Future Challenges and Unsolved Problems in Multi-field Visualization

Evaluation, solved and unsolved problems, and future directions are popular themes pervading the visualization community over the last decade. The top unsolved problem in both scientific and information visualization was the subject of an IEEE Visualization Conference panel in 2004. The future of graphics hardware was another important topic of discussion the same year. The subject of how to evaluate visualization returned a few years later. Chris Johnson published a list of 10 top problems in scientific visualization research. This was followed up by report of both past achievements and future challenges in visualization research as well as financial support recommendations to the National Science Foundation (NSF) and National Institute of Health (NIH). Chen recently published the first list of top unsolved information visualization problems. Future research directions of topology-based visualization was also a major theme of a workshop on topology-based methods. Laramee and Kosara published a list of top future challenges in human-centered visualization

A Bibliometric Analysis and Visualization of the Scientific Publications of Universities: A Study of Hamadan University of Medical Sciences during 1992-2018

The evaluation of universities from different perspectives is important for their scientific development. Analyzing the scientific papers of a university under the bibliometric approach is one main evaluative approach. The aim of this study was to conduct a bibliometric analysis and visualization of papers published by Hamadan University of Medical Science (HUMS), Iran, during 1992-2018. This study used bibliometric and visualization techniques. Scopus database was used for data collection. 3753 papers were retrieved by applying Affiliation Search in Scopus advanced search section. Excel and VOSviewer software packages were used for data analysis and bibliometric indicator extraction. An increasing trend was seen in the numbers of HUMS's published papers and received citations. The highest rate of collaboration in national level was with Tehran University of Medical Sciences. Internationally, HUMS's researchers had the highest collaboration with the authors from the United States, the United Kingdom and Switzerland, respectively. All highly-cited papers were published in high level Q1 journals. Term clustering demonstrated four main clusters: epidemiological studies, laboratory studies, pharmacological studies, and microbiological studies. The results of this study can be beneficial to the policy-makers of this university. In addition, researchers and bibliometricians can use this study as a pattern for studying and visualizing the bibliometric indicators of other universities and research institutions

Measures in Visualization Space

Postponed access: the file will be available after 2021-08-12Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.acceptedVersio

JupyterLab_Voyager: A Data Visualization Enhancement in JupyterLab

With the emergence of big data, scientific data analysis and visualization (DAV) tools are critical components of the data science software ecosystem; the usability of these tools is becoming extremely important to facilitate next-generation scientific discoveries. JupyterLab has been considered as one of the best polyglot, web-based, open-source data science tools. As the next phase of extensible interface for the classic iPython Notebooks, this tool supports interactive data science and scientific computing across multiple programming languages with great performances. Despite these advantages, previous heuristics evaluation studies have shown that JupyterLab has some significant flaws in the data visualization side. The current DAV system in JupyterLab heavily relies on users’ understanding and familiarity with certain visualization libraries, and doesn’t support the golden visual-information-seeking mantra of “overview first, zoom and filter, then details-on-demand”. These limitations often lead to a workflow bottleneck at the start of a project. In this thesis, we present ‘JupyterLab_Voyager’, an extension for JupyterLab that provides a graphical user interface (GUI) for data visualization operations and couples faceted browsing with visualization recommendation to support exploration of multivariate, tabular data, as a solution to improve the usability of the DAV system. The new plugin works with various types of datasets in the JupyterLab ecosystem; using the plugin you can perform a high-level graphical analysis of fields within your dataset sans coding without leaving the JupyterLab environment. It helps analysts learn about the dataset and engage in both open-ended exploration and target specific answers from the dataset. User testings and evaluations demonstrated that this implementation has good usability and significantly improves the DAV system in JupyterLab

The design and evaluation of Novel prototypes to visualize web browsing history

Mainstream Web browsers support users in revisiting Web Pages by providing them with a history tool. Research shows that this history tool is severely underutilized. One possible reason is the manner in which the pages are displayed: a linear list of textual links. This thesis investigates the redesign of the history tool by introducing visualization to display the visited Web pages. Three distinct visual prototypes were designed ranging from a traditional scientific visualization method to a concrete visualization that incorporates a metaphor and knowledge transfer from the real-world. The low-fidelity prototypes were evaluated by participants and the best performing design was implemented as a high-fidelity prototype. Further evaluation with participants was conducted and the results were compared against the performance of participants using the traditional history tool of linear textual links.Master's These

Developing a Data Dashboard Framework for Population Health Surveillance: Widening Access to Clinical Trial Findings

