Integration of System-Dynamics, Aspect-Programming, and Object-Orientation in System Information Modeling

Contemporary information modeling of enterprise systems only focuses on the technical aspect of the systems, though it is known that they are social-technical (socio-tech) systems in essence. In fact, there are many lessons that can be learned from failures in the management of enterprise systems, which range from a small one (e.g., failure to install a printer driver) to a large one (e.g., nuclear power plant post-accident management). This paper, therefore, proposes that the enterprise system should be viewed as a socio-tech system. The paper presents a novel integrated approach to information modeling of socio-tech enterprise systems. In particular, the approach integrates object-orientation, systems-dynamics (as a means to represent high-level dynamics), and aspect-programming. The paper discusses an example to illustrate how the proposed approach works. © 2012 IEEE.published_or_final_versio

Understanding cognitive differences in processing competing visualizations of complex systems

Node-link diagrams are used represent systems having different elements and relationships among the elements. Representing the systems using visualizations like node-link diagrams provides cognitive aid to individuals in understanding the system and effectively managing these systems. Using appropriate visual tools aids in task completion by reducing the cognitive load of individuals in understanding the problems and solving them. However, the visualizations that are currently developed lack any cognitive processing based evaluation. Most of the evaluations (if any) are based on the result of tasks performed using these visualizations. Therefore, the evaluations do not provide any perspective from the point of the cognitive processing required in working with the visualization. This research focuses on understanding the effect of different visualization types and complexities on problem understanding and performance using a visual problem solving task. Two informationally equivalent but visually different visualizations - geon diagrams based on structural object perception theory and UML diagrams based on object modeling - are investigated to understand the cognitive processes that underlie reasoning with different types of visualizations. Specifically, the two visualizations are used to represent interdependent critical infrastructures. Participants are asked to solve a problem using the different visualizations. The effectiveness of the task completion is measured in terms of the time taken to complete the task and the accuracy of the result of the task. The differences in the cognitive processing while using the different visualizations are measured in terms of the search path and the search-steps of the individual. The results from this research underscore the difference in the effectiveness of the different diagrams in solving the same problem. The time taken to complete the task is significantly lower in geon diagrams. The error rate is also significantly lower when using geon diagrams. The search path for UML diagrams is more node-dominant but for geon diagrams is a distribution of nodes, links and components (combinations of nodes and links). Evaluation dominates the search-steps in geon diagrams whereas locating steps dominate UML diagrams. The results also show that the differences in search path and search steps for different visualizations increase when the complexity of the diagrams increase. This study helps to establish the importance of cognitive level understanding of the use of diagrammatic representation of information for visual problem solving. The results also highlight that measures of effectiveness of any visualization should include measuring the cognitive process of individuals while they are doing the visual task apart from the measures of time and accuracy of the result of a visual task

Integrating Visual and Mathematical Models for the Management of Interdependent Critical Infrastructures *

Abstract – Critical infrastructures provide services essential to a nation’s economy and security. These systems are now viewed as interconnected and interdependent systems that must be managed over space and time. The central problem of the present line of research is how to develop computer-based tools to support the delivery of services provided by these infrastructures. This paper draws upon visualization and modeling sciences to develop a methodology for defining a set of visualization and visual tools for monitoring and managing interdependent critical infrastructure systems. An example is used to illustrate the steps in the methodology