TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy

We introduce TempoCave, a novel visualization application for analyzing dynamic brain networks, or connectomes. TempoCave provides a range of functionality to explore metrics related to the activity patterns and modular affiliations of different regions in the brain. These patterns are calculated by processing raw data retrieved functional magnetic resonance imaging (fMRI) scans, which creates a network of weighted edges between each brain region, where the weight indicates how likely these regions are to activate synchronously. In particular, we support the analysis needs of clinical psychologists, who examine these modular affiliations and weighted edges and their temporal dynamics, utilizing them to understand relationships between neurological disorders and brain activity, which could have a significant impact on the way in which patients are diagnosed and treated. We summarize the core functionality of TempoCave, which supports a range of comparative tasks, and runs both in a desktop mode and in an immersive mode. Furthermore, we present a real-world use case that analyzes pre- and post-treatment connectome datasets from 27 subjects in a clinical study investigating the use of cognitive behavior therapy to treat major depression disorder, indicating that TempoCave can provide new insight into the dynamic behavior of the human brain

An Analysis of Machine- and Human-Analytics in Classification

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that amy be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics

The State-of-the-Art of Set Visualization

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

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

Visualisation of Large-Scale Call-Centre Data

The contact centre industry employs 4% of the entire United King-dom and United States’ working population and generates gigabytes of operational data that require analysis, to provide insight and to improve efficiency. This thesis is the result of a collaboration with QPC Limited who provide data collection and analysis products for call centres. They provided a large data-set featuring almost 5 million calls to be analysed. This thesis utilises novel visualisation techniques to create tools for the exploration of the large, complex call centre data-set and to facilitate unique observations into the data.A survey of information visualisation books is presented, provid-ing a thorough background of the field. Following this, a feature-rich application that visualises large call centre data sets using scatterplots that support millions of points is presented. The application utilises both the CPU and GPU acceleration for processing and filtering and is exhibited with millions of call events.This is expanded upon with the use of glyphs to depict agent behaviour in a call centre. A technique is developed to cluster over-lapping glyphs into a single parent glyph dependant on zoom level and a customizable distance metric. This hierarchical glyph repre-sents the mean value of all child agent glyphs, removing overlap and reducing visual clutter. A novel technique for visualising individually tailored glyphs using a Graphics Processing Unit is also presented, and demonstrated rendering over 100,000 glyphs at interactive frame rates. An open-source code example is provided for reproducibility.Finally, a novel interaction and layout method is introduced for improving the scalability of chord diagrams to visualise call transfers. An exploration of sketch-based methods for showing multiple links and direction is made, and a sketch-based brushing technique for filtering is proposed. Feedback from domain experts in the call centre industry is reported for all applications developed