Background: Population surveillance sites generate many datasets relevant to disease surveillance. However, there is a risk that these data are underutilized because of the volumes of data gathered and the lack of means to quickly disseminate analysis. Data visualization offers a means to quickly disseminate, understand, and interpret datasets, facilitating evidence-driven decision making through increased access to information. Objectives: This paper describes the development and evaluation of a framework for data dashboard design, to visualize datasets produced at a demographic health surveillance site. The aim of this research was to produce a comprehensive, reusable, and scalable dashboard design framework to fit the unique requirements of the context. Methods: The framework was developed and implemented at a demographic surveillance platform at the Africa Health Research Institute, in KwaZulu-Natal, South Africa. This context represents an exemplar implementation for the use of data dashboards within a population health-monitoring setting. Before the full launch, an evaluation study was undertaken to assess the effectiveness of the dashboard framework as a data communication and decision-making tool. The evaluation included a quantitative task evaluation to assess usability and a qualitative questionnaire exploring the attitudes to the use of dashboards. Results: The evaluation participants were drawn from a diverse group of users working at the site (n=20), comprising of community members, nurses, scientific and operational staff. Evaluation demonstrated high usability for the dashboard across user groups, with scientific and operational staff having minimal issues in completing tasks. There were notable differences in the efficiency of task completion among user groups, indicating varying familiarity with data visualization. The majority of users felt that the dashboards provided a clear understanding of the datasets presented and had a positive attitude to their increased use. Conclusions: Overall, this exploratory study indicates the viability of the data dashboard framework in communicating data trends within population surveillance setting. The usability differences among the user groups discovered during the evaluation demonstrate the need for the user-led design of dashboards in this context, addressing heterogeneous computer and visualization literacy present among the diverse potential users present in such settings. The questionnaire highlighted the enthusiasm for increased access to datasets from all stakeholders highlighting the potential of dashboards in this context

Segment Streaming for Efficient Pipelined Televisualization

The importance of scientific visualization for both science and engineering endeavors has been well recognized. Televisualization becomes necessary because of the physical distribution of data, computation resources, and users involved in the visualization process. However, televisualization poses a number of challenges to the designers of communication protocols. A pipelined televisualization (PTV) model is proposed for efficient implementation of a class of visualization applications. Central to the proposed research is the development of a segment of streaming IPC (interprocess communication) mechanism in support of efficient pipelining across very high speed internetworks. This requires exploration of special issues arising from extending a pipeline across networks with errors and high latency, determination of alternative solutions, and evaluation of such solutions. The novel aspects of the proposed segment streaming mechanism include a two-level flow control method and an intelligent error control mechanism

Probabilistic Assessment of Soil Liquefaction Potential and Mitigation

It has been well observed and reported that much of the great losses in past earthquakes, such as the 2011 Tohoku earthquake and the 2010-2011 Canterbury earthquake, were attributed to soil liquefaction and the associated ground deformation. Thus, any relevant research that contributes to the worldwide efforts to assess and mitigate liquefaction hazards is considered timely and worthwhile. This dissertation is aimed at addressing two aspects of liquefaction research: (1) improving the existing probabilistic methods for both location-specific and areal liquefaction potential evaluation, (2) creating visualization-based procedure for assessing the effectiveness of dynamic compaction in the liquefaction hazards mitigation. Both are deemed timely contributions to the course of earthquake hazard mitigation efforts by the engineering communities, which are the main objectives of the research. The dissertation research consists of three separate but related efforts that as a whole address the two main objectives of this research. The first part, Predicting liquefaction probability based on shear wave velocity: an update , was intended to improve the existing liquefaction evaluation method using shear wave velocity (Vs). The liquefaction evaluation models using Vs were calibrated based on the expanded Vs-based database was created. In this work, the scientific merits of various generalized linear regression models were investigated. Based on the findings of this investigation, the optimal models were recommended for the evaluation of location-specific liquefaction probability. In the second part of the dissertation research, concerning the Random field-based regional liquefaction hazard mapping — data inference and model verification using a synthetic digital soil field , the focus was on the areal or regional evaluation of liquefaction potential. Although the random field has been applied to many geotechnical problems, including liquefaction evaluation, abundant field data for assessing various issues of random field modeling, such as the accuracy and the computational demand, are lacking. To this end, an extremely detailed three-dimensional synthetic digital soil field was created, which enabled an extensive data inference and model calibration using the random field theories. This part of the dissertation work was more on fundamental scientific exploration. Nevertheless, it set the foundation for establishing the random field-based visualization procedure for liquefaction mitigation problem in the third part of this dissertation work. In the third and last part of the dissertation work: Mitigation of liquefaction hazard by dynamic compaction — a random field perspective , the effectiveness of dynamic compaction (DC) in the mitigation of liquefaction hazards was assessed from a random field perspective. The traditional assessment of this effectiveness was through in situ tests before and after DC, and the effectiveness of such approach depends on whether the one-to-one and side-by-side field tests before and after DC are available. In reality, such ideal situation almost always does not exist due to the construction practicality in the operation of DC. The random field modeling removed such need for the one-to-one and side-by-side field tests before and after DC. In this part, a random field based visualization procedure was created so that the liquefaction potential at the entire project site before and after DC could be clearly compared. The random field based visualization procedure was demonstrated as a practical tool by which the effect of DC could be easily communicated between the engineers and their clients. The scientific endeavor in the creation of a random field based visualization procedure to help solve a practical problem was deemed significant. In summary, the three parts of this dissertation work as a whole have achieved the two main objectives of the research regarding the liquefaction potential evaluation and the liquefaction mitigation. The scientific merits through these three parts of dissertation work have been demonstrated