Chapter

An Extensible Framework for Interactive Real-Time Visualizations of Large-Scale Heterogeneous Multimedia Information from Online Sources

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

This work presents the user-centered design and development of a generic and extensible visualization framework that can be re-used in various scenarios in order to communicate large–scale heterogeneous multimedia information obtained from social media and Web sources, through user-friendly interactive visualizations in real-time. Using the particular framework as a basis, two Web-based dashboards demonstrating the visual analytics components of our framework have been developed. Additionally, three indicative use case scenarios where these dashboards can be employed are described. Finally, preliminary user feedback and improvements are discussed, and directions for further development are proposed on the basis of the findings.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

Article
Full-text available
Disasters and crises are inevitable in this world. In the aftermath of a disaster, a society’s overall growth, resources, and economy are greatly affected as they cause damages from minor to huge proportions. Around the world, countries are interested in improving their emergency decision-making. The institutions are paying attention to collecting different types of data related to crisis information from various resources, including social media, to improve their emergency response. Previous efforts have focused on collecting, extracting, and classifying crisis data from text, audio, video, or files; however, the development of user-friendly multimodal disaster data dashboards to support human-to-system interactions during an emergency response has received little attention. Our paper seeks to fill this gap by proposing usable designs of interactive dashboards to present multimodal disaster information. For this purpose, we first investigated social media data and metadata for the required elicitation and analysis purposes. These requirements are then used to develop interactive multimodal dashboards to present complex disaster information in a usable manner. To validate our multimodal dashboard designs, we have conducted a heuristic evaluation. Experts have evaluated the interactive disaster dashboards using a customized set of heuristics. The overall assessment showed positive feedback from the evaluators. The proposed interactive multimodal dashboards complement the existing techniques of collecting textual, image, audio, and video emergency information and their classifications for usable presentation. The contribution will help the emergency response personnel in terms of useful information and observations for prompt responses to avoid significant damage.
Article
Full-text available
Market participants and businesses have made tremendous efforts to make the best decisions in a timely manner under varying economic and business circumstances. As such, decision-making processes based on Financial data have been a popular topic in industries. However, analyzing Financial data is a non-trivial task due to large volume, diversity and complexity, and this has led to rapid research and development of visualizations and visual analytics systems for Financial data exploration. Often, the development of such systems requires researchers to collaborate with Financial domain experts to better extract requirements and challenges in their tasks. Work to systematically study and gather the task requirements and to acquire an overview of existing visualizations and visual analytics systems that have been applied in Financial domains with respect to real-world data sets has not been completed. To this end, we perform a comprehensive survey of visualizations and visual analytics. In this work, we categorize Financial systems in terms of data sources, applied automated techniques, visualization techniques, interaction, and evaluation methods. For the categorization and characterization, we utilize existing taxonomies of visualization and interaction. In addition, we present task requirements extracted from interviews with domain experts in order to help researchers design better systems with detailed goals.
Article
Full-text available
Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research.
Article
Full-text available
In this paper, we introduce a web-enabled geovisual analytics approach to leveraging Twitter in support of crisis management. The approach is implemented in a map-based, interactive web application that enables information foraging and sensemaking using "tweet" indexing and display based on place, time, and concept characteristics. In this paper, we outline the motivation for the research, review selected background briefly, describe the web application we have designed and implemented, and discuss our planned next steps.
Chapter
Full-text available
Most designers know that yellow text presented against a blue background reads clearly and easily, but how many can explain why, and what really are the best ways to help others and ourselves clearly see key patterns in a bunch of data? This book explores the art and science of why we see objects the way we do. Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness. The book offers practical guidelines that can be applied by anyone: interaction designers, graphic designers of all kinds (including web designers), data miners, and financial analysts.
Conference Paper
Full-text available
Microblogs are a tremendous repository of user-generated content about world events. However, for people trying to understand events by querying services like Twitter, a chronological log of posts makes it very difficult to get a detailed understanding of an event. In this paper, we present TwitInfo, a system for visualizing and summarizing events on Twitter. TwitInfo allows users to browse a large collec-tion of tweets using a timeline-based display that highlights peaks of high tweet activity. A novel streaming algorithm automatically discovers these peaks and labels them mean-ingfully using text from the tweets. Users can drill down to subevents, and explore further via geolocation, sentiment, and popular URLs. We contribute a recall-normalized ag-gregate sentiment visualization to produce more honest sen-timent overviews. An evaluation of the system revealed that users were able to reconstruct meaningful summaries of events in a small amount of time. An interview with a Pulitzer Prize-winning journalist suggested that the system would be especially useful for understanding a long-running event and for identifying eyewitnesses. Quantitatively, our system can identify 80-100% of manually labeled peaks, fa-cilitating a relatively complete view of each event studied.
