Towards an automated system for evaluation of visualizations

The Information Visualization field focuses on the visualization of abstract data, and with the growing interest in big data analysis, the need for analyzing complex datasets is nowadays highly relevant. With the growing amount and diversity of these datasets new and exciting ways to visualize them are being developed. However, being able to thoroughly test and evaluate the effectiveness of these new visualization techniques is an arduous manual process. Moreover, different researchers hold different opinions on how to thoroughly evaluate a new visualization method. A step towards automating the process of evaluation of visualizations, called the Framework for the Evaluation of VizTools (FEV), was developed and is presented in this thesis. The FEV Framework combines, guidelines, scenarios, and tasks, generated by an extensive literature review, into an easy to use open-source and expandable software package. With FEV, researchers are able to generate evaluation task lists based on their own data, and using evaluation methods that have already been vetted by the visualization community. By using the FEV tool with a variety of visualizations, it was possible to generate full evaluation task lists for each of them. By making the framework open-source and with an adaptable architecture, new functionality can easily be added, enabling it to be used by researchers to evaluate an almost limitless number of visualization methods

Modeling Construction Competitive Bidding: An Agent-Based Approach

The construction industry is a complex, multi-level system that includes a large collection of independent, heterogeneous organizations and institutions and is associated with several economic sectors and markets. Because of its unique characteristics, the construction industry as one of the major economic sectors and contributors to the economic development of the nation needs its own specific and dedicated economics. The shortcomings of the existing methodologies call for the use of more sophisticated modeling tools that can capture more important aspects of the real world and its complexity in particular the interconnections among elements of the system, their idiosyncrasies, and emergent behavior. As a pioneer attempt in the exploration of a new theory of construction economics, this study aims to found the first building blocks of the comprehensive economic model of the construction industry. In this dissertation, an agent-based approach is applied to model the low-bid lump-sum construction competitive bidding by which most construction works are allocated. This model has several advantages over the previous analytical and empirical models including the capability of observing the bidding process dynamics, the interaction between the heterogeneous and learning agents, and the emergent bidding patterns arising from multiple scenarios of market conditions and contractors’ attributes. Then the model is used as a virtual laboratory for conducting a variety of experiments to answer several important research questions in the field of construction economics. The main research objectives of this study are to: (1) analyze the effectiveness of major quantitative methods in the bidding environment under a variety of market conditions (2) study the effect of contractors’ risk behavior, cost estimating and project management skills, and complexity of projects on contractors’ choice of optimal markup, long-term financial growth and market share (3) investigate the impact of risk behavior and need for work on contractors’ performance. The results presented in this dissertation offer new understandings and insights on the construction bidding environment and recommendations for both owners and contractors’ competitive success, which are not available using conventional approaches. In particular, results suggest that (1) using Friedman model can result in considerably higher market share whereas using Gates model can result in higher profit per project, (2) the optimal policy for contractors is moderation in both dimensions of risk attitude and need for work, (3) the comparative performance of slightly and extremely risk averse contractors are depending on level of cost estimating accuracy and project execution skills of contractors as well as the level of project complexities