Semantic Web for the Military User Intelligence Breakout Session Dr. Joe Rockmore/Cyladian Technology Consulting
Participants Elaine Marsh/NRL Frank Muller/BBN Paul Kogut/Lockheed-Martin Joe Rockmore/Cyladian
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?
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
Semantic Web Functional Architecture Browsing Visualization Q & A Etc. Docs User interactions Markup Markup Markup { DAML } KB DBs Map Map Map Analyses Ont dev
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
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.) Relative time (before, after, within, overlapping, close to, etc.) Coreference problems in geolocations and times
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
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
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
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]
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)