Shaping Problems, Not Decisions:When Decision Makers Leverage Visual Analytics

Just as modern software development strategies have introduced agile methods and rapid prototyping to organizations. Visual analytic tools now bring the same spirit of prototyping and iteration directly into the decision-making process. Yet decision makers and analysts may not yet be as “agile” as the tools they are using and instead tend to remain in their traditional roles during analytic tasks. _x000D_ _x000D_ The emerging analytic leaders are managers who do not merely act on the findings of others but rather find and shape problems by constantly interacting with data and scrutinizing and adjusting to changes in real-time data. Our research found that: 1) managers need to develop new competencies to cognitively adapt to visual decision making; 2) managers need to become more humble and share data widely across their organizations in order to facilitate a comprehensive analytic culture; and 3) roles and responsibilities of analysts and managers need to be reconsidered

Configurable nD-visualization for complex Building Information Models

With the ongoing development of building information modelling (BIM) towards a comprehensive coverage of all construction project information in a semantically explicit way, visual representations became decoupled from the building information models. While traditional construction drawings implicitly contained the visual representation besides the information, nowadays they are generated on the fly, hard-coded in software applications dedicated to other tasks such as analysis, simulation, structural design or communication. Due to the abstract nature of information models and the increasing amount of digital information captured during construction projects, visual representations are essential for humans in order to access the information, to understand it, and to engage with it. At the same time digital media open up the new field of interactive visualizations. The full potential of BIM can only be unlocked with customized task-specific visualizations, with engineers and architects actively involved in the design and development process of these visualizations. The visualizations must be reusable and reliably reproducible during communication processes. Further, to support creative problem solving, it must be possible to modify and refine them. This thesis aims at reconnecting building information models and their visual representations: on a theoretic level, on the level of methods and in terms of tool support. First, the research seeks to improve the knowledge about visualization generation in conjunction with current BIM developments such as the multimodel. The approach is based on the reference model of the visualization pipeline and addresses structural as well as quantitative aspects of the visualization generation. Second, based on the theoretic foundation, a method is derived to construct visual representations from given visualization specifications. To this end, the idea of a domain-specific language (DSL) is employed. Finally, a software prototype proofs the concept. Using the visualization framework, visual representations can be generated from a specific building information model and a specific visualization description.Mit der fortschreitenden Entwicklung des Building Information Modelling (BIM) hin zu einer umfassenden Erfassung aller Bauprojektinformationen in einer semantisch expliziten Weise werden Visualisierungen von den Gebäudeinformationen entkoppelt. Während traditionelle Architektur- und Bauzeichnungen die visuellen Reprä̈sentationen implizit als Träger der Informationen enthalten, werden sie heute on-the-fly generiert. Die Details ihrer Generierung sind festgeschrieben in Softwareanwendungen, welche eigentlich für andere Aufgaben wie Analyse, Simulation, Entwurf oder Kommunikation ausgelegt sind. Angesichts der abstrakten Natur von Informationsmodellen und der steigenden Menge digitaler Informationen, die im Verlauf von Bauprojekten erfasst werden, sind visuelle Repräsentationen essentiell, um sich die Information erschließen, sie verstehen, durchdringen und mit ihnen arbeiten zu können. Gleichzeitig entwickelt sich durch die digitalen Medien eine neues Feld der interaktiven Visualisierungen. Das volle Potential von BIM kann nur mit angepassten aufgabenspezifischen Visualisierungen erschlossen werden, bei denen Ingenieur*innen und Architekt*innen aktiv in den Entwurf und die Entwicklung dieser Visualisierungen einbezogen werden. Die Visualisierungen müssen wiederverwendbar sein und in Kommunikationsprozessen zuverlässig reproduziert werden können. Außerdem muss es möglich sein, Visualisierungen zu modifizieren und neu zu definieren, um das kreative Problemlösen zu unterstützen. Die vorliegende Arbeit zielt darauf ab, Gebäudemodelle und ihre visuellen Repräsentationen wieder zu verbinden: auf der theoretischen Ebene, auf der Ebene der Methoden und hinsichtlich der unterstützenden Werkzeuge. Auf der theoretischen Ebene trägt die Arbeit zunächst dazu bei, das Wissen um die Erstellung von Visualisierungen im Kontext von Bauprojekten zu erweitern. Der verfolgte Ansatz basiert auf dem Referenzmodell der Visualisierungspipeline und geht dabei sowohl auf strukturelle als auch auf quantitative Aspekte des Visualisierungsprozesses ein. Zweitens wird eine Methode entwickelt, die visuelle Repräsentationen auf Basis gegebener Visualisierungsspezifikationen generieren kann. Schließlich belegt ein Softwareprototyp die Realisierbarkeit des Konzepts. Mit dem entwickelten Framework können visuelle Repräsentationen aus jeweils einem spezifischen Gebäudemodell und einer spezifischen Visualisierungsbeschreibung generiert werden

