Exploring user and system requirements of linked data visualization through a visual dashboard approach

One of the open problems in SemanticWeb research is which tools should be provided to users to explore linked data. This is even more urgent now that massive amount of linked data is being released by governments worldwide. The development of single dedicated visualization applications is increasing, but the problem of exploring unknown linked data to gain a good understanding of what is contained is still open. An effective generic solution must take into account the user’s point of view, their tasks and interaction, as well as the system’s capabilities and the technical constraints the technology imposes. This paper is a first step in understanding the implications of both, user and system by evaluating our dashboard-based approach. Though we observe a high user acceptance of the dashboard approach, our paper also highlights technical challenges arising out of complexities involving current infrastructure that need to be addressed while visualising linked data. In light of the findings, guidelines for the development of linked data visualization (and manipulation) are provided

Leveraging Peer Feedback to Improve Visualization Education

Peer review is a widely utilized pedagogical feedback mechanism for engaging students, which has been shown to improve educational outcomes. However, we find limited discussion and empirical measurement of peer review in visualization coursework. In addition to engagement, peer review provides direct and diverse feedback and reinforces recently-learned course concepts through critical evaluation of others' work. In this paper, we discuss the construction and application of peer review in a computer science visualization course, including: projects that reuse code and visualizations in a feedback-guided, continual improvement process and a peer review rubric to reinforce key course concepts. To measure the effectiveness of the approach, we evaluate student projects, peer review text, and a post-course questionnaire from 3 semesters of mixed undergraduate and graduate courses. The results indicate that course concepts are reinforced with peer review---82% reported learning more because of peer review, and 75% of students recommended continuing it. Finally, we provide a road-map for adapting peer review to other visualization courses to produce more highly engaged students

Semantic Support for Log Analysis of Safety-Critical Embedded Systems

Testing is a relevant activity for the development life-cycle of Safety Critical Embedded systems. In particular, much effort is spent for analysis and classification of test logs from SCADA subsystems, especially when failures occur. The human expertise is needful to understand the reasons of failures, for tracing back the errors, as well as to understand which requirements are affected by errors and which ones will be affected by eventual changes in the system design. Semantic techniques and full text search are used to support human experts for the analysis and classification of test logs, in order to speedup and improve the diagnosis phase. Moreover, retrieval of tests and requirements, which can be related to the current failure, is supported in order to allow the discovery of available alternatives and solutions for a better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic discovery, ontology, big dat

Data Visualization in Online Educational Research

This chapter presents a general and practical guideline that is intended to introduce the traditional visualization methods (word clouds), and the advanced visualization methods including interactive visualization (heatmap matrix) and dynamic visualization (dashboard), which can be applied in quantitative, qualitative, and mixed-methods research. This chapter also presents the potentials of each visualization method for assisting researchers in choosing the most appropriate one in the web-based research study. Graduate students, educational researchers, and practitioners can contribute to take strengths from each visual analytical method to enhance the reach of significant research findings into the public sphere. By leveraging the novel visualization techniques used in the web-based research study, while staying true to the analytical methods of research design, graduate students, educational researchers, and practitioners will gain a broader understanding of big data and analytics for data use and representation in the field of education

Novel Alert Visualization: The Development of a Visual Analytics Prototype for Mitigation of Malicious Insider Cyber Threats

Cyber insider threat is one of the most difficult risks to mitigate in organizations. However, innovative validated visualizations for cyber analysts to better decipher and react to detected anomalies has not been reported in literature or in industry. Attacks caused by malicious insiders can cause millions of dollars in losses to an organization. Though there have been advances in Intrusion Detection Systems (IDSs) over the last three decades, traditional IDSs do not specialize in anomaly identification caused by insiders. There is also a profuse amount of data being presented to cyber analysts when deciphering big data and reacting to data breach incidents using complex information systems. Information visualization is pertinent to the identification and mitigation of malicious cyber insider threats. The main goal of this study was to develop and validate, using Subject Matter Experts (SME), an executive insider threat dashboard visualization prototype. Using the developed prototype, an experimental study was conducted, which aimed to assess the perceived effectiveness in enhancing the analysts’ interface when complex data correlations are presented to mitigate malicious insiders cyber threats. Dashboard-based visualization techniques could be used to give full visibility of network progress and problems in real-time, especially within complex and stressful environments. For instance, in an Emergency Room (ER), there are four main vital signs used for urgent patient triage. Cybersecurity vital signs can give cyber analysts clear focal points during high severity issues. Pilots must expeditiously reference the Heads Up Display (HUD), which presents only key indicators to make critical decisions during unwarranted deviations or an immediate threat. Current dashboard-based visualization techniques have yet to be fully validated within the field of cybersecurity. This study developed a visualization prototype based on SME input utilizing the Delphi method. SMEs validated the perceived effectiveness of several different types of the developed visualization dashboard. Quantitative analysis of SME’s perceived effectiveness via self-reported value and satisfaction data as well as qualitative analysis of feedback provided during the experiments using the prototype developed were performed. This study identified critical cyber visualization variables and identified visualization techniques. The identifications were then used to develop QUICK.v™ a prototype to be used when mitigating potentially malicious cyber insider threats. The perceived effectiveness of QUICK.v™ was then validated. Insights from this study can aid organizations in enhancing cybersecurity dashboard visualizations by depicting only critical cybersecurity vital signs

