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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.

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Semantic web for the military user

Semantic Web for the Military User

Intelligence Breakout Session

Dr. Joe Rockmore/Cyladian Technology Consulting


  • Elaine Marsh/NRL

  • Frank Muller/BBN

  • Paul Kogut/Lockheed-Martin

  • Joe Rockmore/Cyladian


  • 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
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







Semantic Web Functional Architecture

  • Browsing

  • Visualization

  • Q & A

  • Etc.




{ DAML }




Ont dev

Intelligence ontologies vice c2 logistics or others
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
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

Significant issue markup tools
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
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
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
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]


  • 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)