Semantic Web for the Military User

1. Semantic Web for the Military User Intelligence Breakout Session Dr. Joe Rockmore/Cyladian Technology Consulting

2. Participants • Elaine Marsh/NRL • Frank Muller/BBN • Paul Kogut/Lockheed-Martin • Joe Rockmore/Cyladian

3. 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?

4. Value Propositions • Consumers = custom products; producers = get credit for production • Partial automation of analysis tasks (helps info overload) • Consolidation of data (structured and unstructured) • Supports collaboration across orgs by common understanding (via ontologies and inference making) • Publish once, derived products • Better extraction of information & “query mining” • Feedback on missing information, including to collection management

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

6. Intelligence Ontologies(vice C2, logistics, or others) • .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

7. Significant Issue: Geolocation & Temporal Representation • 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.) • Coreference problems in geolocations and times

8. Significant Issue: Markup Tools • 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

9. Significant Issue: Access to Data • 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

10. Significant Issue: Collection • 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

11. Significant issue:Security • 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)? • [other issues]

12. Recommendations • 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 Need straightforward explanation of what DAML is and its value added (over XML)