In this research note, we examine the design, development, validation, and use of virtual worlds. Our purpose in doing so is to extend the design science paradigm by developing a set of design principles applicable to the context of virtual environments, particularly those using agent-based simulation as their underlying technology. Our central argument is that virtual worlds comprise a new class of information system, one that combines the structural aspects of traditional modeling and simulation systems in concert with emergent user dynamics of systems supporting emergent knowledge processes. Our approach involves two components. First, we review the characteristics of agent-based virtual worlds (ABVWs) to discern design requirements that may challenge current design theory. From this review, we derive a set of design principles based on deep versus emergent structures where deep structures reflect conventional modeling and simulation system architectures and emergent structures capture the unpredictable user-system dynamics inherent in emergent knowledge processes, which increasingly characterize virtual worlds. We illustrate how these design challenges are addressed with an exemplar of a complex mirror world, a large-scale ABVW we developed called Sentient World. Our contribution is the insight of partitioning ABVW architectures into deep and emergent structures that mirror modeling systems and emergent knowledge processes respectively, while developing extended design principles to facilitate their integration. We conclude with a discussion of the implications of our design principles for informing and guiding future research and practice.
Development of large-scale models often involves-or, certainly could benefit From—linking existing models. This process is termed model integration and involves two related aspects: (1) the coupling of model representations, and (2) the coupling of the processes for evaluating, or executing, instances of these representations. Given this distinction, we overview model integration capabilities in existing executable modeling languages, discuss current theoretical approaches to model integration, and identify the limiting assumptions implicitly made in both cases. In particular, current approaches assume away issues of dynamic variable correspondence and synchronization in composite model execution. We then propose a process-oriented conceptualization and associated constructs that overcome these limiting assumptions. The constructs allow model components to be used as building blocks for more elaborate composite models in ways unforeseen when the components were originally developed. While we do not prove the sufficiency of the constructs over the set of all model types and integration configurations, we present several examples of model integration from various domains to demonstrate the utility of the approach.