• establishing simple first order relationships among real world situational and environmental entities
• tracking their “status,” primarily location and activities
• providing relatively unsophisticated estimations that evaluate current or short-term future status

Supported operations definable with these computational tools have limited, simple objectives, again related to physical entities (adversaries, their organization, their operations). Indeed, most of the computational support is focused on such entities. We are only just beginning, for example, to consider the consequences and impacts of activities in one dimension of operations (say, military) against others (political, social, economic). Even there, the relationships are delimited by the simplicity of the data and knowledge development and management techniques in our toolsets, where complex cross-issues cannot adequately be addressed by the computational framework.

The operational context for national security operations is, however, far more complex, and exhibits all the characteristics defined by chaos theory (which is expected, as all leading military theorists describe the operational context as complex adaptive systems). We are mostly operating in that boundary between order and chaos, where concepts and perceptions are ultimately as important, if not more important, than grounded truth. The paucity of tools, conceptual baselines, and underlying theory forces the development of unique, hard-coded algorithms with limited range and scope to even begin to address the complexity (an example: the discrete dimensional models, at best very loosely connected, envisioned for Operational Net Assessment).

One of the best examples of the need for more advanced capabilities that allow us to operate in that range of complexity between chaos and order is found in Operation Iraqi Freedom, and in the continuing counter-insurgency and war on terror taking place in Iraq. In order to effectively (to use a word) deter, and even anticipate and preempt, the insurgency and terrorist operations, it is necessary to identify, if possible, a pattern of such operations and the potential perpetrators. To that end, it is necessary to identify which organization is truly responsible for some act. This requires being able to measure the potential relationship of an event to an organization or its constituent elements.

As many of the events are similar (homicide bombings, improvised explosive devices (IED), kidnappings, executing government agents), one must develop a concept that relates aspects of events, conditions, and behavior to one or another group (al Qaeda in Iraq, Sunnah, Baathist sympathizers, Sunni malcontents, old Iraqi security forces, Ansar al Islam). This leads to the development of a measure called “Zarqawiness,” which is independent from the leader of al Qaeda in Iraq, but is representative of his organization’s actions.

Our current database technologies are not sufficiently rich to permit conditional, probabilistic assessments of actions relative to somewhat nebulous characteristics that adapt and morph over time. These assessment require higher order logic to be able to use templates of knowledge, i.e., metaknowledge, as part of the computational processes. They require knowledge management of a varying set of metrics, that is, parameters that describe events and are themselves linked to identify subtle, nuanced patterns of behavior. The “Zarqawiness” factor can coexist as a measure of an event with a “Baathness” factor, where the sum of its respective probabilistic assessments is not necessarily one.

In developing a cohesive, integrative, and holistic framework for national security operations, it will be necessary to stretch beyond the limitations of existing technologies and concepts to accommodate the complexity and chaos that is out there.