Conference Paper
Full-text available
FinVis is a visual analytics tool that allows the non-expert casual user to interpret the return, risk and correlation aspects of financial data and make personal finance decisions. This interactive exploratory tool helps the casual decision-maker quickly choose between various financial portfolio options and view possible outcomes. FinVis allows for exploration of inter-temporal data to analyze outcomes of short-term or long-term investment decisions. FinVis helps the user overcome cognitive limitations and understand the impact of correlation between financial instruments in order to reap the benefits of portfolio diversification. Because this software is accessible by non-expert users, decision-makers from the general population can benefit greatly from using FinVis in practical applications. We quantify the value of FinVis using experimental economics methods and find that subjects using the FinVis software make better financial portfolio decisions as compared to subjects using a tabular version with the same information. We also find that FinVis engages the user, which results in greater exploration of the dataset and increased learning as compared to a tabular display. Further, participants using FinVis reported increased confidence in financial decision-making and noted that they were likely to use this tool in practical application.
Article
Full-text available
On a grand scale, visual analytics solutions provide technology that combines the strengths of human and electronic data processing. Visualization becomes the medium of a semi-automated analytical process, where humans and machines cooperate using their respective distinct capabilities for the most effective results. The diversity of these tasks can not be tackled with a single theory. Visual analytics research is highly interdisciplinary and combines various related research areas such as visualization, data mining, data management, data fusion, statistics and cognition science (among others).
Article
Full-text available
This paper is intended to give the visualization practitioner an overview of Edward Tufte's work on information display. Dr. Tufte has written two classic books on information display: The Visual Display of Quantitative Information and Envisioning Information. I believe that many of the concepts in these books are important to scientific visualization, but are often not applied by practitioners. Much of this paper is Tufte paraphrased: e.g., where Tufte might say 'graphical excellence', I write 'visualization excellence'. When you see the word 'ink' (paper technology!), think 'non-back-ground pixels'. Passages in quotation marks are direct quotes. Most of the text is a re-wording of Dr. Tufte's ideas, but all comments on the current state of visualization belong to me; and I am responsible for all errors. The reader is encouraged to read Tufte's books. The treatment here is brief, incomplete, picture-poor, and low resolution.
Conference Paper
Full-text available
We present a novel visual correlation paradigm for situational awareness (SA) and suggest its usage in a diverse set of applications that require a high level of SA. Our approach is based on a concise and scalable representation, which leads to a flexible visualization tool that is both clear and intuitive to use. Situational awareness is the continuous extraction of environmental information, its integration with previous knowledge to form a coherent mental picture, and the use of that picture in anticipating future events. In this paper we build on our previous work on visualization for network intrusion detection and show how that approach can be generalized to encompass a much broader class of SA systems. We first propose a generalization that is based on what we term, the w<sup>3</sup> premise, namely that each event must have at least the what, when and where attributes. We also present a second generalization, which increases flexibility and facilitates complex visual correlations. Finally, we demonstrate the generality of our approaches by applying our visualization paradigm in a collection of diverse SA areas.
Chapter
Novel graphical and direct-manipulation approaches to query formulation and information visualization are now possible. A useful starting point for designing advanced graphical user interfaces is the Visual Information-Seeking Mantra: first overview, followed by zoom and filter, and then details-on-demand. This chapter offers a task by data type taxonomy with seven data types (1D, 2D, 3D data, temporal data, multi-dimensional data, tree data, and network data) and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts). The success of direct-manipulation interfaces is indicative of the power of using computers in a more visual or graphical manner. Visual displays become even more attractive to provide orientation or context, to enable selection of regions, and to provide dynamic feedback for identifying changes (for example, a weather map). Scientific visualization has the power to make atomic, cosmic, and common 3D phenomena (for example, heat conduction in engines, airflow over wings, or ozone holes) visible and comprehensible. In the visual representation of data, users can scan, recognize, and recall images rapidly and can detect changes in size, color, shape, movement, or texture. They can point to a single pixel, even in a megapixel display, and can drag one object to another to perform an action. The novel-information exploration tools—such as dynamic queries, treemaps, fisheye views, parallel coordinates, starfields, and perspective walls—are a few of the inventions that will have to be validated.
Article
Advances in computer technology, patient monitoring systems, and electronic health record systems have enabled rapid accumulation of patient data in electronic form (i.e. big data). Organizations such as the Anesthesia Quality Institute and Multicenter Perioperative Outcomes Group have spearheaded large-scale efforts to collect anaesthesia big data for outcomes research and quality improvement. Analytics-the systematic use of data combined with quantitative and qualitative analysis to make decisions-can be applied to big data for quality and performance improvements, such as predictive risk assessment, clinical decision support, and resource management. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces, and it can facilitate performance of cognitive activities involving big data. Ongoing integration of big data and analytics within anaesthesia and health care will increase demand for anaesthesia professionals who are well versed in both the medical and the information sciences. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Article
This article describes how to use level sets to represent and compute deformable surfaces. A deformable surface is a sequence of surface models obtained by taking an initial model and incrementally modifying its shape. Typically, we can parameterize ...
