Visualizing information on mobile devices

Visualization can make a wide range of mobile applications more intuitive and productive. The mobility context and technical limitations such as small screen size make it impossible to simply port visualization applications from desktop computers to mobile devices, but researchers are starting to address these challenges. From a purely technical point of view, building more sophisticated mobile visualizations become easier due to new, possibly standard, software APIs such as OpenGLES and increasingly powerful devices. Although ongoing improvements would not eliminate most device limitations or alter the mobility context, they make it easier to create and experiment with alternative approaches.     

Visualizing with VTK: a tutorial

We introduce basic concepts behind the Visualization Toolkit (VTK). An overview of the system, plus some detailed examples, will assist in learning this system. The tutorial targets researchers of any discipline who have 2D or 3D data and want more control over the visualization process than a turn-key system can provide. It also assists developers who would like to incorporate VTK into an application as a visualization or data processing engine     

Text information extraction in images and video: a survey

Text data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. While comprehensive surveys of related problems such as face detection, document analysis, and image & video indexing can be found, the problem of text information extraction is not well surveyed. A large number of techniques have been proposed to address this problem, and the purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research.     

DNA-inspired information concealing: A survey

Various research efforts would benefit from the ability to exchange and share information (traces with packet payloads, or other detailed system logs) to enable more data-driven research. Protection of the sensitive content is crucial for extensive information sharing. We present results of Kencl and Loebl (2009) [41] and Blamey et al. (in preparation) [4] about a technique of information concealing, based on introduction and maintenance of families of repeats. The structure of repeats in DNA constitutes an important obstacle for its reconstruction by hybridisation. A large proportion of eukaryotic genomes is composed of DNA segments that are repeated either precisely or in variant form more than once. As yet, no function has been associated with many of the repeats. In the paper by Blamey et al. (in preparation) [4], the authors propose that in eukaryotes the cells have DNA as a depositary of concealed genetic information and the genome achieves the self-concealing by accumulation and maintenance of repeats. The protected information may be shared and this is useful for the development of intercellular communication and in the development of multicellular organisms. The results presented here are protected by Czech patent number 301799 and by US Patent Application number 12/670.     

Contextual information fusion for intrusion detection: a survey and taxonomy

Research in cyber-security has demonstrated that dealing with cyber-attacks is by no means an easy task. One particular limitation of existing research originates from the uncertainty of information that is gathered to discover attacks. This uncertainty is partly due to the lack of attack prediction models that utilize contextual information to analyze activities that target computer networks. The focus of this paper is a comprehensive review of data analytics paradigms for intrusion detection along with an overview of techniques that apply contextual information for intrusion detection. A new research taxonomy is introduced consisting of several dimensions of data mining techniques, which create attack prediction models. The survey reveals the need to use multiple categories of contextual information in a layered manner with consistent, coherent, and feasible evidence toward the correct prediction of cyber-attacks.     

Visualizing a sphere eversion

The mathematical process of everting a sphere (turning it inside-out allowing self-intersections) is a grand challenge for visualization because of the complicated, ever-changing internal structure. We have computed an optimal minimax eversion, requiring the least bending energy. Here, we discuss techniques we used to help visualize this eversion for visitors to virtual environments and viewers of our video The Optiverse.     

Visualizing a real forest

The authors collaborated with computer scientists, psychologists, artists, and others to create a highly realistic, computer-generated walkthrough of an existing forest. Funded by the US Department of Agriculture (USDA) Forest Service, this work supported current experiments at the University of Arizona's Department of Psychology. Researchers hope to determine the level of realism needed in computer-generated visualizations or animations of natural scenes for humans to reach conclusions about the virtual environment similar to those they would have reached by experiencing the actual site. The plan is to compare subjects' responses to actual, video taped, and photographed walkthroughs, and computer simulated walkthroughs     

Caching in information centric networking: A survey

Internet usage has drastically shifted from host-centric end-to-end communication to receiver-driven content retrieval. In order to adapt to this change, a handful of innovative information/content centric networking (ICN) architectures have recently been proposed. One common and important feature of these architectures is to leverage built-in network caches to improve the transmission efficiency of content dissemination. Compared with traditional Web Caching and CDN Caching, ICN Cache takes on several new characteristics: cache is transparent to applications, cache is ubiquitous, and content to be cached is more ine-grained. These distinguished features pose new challenges to ICN caching technologies. This paper presents a comprehensive survey of state-of-art techniques aiming to address these issues, with particular focus on reducing cache redundancy and improving the availability of cached content. As a new research area, this paper also points out several interesting yet challenging research directions in this subject.     

