Visual representation of construction management data

Construction projects are associated with voluminous and often unstructured data sets, generated in support of construction management functions. Project managers face the challenge of making meaningful deductions from this data. A central contribution of this paper is that visual analytics can provide a means of analyzing data from various dimensions of a project to extract information in aid of decision making and helping to explain reasons for performance to date. Questions posed relate to the role of visual analytics in the execution and post-construction phases of a project, data representations and transformations of specific interest, and the kinds of visual representations and interactions that provide useful insights to management personnel, help explain performance, or assist with communication. Principles of designing effective visual analytics solutions for various construction management functions and applicable to the associated analytic reasoning tasks, data representations and transformations, and visual representations including relevant interaction features are described. Emphasis is placed on the choice of visual representations along with discussion of approaches for validating the usefulness of the visual analytics solutions proposed. The notion of context dimensions and performance dimensions for representing construction projects is introduced as part of the formulation of visual representation designs. To demonstrate the application of the concepts presented, data sets from two different projects were used to produce visual representations helpful for analytical reasoning about change order management data. A detailed assessment is given of several of the images presented in terms of strengths and weaknesses, and interaction features desired. The findings of the paper in terms of principles, concepts and lessons learned should prove helpful to those wishing to apply visual analytics to a broad range of construction management functions. (c) 2009 Elsevier B.V. All rights reserved.