Visual analytics

Recommendations for the medical treatment of patients, by a physician, can be provided as so called Clinical Guidelines. A lot of previous and current research focuses on how to integrate the computerized form of Guidelines, Computer Interpretable Guidelines into clinical practice. Such an integration could be used to provide real time-decision support. The retrospective analysis of adherence to a guideline is also an area of interest. Such an analysis provides insight into guideline quality in terms of treatment success and the general acceptance of the guideline by healthcare professionals. Medical studies are often conducted with a cohort, which is a group of patients who share a common characteristic. In case of this thesis, the commonality is that all patients of the cohort received the same treatment recommended by the guideline we want to evaluate. The goal of our thesis is to enable a retrospective visual analysis of the treatment data of a whole cohort. Furthermore the information is not only visualized but also interaction techniques are provided to the user, to enable exploratory analysis. We extended techniques for single patients and also implemented new approaches for the visualization of all measurements of certain clinical parameters as well as the executed actions and adherence to a guideline by healthcare professionals. For both distinct types of data we developed one visualization technique that aggregates the information and another one that keeps as much detail as possible for each patient. State of the art visualizations for guideline and statistical compliance information were extended to handle the accumulated data within a cohort. The result is a fully functional prototype based on the Java Programming Language and the Prefuse visualization framework. All developed visualization techniques were implemented in the prototype and are available for use. In an evaluation with a domain expert we assessed the usability of the techniques and visual encodings. We found out, that they are mostly intuitive and understandable. Some of them are harder to grasp but only short introductions were necessary for the expert to properly use them as well. During the conduction of the thesis and the evaluation we were able to identify approaches and ideas for subsequent future research and present them briefly.

efficiently store network structured data. But while plenty of research has gone into the development of this technology, querying for a subset of the data is lacking user friendly interfaces. Of the two main query methods, graph pattern matching and graph traversal, the first has received more attention and more methods providing visual support in querying are available. The latter, graph traversal, while being very powerful, has seen little advances in visual querying. This thesis aims at providing a novel user interface for graph traversal query formulation - a visual query language for graph databases - entitled Pygmalion Query. In the thesis, first a literature review is undertaken to discover any previous approaches taken at such a visual query language. With it, gaps in the currently available research are identified. Following the literature review, needs and requirements are identified from different sources, such as queries posted online and documentation for graph traversal query languages. After selection of minimum required features, the design for Pygmalion Query is created. A web-based implementation, built on available frameworks, is implemented. Following the creation of Pygmalion Query, a twofold evaluation is conducted. An expert review serves as the initial confirmation of the approach taken. Using feedback coming from the experts, an updated implementation is created. A small comparative user study is carried to test for usability. The results of the expert review and user study indicate a positive usability effect of Pygmalion Query in the formulation of graph traversal queries over the currently available solutions. The participants of the study, in greatest part novice users, are more likely to complete the tasks posed to them with the visual query language.

Information present in resumes has temporal as well as spatial dimensions, such as a person¿s work experience or education. This information by itself is comprehensible - it is very clear when, where, and for how long a person has worked or studied. It becomes increasingly difficult to maintain a clear overview when comparing multiple resumes, specifically their chronological information. Navigating back and forth between resumes, switching between views and attempting to compare every single event is highly inefficient. The most common and intuitive way to compare events from multiple resumes, would be to view them in a side-by-side fashion. Many similarities can be quickly recognized by doing this, but in cases where more than two resumes need to be compared simultaneously, the overview becomes cluttered, the amount of information increases substantially and comparing events becomes a difficult task. We propose the design and implementation of a web application - CV3 - that is capable of comparing multiple chronologies and visualizing the output in a clear manner, whilst maintaining a clean overview. Our approach supports users in filtering timeline events across all resumes, recognizing and extracting relevant information from resumes and visualizing their similarities efficiently in a single overview.

This work has as its main focus the creation of resumes, how they are integrated into the hiring process, and how visual resumes play into the current world of recruitment and applications. On the side of applicants, there is a trend to create visualised resumes in the form of infographics whereas the recruiting side employs more and more automation technology that extracts the information contained in regular resumes and on social media sites in order to have to spend less time and therefore money on individualised resumes. Instead of viewing both these sides as opposites, this research tries to unify them and design a system that appeases both. The challenge is to find a way to create and use a new and innovative form of resume that benefits both recruiters and applicants. A new global specification created within a Community Group at the World Wide Web Consortium as well as a rudimentary implementation that can evolve into a rich ecosystem using that specification are introduced. Research for the topic had to be conducted from three different angles: the state of the art in research regarding recruitment and resumes, the state of the art in the industry, and currently existing resume standards, including the question whether they are suitable for the next-generation resume we are proposing. We are defining the core points of this next-generation resume that we labelled CV 2.0 and are proposing ways to reach a greater adoption of this resume in the future.

Data wrangling generally denotes the cumbersome task of making data useful for analysis. Usually, this means applying hand-crafted scripts, requiring at least a certain degree of technical expertise. In order to make suchlike data preparation accessible for rather casual users as well, we have built a visual analytics prototype in the context of this thesis, easing related tasks. Our approach is an interdisciplinary one, combining contemporary concepts and ideas from various fields: human-computer interaction and usability engineering with information retrieval, data mining, machine learning, plus information visualization. In particular we focus on supporting transformations of time-oriented data since this kind of data exhibits unique characteristics which demand for special consideration. After analyzing related state of the art we identified open issues and derived requirements for such a system. We followed an iterative design process to develop a software prototype called TempMunger, in an agile manner. The process as well as corresponding artifacts are documented and presented in this thesis. Our prototype is a web-based application, tailored for desktop browser usage. More concretely, it offers interactive dashboard visualizations for preferably intuitive and exploratory transformation operations of time-oriented data. A qualitative evaluation of the prototype demonstrates its usefulness and reveals opportunities for future work. Concluding it is safe to say that data wrangling continues to be an exciting field of research where much is yet to be discovered.

As companies gather more and more data, we need to find a way to allow interested decision makers to access this data in an efficient way. In the context of sports practice, users could benefit from suggestions about new sports they could try out and the company could increase its sales. This work aims to support the analysts, simultaneously domain experts and IT laymen, in their data exploration and suggestion retrieval tasks through a user friendly interface, abstracting away the complexity of formulating expressive queries into the visual domain. We present a characterization and task analysis for this domain, and a prototype that meets the requirements emerging from them, based on an interdisciplinary literature research. The resulting prototype combines a visual query language with a collaborative filtering approach to render suggestions for new activities, and show multiple types of relationships in a visually compelling way. It has been implemented as a web application that handles the transformation of user input from a graphical pattern into a database query language and the results of this query into an easy to digest information representation. We conclude with an expert interview to validate the design for analysis and exploration.

More and more hospitals have been switching from paper-based patient records to electronic health records within the last years, which introduced new challenges for healthcare professionals. Each electronic record can hold a vast amount of diverse data, which can easily overwhelm a clinician in the stressful environment of a hospital. Consequently, important information can easily be missed or misinterpreted. These effects are especially critical for medication data, as medication errors can harm the treated patient directly. Proper information visualization is able to address these issues by providing cognitive support to healthcare professionals and facilitating insight into health records. The objectives of this thesis were to design a visualization of patient-specific medication histories and to implement an interactive prototype, which can be used in daily treatment settings. For this purpose, the characteristics and use cases of existing projects addressing