The High Level Architecture Object Model Template (HLA OMT) supports simulation interoperability by providing a Federation Object Model (FOM) to formally describe the information interchange (objects, object attributes, interactions, and interaction parameters) within a simulation federation. Information used by a single federate within the federation is defined by the Simulation Object Model (SOM).

Often the federate SOMs are mutually incompatible, so standing up a federation typically requires a tedious process of modifying the simulation federates to conform to the proposed FOM. A variety of agile FOM techniques have been proposed to facilitate this integration process.

From the simulation data logging and analysis perspective, there is an analogous problem of adapting the analysis tools to particular federations. Data analysis tools are designed in accordance with the analysts' notion of Measures of Effectiveness (MOE) and Measures of Performance (MOP). Often these measures are not directly compatible with respect to the underlying federation object model. This is especially troublesome for the lower-level MOP, which must have common characteristics with the logged FOM data.

This paper presents a two-layered framework that supports the agile adaptation of analysis tools to specific federations. The top semantic layer provides a modeling framework to capture concepts that analysts tend to use. The concepts include measurements and dimensions. Examples of dimension include object classifications, time, and geographic containment. The lower syntactic layer describes how to map the particular federation object models to more abstract semantic concepts. In addition, we show how this approach supports reuse by taking advantage of the hierarchical nature of the object models. These concepts are now being successfully implemented and evaluated in the Joint Forces Command Urban Resolve 2015 experiment.