The Challenge: A Picture of Objects Is Not Awareness

An unattended ground sensor reports three wheeled vehicles at location L, moving due east at 25 kph. Nothing in that report says whether they matter. Whether they matter is a relation — between those vehicles, the mission, the terrain, the civilians, and the enemy's order of battle — and relations are not measured. They are derived.

Fusion doctrine has a name for the gap. Level-one processing gives you objects and their properties: tracks, positions, velocities, equipment types. Situation assessment — level two — is the estimation of the relations among those entities. Every fielded common operational picture is very good at the first and mostly silent about the second, and the second is where command decisions are actually made. VIStology's most-cited paper puts the reason for that gap in a single sentence:

“While it is typical that information about objects (or at least their properties) can be experienced, or observed directly, the relational information must be inferred.”

The consequence is that awareness cannot be bought by adding sensors. It has to be reasoned to — and the reasoning needs knowledge the sensor does not have. The paper's own illustration is a person watching a game whose rules they have never learned: they can see exactly where every player and the ball is, and still have “no idea of ‘what is going on’.” Perception without background knowledge is not awareness.

Our Approach: What a Situation Is, Formally

A situation is not a picture; it is a fragment of the world — objects standing in relations that bear on a goal. VIStology formalized that claim in the Situation Theory Ontology: an infon is a relation, its objects, and one explicit polarity bit; a situation supports the infons that hold in it; and relevance is part of the model itself, decided by the mission’s question. Recognizing a situation then becomes classification — a job a reasoner can do — and the ontology is the interlingua between the human’s mental model and the machine’s.

That formal core carries two use cases, each with its own page and its own record: the reference system that puts derived relations in front of a commander, and the relevance reasoning that returns exactly the facts a question needs. None of the papers in this cluster reports a quantitative evaluation — each use-case page states what was demonstrated and what was not.

Proof Points

This is a body of work whose proof is authority, not benchmark — and we would rather say so than dress it up. Not one paper in this cluster reports an evaluation. What they establish is who defined the problem, who built the reference system, and whose names are on the byline.

Flagship

We Wrote the Definition the Field Cites

Ontology-Based Situation Awareness (Information Fusion, Elsevier) is the most-cited work in VIStology's corpus — 295 citations. Its self-declared contribution is “a computer-processable semantics for situation theory,” compatible both with Barwise's situation theory and with Endsley's model of human situation awareness: situations, objects, n-ary relations, infons with explicit polarity, attributes with units, and the relevance and focus relations that decide which facts bear on a situation. It is a formalization paper — no system, no experiment, no numbers, and we will not imply any. The citation count is the result: the community took it as a reference point.

Endsley

Co-Authored with the Author of the Canonical Model

VIStology's president, Mieczyslaw Kokar, co-authored Situation Awareness and Cognitive Modeling in IEEE Intelligent Systems with Mica R. Endsley, president of SA Technologies and originator of the three-level model of situation awareness — perception, comprehension, projection — that the field runs on. The article sets out what a computer model of situations must have if it is to reach the awareness humans reach, and puts a logic-based ontology of situations on the table as one answer. To be exact about what it is and is not: it is a co-authored article laying out requirements. Endsley evaluates, uses and endorses no VIStology technology in it, and we do not claim she does.

Assurance

Explainability, Written with the Army in 2006

Two decades before AI assurance became a mandatory paragraph in defense solicitations, the FUSION 2006 requirements list — item seven, added by the authors themselves — said this: “If the system is unable to provide some transparency into its reasoning process and assure the user its interpretations are plausible, the system is unlikely to be trusted and thus unlikely to be used.” The same list calls for abductive generation of multiple plausible interpretations from incomplete knowledge, and for ranking them by economy, accumulated certainty, and the threat they imply. We can answer the transparency paragraph of a modern solicitation with a citation, not a promise.

Selected Publications

The peer-reviewed record behind VIStology's situation-awareness and command-and-control practice.

Ontology-Based Situation Awareness

Kokar, M.M., Matheus, C.J. & Baclawski, K.

Information Fusion 10(1):83-98

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SAWA: An Assistant for Higher-Level Fusion and Situation Awareness

Matheus, C.J., Kokar, M.M., Baclawski, K., Letkowski, J., Call, C., Hinman, M., Salerno, J. & Boulware, D.

SPIE Conference on Multisensor, Multisource Information Fusion (2005)

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Inferring Relations and Individuals Relevant to a Situation: An Example

Kokar, M.M., Shin, S., Ulicny, B. & Moskal, J.J.

2014 IEEE Conference on Cognitive Situation Management (CogSIMA 2014)

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Situation Awareness and Cognitive Modeling

Kokar, M.M. & Endsley, M.R.

IEEE Intelligent Systems 27(3):91-96

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Understanding the Role of Context in the Interpretation of Complex Battlespace Intelligence

Powell, G.M., Matheus, C.J., Kokar, M.M. & Lorenz, D.

FUSION 2006

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See the full list of VIStology publications →

Make the Relations Computable

If your operational picture shows objects and your commanders need to know what is going on among them, we can help you model the situations that matter and build the reasoning that recognizes them.

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