Conference Paper
Journalists increasingly turn to social media sources such as Facebook or Twitter to support their coverage of various news events. For large-scale events such as televised debates and speeches, the amount of content on social media can easily become overwhelming, yet still contain information that may aid and augment reporting via individual content items as well as via aggregate information from the crowd's response. In this work we present a visual analytic tool, Vox Civitas, designed to help journalists and media professionals extract news value from large-scale aggregations of social media content around broadcast events. We discuss the design of the tool, present the text analysis techniques used to enable the presentation, and provide details on the visual and interaction design. We provide an exploratory evaluation based on a user study in which journalists interacted with the system to explore and report on a dataset of over one hundred thousand twitter messages collected during the U.S. State of the Union presidential address in 2010.
Conference Paper
Despite the growing number of systems providing visual analytic support for investigative analysis, few empirical studies of the potential benefits of such systems have been conducted, particularly controlled, comparative evaluations. Determining how such systems foster insight and sensemaking is important for their continued growth and study, however. Furthermore, studies that identify how people use such systems and why they benefit (or not) can help inform the design of new systems in this area. We conducted an evaluation of the visual analytics system Jigsaw employed in a small investigative sensemaking exercise, and we compared its use to three other more traditional methods of analysis. Sixteen participants performed a simulated intelligence analysis task under one of the four conditions. Experimental results suggest that Jigsaw assisted participants to analyze the data and identify an embedded threat. We describe different analysis strategies used by study participants and how computational support (or the lack thereof) influenced the strategies. We then illustrate several characteristics of the sensemaking process identified in the study and provide design implications for investigative analysis tools based thereon. We conclude with recommendations for metrics and techniques for evaluating other visual analytics investigative analysis tools.
Conference Paper
User-contributed messages on social media sites such as Twitter have emerged as powerful, real-time means of information sharing on the Web. These short messages tend to reflect a variety of events in real time, making Twitter particularly well suited as a source of real-time event content. In this paper, we explore approaches for analyzing the stream of Twitter messages to distinguish between messages about real-world events and non-event messages. Our approach relies on a rich family of aggregate statistics of topically similar message clusters. Large-scale experiments over millions of Twitter messages show the effectiveness of our approach for surfacing real-world event content on Twitter. 1
Article
Interactive visualizations have the potential to greatly enhance our ability to analyze data. Although the user is central to the use of such environments, perceptual and cognitive processes are not well understood within the context of interactive visualization. Although cognitive psychology has provided a greater understanding of visual perception and cognition, a theoretical framework that links this knowledge with the interactive visualization process is needed. This article aims to fill this gap by introducing a visual information processing model that facilitates the understanding of how users interact with interactive visualization environments.
Article
In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data rapidly grows, the ability to analyze these data volumes increases at much lower rates. This gap leads to new challenges in the analysis process, since analysts, decision makers, engineers, or emergency response teams depend on information hidden in the data. The emerging field of visual analytics focuses on handling these massive, heterogenous, and dynamic volumes of information by integrating human judgement by means of visual representations and interaction techniques in the analysis process. Furthermore, it is the combination of related research areas including visualization, data mining, and statistics that turns visual analytics into a promising field of research. This paper aims at providing an overview of visual analytics, its scope and concepts, addresses the most important research challenges and presents use cases from a wide variety of application scenarios.
Conference Paper
This paper consists of a review of contemporary methods that map and materialize abstract data as physical artifacts. With computing technology and the access of information influencing every aspect of our everyday lives, one can question the current habit of information displays to dasiasimulatepsila real world metaphors, and whether information could instead be conveyed by approximating the analogue and tangible characteristics of our daily experiences. This paper introduces five different degrees of dasiadata physicalitypsila, which differ in the level of abstraction of how data is mapped and perceived by human senses: ambient display, pixel sculptures, object augmentation, data sculptures and alternative modality. This categorization demonstrates the potential of information visualization as a communication medium in its own right, which proliferates beyond the ubiquitous pixel-based, light-emitting surfaces of today.
Article
A useful starting point for designing advanced graphical user interfaces is the Visual InformationSeeking Mantra: Overview first, zoom and filter, then details-on-demand. But this is only a starting point in trying to understand the rich and varied set of information visualizations that have been proposed in recent years. This paper offers a task by data type taxonomy with seven data types (1-, 2-, 3-dimensional data, temporal and multi-dimensional data, and tree and network data) and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extract). The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations Ben Shneiderman Department of Computer Science, Human-Computer Interaction Laboratory, and Institute for Systems Research University of Maryland College Park, Maryland 20742 USA ben@cs.umd.edu Abstract: A useful starting point for designing advanced graphical user interfaces is the Visual Information-Seeking Mantra: Overview first, ...
As you like it: tailorable information visualization
  • M Averbuch