Analysis and Design of Visualization of Educational Institution database using Power BI Tool

Visualization of data set is a process of making understand the significance of data through visual context and part of data analytics where it2019;s executed after the data correction. Nowadays visualization is more useful in business intelligence and Analytics in every field, There are different techniques for visualizing the datasets, it may be in dynamic or interactive nature, and datasets can be visualized in different types of visuals insights, This paper deals with the interactive visualization of educational institution database using Microsoft Power BI Tool with different modules and this paper focuses on process model, operations of Microsoft Power BI, types of data sources available in Tool and its different related types of visual insights or context

Representation of virtual choreographies in learning dashboards of interoperable LMS analytics

Learning management systems (LMS) collect a large amount of data from user interaction, and it isn't easy to analyze this data in a reliable and context-independent manner. This research seeks to comprehend how virtual choreographies can be represented in interoperable LMS analytics dashboards. In order to gain a better understanding of the problem, this objective has been divided into three sub-goals: determining which interactions can be gathered from LMS contexts, identifying virtual choreographies from LMS logs, and representing virtual choreographies in learning dashboards. To achieve these objectives, we first conducted a Systematic Literature Review to comprehend the behaviors and interactions other authors have investigated in LMS contexts. Then, by applying these findings to this dissertation's case study, a methodical procedure for extracting valuable choreographies from the logs was outlined. The Design Science Research methodology was then applied to transforming logs into virtual choreographies and their representation in learning dashboards. It was implemented two services: one responsible for identifying virtual choreographies from data logs and transforming the logs into statements, recipes, and choreographies, following xAPI specification elements; and the other translates the information from the backend service into dashboard visualizations, allowing the user to view representations for statements, recipes, choreographies, and various visualizations. These artifacts provide a new flexible and cost-efficient solution for the identification of virtual choreographies, thereby facilitating the widespread adoption of their use

Alexandria: Extensible Framework for Rapid Exploration of Social Media

The Alexandria system under development at IBM Research provides an extensible framework and platform for supporting a variety of big-data analytics and visualizations. The system is currently focused on enabling rapid exploration of text-based social media data. The system provides tools to help with constructing "domain models" (i.e., families of keywords and extractors to enable focus on tweets and other social media documents relevant to a project), to rapidly extract and segment the relevant social media and its authors, to apply further analytics (such as finding trends and anomalous terms), and visualizing the results. The system architecture is centered around a variety of REST-based service APIs to enable flexible orchestration of the system capabilities; these are especially useful to support knowledge-worker driven iterative exploration of social phenomena. The architecture also enables rapid integration of Alexandria capabilities with other social media analytics system, as has been demonstrated through an integration with IBM Research's SystemG. This paper describes a prototypical usage scenario for Alexandria, along with the architecture and key underlying analytics.Comment: 8 page

Doctor of Philosophy

dissertationThis dissertation establishes a new visualization design process model devised to guide visualization designers in building more effective and useful visualization systems and tools. The novelty of this framework includes its flexibility for iteration, actionability for guiding visualization designers with concrete steps, concise yet methodical definitions, and connections to other visualization design models commonly used in the field of data visualization. In summary, the design activity framework breaks down the visualization design process into a series of four design activities: understand, ideate, make, and deploy. For each activity, the framework prescribes a descriptive motivation, list of design methods, and expected visualization artifacts. To elucidate the framework, two case studies for visualization design illustrate these concepts, methods, and artifacts in real-world projects in the field of cybersecurity. For example, these projects employ user-centered design methods, such as personas and data sketches, which emphasize our teams' motivations and visualization artifacts with respect to the design activity framework. These case studies also serve as examples for novice visualization designers, and we hypothesized that the framework could serve as a pedagogical tool for teaching and guiding novices through their own design process to create a visualization tool. To externally evaluate the efficacy of this framework, we created worksheets for each design activity, outlining a series of concrete, tangible steps for novices. In order to validate the design worksheets, we conducted 13 student observations over the course of two months, received 32 online survey responses, and performed a qualitative analysis of 11 in-depth interviews. Students found the worksheets both useful and effective for framing the visualization design process. Next, by applying the design activity framework to technique-driven and evaluation-based research projects, we brainstormed possible extensions to the design model. Lastly, we examined implications of the design activity framework and present future work in this space. The visualization community is challenged to consider how to more effectively describe, capture, and communicate the complex, iterative nature of data visualization design throughout research, design, development, and deployment of visualization systems and tools

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