From Information to Choice: A Critical Inquiry Into Visualization Tools for Decision Making

In the face of complex decisions, people often engage in a three-stage process that spans from (1) exploring and analyzing pertinent information (intelligence); (2) generating and exploring alternative options (design); and ultimately culminating in (3) selecting the optimal decision by evaluating discerning criteria (choice). We can fairly assume that all good visualizations aid in the intelligence stage by enabling data exploration and analysis. Yet, to what degree and how do visualization systems currently support the other decision making stages, namely design and choice? To explore this question, we conducted a comprehensive review of decision-focused visualization tools by examining publications in major visualization journals and conferences, including VIS, EuroVis, and CHI, spanning all available years. We employed a deductive coding method and in-depth analysis to assess if and how visualization tools support design and choice. Specifically, we examined each visualization tool by (i) its degree of visibility for displaying decision alternatives, criteria, and preferences, and (ii) its degree of flexibility for offering means to manipulate the decision alternatives, criteria, and preferences with interactions such as adding, modifying, changing mapping, and filtering. Our review highlights the opportunities and challenges and reveals a surprising scarcity of tools that support all stages, and while most tools excel in offering visibility for decision criteria and alternatives, the degree of flexibility to manipulate these elements is often limited, and the lack of tools that accommodate decision preferences and their elicitation is notable. Future research could explore enhancing flexibility levels and variety, exploring novel visualization paradigms, increasing algorithmic support, and ensuring that this automation is user-controlled via the enhanced flexibility levels

Acadia Visitor Study: A Mobile Tracking Application

Visitor congestion is an issue in Acadia National Park, as it is the most densely visited national park in the United States. We addressed this problem with a visitor tracking cell phone application. The data collected from the application aims to aid the park in efficiently using their limited resources. We tracked WPI students and administered a survey to park visitors. We then visualized all of the data into intuitive formats. Finally, we generated three ways for the park to deploy the project in various capacities

Preliminary Study of Communication Network Characterization Towards Improved Organizational Behavior

Nearly one third of the Air Force acquisition system’s large programs are over cost and half are over budget; performance must improve. This research applies a systems perspective to this challenge and frames the acquisition system as a complex system of systems. It is a system composed of people in multiple organizations; organizations interacting with one another to develop, acquire and sustain weapon programs. The system’s performance is an emergent behavior of its components (people), structure and processes. Communication networks are a view of a system’s structure, revealing the flows and interactions between components (people) as the system accomplishes its functions. Literature demonstrates that these networks are key to the effective performance of various system functions (ex. innovation). Further, established methods in organization behavior literature allow for characterization of these networks. Yet, limits to existing methods reduce their utility. This research validates a method to characterize communication networks within large technical organizations. This research compares communication network mapping with two separate data sources: interviews (existing) and archival e-mail log files (new). Ego-centric networks for five volunteers are characterized with both data sources and compared via case study methods. This research makes three contributions. First, it demonstrates the effect of archival data inclusion on the observed network completeness. Second, it compares the content of the networks observed with both data sources. Third, it compares established network measures obtained with both data sources. Future research can leverage this method validation to explore the use of e-mail-based network characterization to improve organizational performance