Collection understanding shifts the traditional focus of retrieval in large collections from locating specific artifacts to gaining a comprehensive view of the collection. Visualization tools are critical to the process of efficient collection understanding. By presenting simple visual interfaces and intuitive methods of interacting with a collection, users come to understand the essence of the collection by focusing on the artifacts. This thesis discusses a practical approach for enhancing collection understanding in image collections.

Large data sets are difficult to analyze. Visualization has been proposed to assist exploratory data analysis (EDA) as our visual systems can process signals in parallel to quickly detect patterns. Nonetheless, designing an effective visual analytic tool remains a challenge. This challenge is partly due to our incomplete understanding of how common visualization techniques are used by human operators during analyses, either in laboratory settings or in the workplace. This thesis aims to further understand how visualizations can be used to support EDA. More specifically, we studied techniques that display multiple levels of visual information resolutions (VIRs) for analyses using a range of methods. The first study is a summary synthesis conducted to obtain a snapshot of knowledge in multiple-VIR use and to identify research questions for the thesis: (1) low-VIR use and creation; (2) spatial arrangements of VIRs. The next two studies are laboratory studies to investigate the visual memory cost of image transformations frequently used to create low-VIR displays and overview use with single-level data displayed in multiple-VIR interfaces. For a more well-rounded evaluation, we needed to study these techniques in ecologically-valid settings. We therefore selected the application domain of web session log analysis and applied our knowledge from our first three evaluations to build a tool called Session Viewer. Taking the multiple coordinated view and overview + detail approaches, Session Viewer displays multiple levels of web session log data and multiple views of session populations to facilitate data analysis from the high-level statistical to the low-level detailed session analysis approaches. Our fourth and last study for this thesis is a field evaluation conducted at Google Inc. with seven session analysts using Session Viewer to analyze their own data with their own tasks. Study observations suggested that displaying web session logs at multiple levels using the overview + detail technique helped bridge between high-level statistical and low-level detailed session analyses, and the simultaneous display of multiple session populations at all data levels using multiple views allowed quick comparisons between session populations. We also identified design and deployment considerations to meet the needs of diverse data sources and analysis styles.

This dissertation describes a series of studies conducted to explore why people use information visualizations during their non-work time (casual InfoVis) and which factors are critical for visualization adoption and long duration use. I also model typical casual InfoVis usage patterns and provide a framework for future hypothesis testing. Each study explored a different facet of casual InfoVis research and each built on lessons from the previous studies. The first study explored the development and evaluation of a casual InfoVis system, PartyVote, and how visualizations can be used to aid informal group social interactions. Results from the evaluation indicate that the system successfully helped give people a more equal share in choosing music during social gatherings and people could strategically choose music, but social pressures did not constrain behaviors or reduce cheating as much as expected. The complexity of factors affecting PartyVote use led to a pseudo-experiment evaluating the appeal of motion based data encoding. Study results indicated that participants formed distinct opinion-based groups and motion data encoding was only considered appealing to less than half of the participants. Utility was a critical factor for half the participants, but a sizable group still preferred motion use, despite knowing that it reduced system utility. My final study examined how people encountered and used visual representations of data (artifacts) during their non-work time. The artifact study led me to develop the Promoter / Inhibitor Motivation Model (PIMM) of casual visualization interaction. PIMM subsequently helps explain results encountered during the first two studies. The model provides a framework for future casual InfoVis investigations and identifies potential shortfalls and areas of concern when conducting casual InfoVis research. PIMM should also help guide future casual InfoVis system designs. / Graduate

As more and more data is created each day, researchers from different science domains are trying to make sense of it. A lot of this data, for example our connections to friends on different social networking websites, can be modeled as graphs, where the nodes are actors and the edges are relationships between them. Researchers analyze this data to find new forms of communication, to explore different social groups or subgroups, to detect illegal activities or to seek for different communication patterns that could help companies in their marketing campaigns. Another example are huge networks in system biology. Their visualization is crucial for the understanding of living beings. The topological structure of a network on its own could give insight into the existence or distribution of interesting actors in the network. However, this is often not enough to understand complex network systems in real-world applications. The reason for this is that all the network elements (nodes or edges) are not simple one-dimensional data. For instance in biology, experiments can be performed on biological networks. These experiments and network analysis approaches produce additional data that are often important to be analyzed with respect to the underlying network structure. Therefore, it is crucial to visualize the additional attributes of the network while preserving the network structure as much as possible. The problem is not trivial as these so-called multivariate networks could have a high number of attributes that are related to their nodes, edges, different groups, or clusters of nodes and/or edges. The aim of this thesis is to contribute to the development of different visualization and interaction techniques for the visual analysis of multivariate networks. Two research goals are defined in this thesis: first, a deeper understanding of existing approaches for visualizing multivariate networks should be acquired in order to classify them into categories and to identify disadvantages or unsolved visualization challenges. The second goal is to develop visualization and interaction techniques that will overcome various issues of these approaches. Initially, a brief survey on techniques to visualize multivariate networks is presented in this thesis. Afterwards, a small task-based user study investigating the usefulness of two main approaches for multivariate network visualization is discussed. Then, various visualization and interaction techniques for multivariate network visualization are presented. Three different software tools were implemented to demonstrate our research efforts. All features of our systems are highlighted, including a description of visualization and interaction techniques as well as disadvantages and scalability issues if present.

Large data sets are difficult to analyze. Visualization has been proposed to assist exploratory data analysis (EDA) as our visual systems can process signals in parallel to quickly detect patterns. Nonetheless, designing an effective visual analytic tool remains a challenge. This challenge is partly due to our incomplete understanding of how common visualization techniques are used by human operators during analyses, either in laboratory settings or in the workplace. This thesis aims to further understand how visualizations can be used to support EDA. More specifically, we studied techniques that display multiple levels of visual information resolutions (VIRs) for analyses using a range of methods. The first study is a summary synthesis conducted to obtain a snapshot of knowledge in multiple-VIR use and to identify research questions for the thesis: (1) low-VIR use and creation; (2) spatial arrangements of VIRs. The next two studies are laboratory studies to investigate the visual memory cost of image transformations frequently used to create low-VIR displays and overview use with single-level data displayed in multiple-VIR interfaces. For a more well-rounded evaluation, we needed to study these techniques in ecologically-valid settings. We therefore selected the application domain of web session log analysis and applied our knowledge from our first three evaluations to build a tool called Session Viewer. Taking the multiple coordinated view and overview + detail approaches, Session Viewer displays multiple levels of web session log data and multiple views of session populations to facilitate data analysis from the high-level statistical to the low-level detailed session analysis approaches. Our fourth and last study for this thesis is a field evaluation conducted at Google Inc. with seven session analysts using Session Viewer to analyze their own data with their own tasks. Study observations suggested that displaying web session logs at multiple levels using the overview + detail technique helped bridge between high-level statistical and low-level detailed session analyses, and the simultaneous display of multiple session populations at all data levels using multiple views allowed quick comparisons between session populations. We also identified design and deployment considerations to meet the needs of diverse data sources and analysis styles.

Thesis (Ph.D.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (p. 196-204).

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 78-80).

Thesis (Ph.D.). / Title from title page of PDF (viewed 2008/01/30). Written for the Dept. of Animal Science, Macdonald College. Includes bibliographical references.

Honors Project--Smith College, Northampton, Mass., 2009. / Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 104-107).