .. 2. Sensors, .. 3. Agents in C2 4. Ontologies for.. *Cross-Pollination Opportunity

37. Joint SWMU/GMUG/EEE - Working Group Process – Final POA&M’s – Interrelated • Connectivity, .. 2. Sensors, .. 3. Agents in C2 4. Ontologies for..

38. Joint SWMU/GMUG/EEESchedule Wednesday 3/27 Monday 3/25 Tuesday 3/26 AM PM

39. Joint SWMU/GMUG/EEEOutcome • Connectivity, .. Tuesday 3/26 Wednesday 3/27 2. Sensors, .. 3. Agents in C2 4. Ontologies for..