Hybrid visualizations for data exploration

Information Visualization (Infovis) graphically encodes information to help a user explore a data set visually and interactively. This graphical encoding can take the form of widespread visualizations such as bar charts and scatterplots. Multiple visualizations can share the same functional space to form complete tools for visual exploration or for communicating information. There is multiple ways of combining these visualizations. The assembly of multiple visualizations can give some complex assemblies sometimes called hybrid visualizations. A hybrid visualization is the result of assembling multiple simpler visualizations. For example, NodeTrix (Henry et al., 2007a) is composed of a node-link diagram and an adjacency matrix, and MatLink (Henry and Fekete, 2007a) adds arc links to an adjacency matrix. This integration of multiple visualizations can be a way to combine their advantages into a coherent structure. The integration can be achieved, for example, through color coding, or through explicit linking (such as with arrows), or through interaction (such as when different visualizations respond to the manipulation of others). Recent literature contains several examples of new hybrid visualizations, most often to deal with complex datasets where the user can benefit from multiple, complementary visual encodings of the same data. However, to date, there is almost no theory or framework to help researchers understand and characterize existing hybrids or design new ones. This thesis advances the state of the art in hybrid visualizations in two ways: first, by developing a framework that defines and characterizes hybrid visualizations to help better identify, describe and design them, and second, by demonstrating a variety of novel hybrids. The hybrid visualizations we explored cover a wide range of possibilities. Two of the most general and widely used data types in Infovis, multidimensional multivariate data and graph (i.e., network) data, are each the subject of a chapter in the thesis, with novel hybrid visualization techniques presented for each. A wide range of possibilities for integration is also presented using a pipeline model. After some preliminary material, chapter 2 of the thesis presents a conceptual framework that defines and characterizes hybrid visualizations. This framework was itself derived from experience designing the hybrid visualizations presented in the subsequent chapters. A hybrid visualization is described as a graphical encoding using other visualizations as building blocks. We present a pipeline to illustrate the assembly of a visualization, starting from the generation of basic shapes or glyphs, then placed on a layout, embellished by adding other graphical elements, then sent to some view transform operators and assembled on the same space. Simple charts can be described with this pipeline as well as more complex assembly and new hybrids are described. Chapter 3 presents ConnectedCharts, an example of a hybrid assembled on the assembly level of the pipeline, made of multiple multidimensional and multivariate charts explicitly connected by lines or curves showing the relationship between their elements. A user interface enables the interactive assembly of ConnectedCharts, including a wide range of previously-published hybrid visualizations, as well as novel hybrid arrangements. ConnectedCharts serve as an illustration of the conceptual framework in chapter 2, by exploring possible connections between different graphics depending on the relationship of their encoded data types. Chapter 4 presents another user interface, this time for graph exploration, that incorporates several highly integrated hybrid visualizations. A Parallel Scatter Plot Matrix (P-SPLOM) is presented that constitutes a fusion of a Scatter Plot Matrix (SPLOM) and a Parallel Coordinates Plot (PCP). A radial menu called the FlowVizMenu enables the modification of a visualization integrated at the center of the menu. This menu is also used to select the dimensions for configuring a third hybrid based on an Attribute-Driven Layout (ADL) that combines a nodelink diagram and a scatterplot. The characterization of hybrid visualizations offered by the conceptual framework, as well as the illustration of the framework by innovative hybrid visualizations, are the main contributions of this thesis to the Infovis community

Understanding and Supporting Trade-offs in the Design of Visualizations for Communication.

A shift in the availability of usable tools and public data has prompted mass manufacturing of information visualizations to communicate data insights to broad audiences. Despite available software, professional and novice creators of visualizations that are intended to communicate data insights to broad audiences may struggle to balance conflicting considerations in design. Studying professional practice suggests that expert visualization designers and analysts negotiate difficult design trade-offs in creating customized visualizations, many of which involve deciding how and how much data to present given a priori design goals. This dissertation presents three studies that demonstrate how studying expert visual design and data modeling practice can advance visualization design tools. Insights from these formative studies inform the development of specific frameworks and algorithms. The first study addresses the often ignored, persuasive dimension of narrative visualizations. The framework I propose characterizes the persuasive dimension of visualization design by providing empirical evidence of several classes of rhetorical design strategies that trade-off comprehensive, unbiased data presentation goals with intentions to persuade users toward intended interpretations. The rhetorical visualization framework highlights a second trade-off: the act of dividing and sequencing information from a multivariate data set in separate visualizations for ordered presentation. I contribute initial evidence of ordering principles that designers apply to ease comprehension and support storytelling goals with a visualization presentation. The principles are used in developing a novel algorithmic approach to supporting designers of visualizations in making decisions related to visualization presentation order and structuring, highlighting the importance of optimizing for both local or “single visualization” design in tandem with global “sequence” design. The final design trade-off concerns how to convey uncertainty to end-users in order to support accurate conclusions despite diverse educational backgrounds. I demonstrate how non-statistician end-users can produce more cautious and at times more accurate estimates of the reliability of data patterns through the use of a comparative sample plots method motivated by statistical resampling approaches to modeling uncertainty. Taken together, my results deepen understanding of the act of designing visualizations for potentially diverse online audiences, and provide tools to support more effective design.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107170/1/jhullman_1.pd