Visualizing functions over a sphere

Techniques for the visualization of a scalar-valued function defined over a spherical domain are discussed. Functions of this type arise, for example, in the fitting of measured data on the surface of the earth. Methods for contouring and for displaying the graph of a function are presented, along with several examples. The projected graph technique can also be considered as a method for modeling closed surfaces     

Psycho-visual modulation based information display: introduction and survey

Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality. As a result, many modern displays have spatial and temporal resolutions far beyond the discern capability of human visual systems. Thus, leading to the possibility of using those display-eye redundancies for innovative usages. Temporal/ spatial psycho-visual modulation (TPVM/SPVM) was proposed to exploit those redundancies to generate multiple visual percepts for different viewers or to transmit non-visual data to computing devices without affecting normal viewing. This paper reviews the STPVM technology from both conceptual and algorithmic perspectives, with exemplary applications in multiview display, display with visible light communication, etc. Some possible future research directions are also identified.     

SmallWorlds: Visualizing Social Recommendations

We present SmallWorlds, a visual interactive graph‐based interface that allows users to specify, refine and build item‐preference profiles in a variety of domains. The interface facilitates expressions of taste through simple graph interactions and these preferences are used to compute personalized, fully transparent item recommendations for a target user. Predictions are based on a collaborative analysis of preference data from a user's direct peer group on a social network. We find that in addition to receiving transparent and accurate item recommendations, users also learn a wealth of information about the preferences of their peers through interaction with our visualization. Such information is not easily discoverable in traditional text based interfaces. A detailed analysis of our design choices for visual layout, interaction and prediction techniques is presented. Our evaluations discuss results from a user study in which SmallWorlds was deployed as an interactive recommender system on Facebook.     

Visualizing the application of filters: A comparison of blocking,blurring, and colour-coding whiteboard information

Through a mixed-design experiment we compare how emergency-department clinicians perform when solving realistic work tasks with an electronic whiteboard where the application of information filters is visualized either by blocking, colour-coding or blurring information. We find that clinicians perform significantly faster and with less effort and temporal demand when using the blocking interface. However, we also find that the colour-coding interface provides clinicians with a better overview of the information displayed by the electronic whiteboard. The blurring interface did not perform as well as previous research has shown and we discuss the differences between these results and ours. Finally, we find that the clinicians worked much less in parallel than we had expected and discuss the reasons for this.     

Visualizing a knowledge domain's intellectual structure

To make knowledge visualizations clear and easy to interpret, we have developed a method that extends and transforms traditional author co-citation analysis by extracting structural patterns from the scientific literature and representing them in a 3D knowledge landscape     

Ontology-driven geographic information integration: A survey of current approaches

Integrating different information sources is a growing research area within different application domains. This is particularly true for the geographic information domain which is facing new challenges because newer and better technologies are capturing large amounts of information about the Earth. This trend can be combined with increases in the distribution of GIS (Geographic Information Systems) on the Web, which is leading to the proliferation of different geospatial information repositories and the subsequent need to integrate information across repositories to get consistent information. To overcome this situation, many proposals use ontologies in the integration process. In this paper we analyze and compare the most widely referred proposals of geographic information integration, focusing on those using ontologies as semantic tools to represent the sources, and to facilitate the integration process.     

A survey on information visualization: recent advances and challenges

Information visualization (InfoVis), the study of transforming data, information, and knowledge into interactive visual representations, is very important to users because it provides mental models of information. The boom in big data analytics has triggered broad use of InfoVis in a variety of domains, ranging from finance to sports to politics. In this paper, we present a comprehensive survey and key insights into this fast-rising area. The research on InfoVis is organized into a taxonomy that contains four main categories, namely empirical methodologies, user interactions, visualization frameworks, and applications, which are each described in terms of their major goals, fundamental principles, recent trends, and state-of-the-art approaches. At the conclusion of this survey, we identify existing technical challenges and propose directions for future research.     

A survey on socio-semantic information retrieval

The rise of the Social Web and advances in the Semantic Web provides unprecedented possibilities for the development of novel methods to enhance the information retrieval (IR) process by including varying degrees of semantics. We shed light on the corresponding notion of semantically-enhanced information retrieval by presenting state-of-the art techniques in related research areas. We describe techniques based on the main processes of a typical IR workflow and map them onto three main types of semantics, which vary from formal semantic knowledge representations and content-based semantics to social semantics emerging through usage and user interactions.