1 / 21

A Core Ontology for Situation Awareness

A Core Ontology for Situation Awareness. Christopher J. Matheus Versatile Information Systems, Inc. Mieczyslaw M. Kokar Kenneth Baclawski Northeastern University/VIS. Acknowledgments. Contract: F30602-02-C-0039 Michael L. Hinman, AFRL/IFEA John Salerno, AFRL/IFEA

axelle
Download Presentation

A Core Ontology for Situation Awareness

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A Core Ontologyfor Situation Awareness Christopher J. Matheus Versatile Information Systems, Inc. Mieczyslaw M. Kokar Kenneth Baclawski Northeastern University/VIS

  2. Acknowledgments Contract: F30602-02-C-0039 Michael L. Hinman, AFRL/IFEA John Salerno, AFRL/IFEA Contractor: Versatile Information Systems, Inc. Fusion’2003, Cairns Matheus, Kokar, Baclawski

  3. Objectives • Show a core ontology for situation awareness (SAW Ontology) • Show alternative designs of SAW Ontology • Show how SAW Ontology can be extended to satisfy specific requirements Fusion’2003, Cairns Matheus, Kokar, Baclawski

  4. The Situation Awareness Problem • Knowing states of objects doesn’t necessarily mean understanding what’s going on (football) • Examples: close_to, under_attack, retreating, operational_readiness, …. • Need information about multiple objects,history, background knowledge, context, evolution over time…. • Need to derive relationships (no direct measurements) • Which ones? • 100 objects  210000 possible relations! • Need a theory of how the world “works” in a given context (ontology, situation) Fusion’2003, Cairns Matheus, Kokar, Baclawski

  5. SAW Definition Situation Awareness (SAW) is the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future. - Endsley & Garland, 2000 Fusion’2003, Cairns Matheus, Kokar, Baclawski

  6. Situations – First Class Citizens “One of the starting points for situation semantics was the promotion of real situations from second class citizens to first class citizens.” “By a situation, then, we mean a part of reality that can be comprehended as a whole in its own right – one that interacts with other things. By interacting with other things we mean that they have properties or relate to other things.” - John Barwise, The Situation in Logic, 1989 Fusion’2003, Cairns Matheus, Kokar, Baclawski

  7. Informal SAW Definition Situation Awareness is knowledge of the following elements: • Goal (for the level of decision making); • Theories of the world (ontology); • Knowledge of which theories in the ontology are relevant to the Goal at time t (current time) and at t+1 (in the near future); • Objects that are relevant to the Goal at time t and t+1; and • Relations among the objects that are relevant to the Goal at time t and t+1. Fusion’2003, Cairns Matheus, Kokar, Baclawski

  8. Core SAW Ontology Fusion’2003, Cairns Matheus, Kokar, Baclawski

  9. Attribute Values and Events Fusion’2003, Cairns Matheus, Kokar, Baclawski

  10. “Snapshot” Design • Everything is captured for each time instant • Advantage: easy to retrieve (by time index) • Disadvantages: • Keep records even if nothing changes • Information must arrive in lock-step fashion (fixed delta-t) Fusion’2003, Cairns Matheus, Kokar, Baclawski

  11. Time-Interval Design • Attributes and relations for arbitrary time intervals • Problem: where to keep uncertainty info for relations? • Relation – would be constant over time • Time Interval – would be the same for all relations Fusion’2003, Cairns Matheus, Kokar, Baclawski

  12. Property Value with Certainty • Uncertainty part of Relations and Attributes through PropertyValue • Problem: PropertyValues are associated with time events and not arrival of new information Fusion’2003, Cairns Matheus, Kokar, Baclawski

  13. Event Notices • PropertyValues are associated with EventNotices, i.e., with arrival of new information (e.g., Level 1 events) Fusion’2003, Cairns Matheus, Kokar, Baclawski

  14. Battlefield Scenario Fusion’2003, Cairns Matheus, Kokar, Baclawski

  15. SAW Ontology Extensions • Q: Is Core SAW Ontology sufficient to represent this scenario? • A: No. • Q: Can it be extended, or would it need to be changed? • A: It needs to be extended Fusion’2003, Cairns Matheus, Kokar, Baclawski

  16. Battlefield Ontology Fusion’2003, Cairns Matheus, Kokar, Baclawski

  17. Battlefield Obstacle Ontology Fusion’2003, Cairns Matheus, Kokar, Baclawski

  18. Battlefield Relation Ontology Fusion’2003, Cairns Matheus, Kokar, Baclawski

  19. SAW Process Flow Fusion’2003, Cairns Matheus, Kokar, Baclawski

  20. Summary of the Process • Possess a Theory of the World, TO, consisting of a number of interrelated theories T1, T2, T3… and specify all of them in a formal language. • Post a Goal Tg in terms of the formal language. • Demonstrate the process of selecting relevant theories, T1, T2, T3…from among the theories of the world. • Collect events W1, W2, W3… and specify them in a formal language. • Specify (in the formal language) and then select relevant models, M1, M2, M3… of the relevant theories. • Combine the relevant theories (theory fusion) within the formal methods tool (Specware) using the category theory operator of colimit. • Similarly, combine the relevant models (model fusion) so that the combined model satisfies the combined theory from step 6 above. • Prove/disprove the Goal theorem using the combined theory. This proof includes the fusion of: • a. theories • b. models • c. uncertainty. Fusion’2003, Cairns Matheus, Kokar, Baclawski

  21. Conclusions • Showed a core SAW Ontology • Analyzed alternative approaches • Showed extensibility of the ontology to more complex scenarios • Discussed the SAW process • More research needed on: SAW case studies, ontology extensions (agree to use the same ontologies), ontology tools – especially efficient reasoners Fusion’2003, Cairns Matheus, Kokar, Baclawski

More Related