Walking the Path: A New Journey to Explore and Discover Through Visual Analytics
Under the leadership of the US Department of Homeland Security (DHS), researchers at the Pacific Northwest National Laboratory (PNNL) established a research center focusing on the discipline of visual analytics in 2004. A year later, the center led a multidisciplinary panel representing academia, industry, and government to formally define directions and priorities for future research and development (R&D) for visual analytics tools. The R&D agenda, Illuminating the Path, defines the term visual analytics as ‘the science of analytical reasoning facilitated by interactive visual interfaces’. This article describes our progress to date in walking that path. We briefly describe the background of the subject, present major professional activities and accomplishments of its community, and highlight some of the ongoing R&D efforts being carried out by researchers at PNNL to fulfill the requirements and missions of a new discipline that promises to change the way we deal with today's information.

title: Vector fields simplification-a case study of visualizing climate modeling and simulation data sets
abstract: In our study of regional climate modeling and simulation, we frequently encounter vector fields that are crowded with large numbers of critical points. A critical point in a flow is where the vector field vanishes. While these critical points accurately reflect the topology of the vector fields, in our study only a subset of them is worth further investigation. We present a filtering technique based on the vorticity of the vector fields to eliminate the less interesting and sometimes sporadic critical points in a multiresolution fashion. The neighboring regions of the preserved features, which are characterized by strong shear and circulation, are potential locations of weather instability. We apply our feature filtering technique to a regional climate modeling data set covering East Asia in the summer of 1991.

title: Data Signatures and Visualization of Scientific Data Sets
abstract: Today, as data sets used in computations grow in size and complexity, the technologies developed over the years to deal with scientific data sets have become less efficient and effective. Many frequently used operations, such as eigenvector computation, could quickly exhaust our desktop workstations once the data size reaches certain limits. On the other hand, the high-dimensional data sets we collect every day don't relieve the problem. Many conventional metric designs that build on quantitative or categorical data sets cannot be applied directly to heterogeneous data sets with multiple data types. While building new machines with more resources might conquer the data size problems, the complexity of today's computations requires a new breed of projection techniques to support analysis of the data and verification of the results. We introduce the concept of a data signature, which captures the essence of a scientific data set in a compact format, and use it to conduct analysis as if using the original. A time-dependent climate simulation data set demonstrates our approach and presents the results.

title: Generating Graphs for Visual Analytics through Interactive Sketching
abstract: We introduce an interactive graph generator, GreenSketch, designed to facilitate the creation of descriptive graphs required for different visual analytics tasks. The human-centric design approach of GreenSketch enables users to master the creation process without specific training or prior knowledge of graph model theory. The customized user interface encourages users to gain insight into the connection between the compact matrix representation and the topology of a graph layout when they sketch their graphs. Both the human-enforced and machine-generated randomnesses supported by GreenSketch provide the flexibility needed to address the uncertainty factor in many analytical tasks. This paper describes more than two dozen examples that cover a wide variety of graph creations from a single line of nodes to a real-life small-world network that describes a snapshot of telephone connections. While the discussion focuses mainly on the design of GreenSketch, we include a case study that applies the technology in a visual analytics environment and a usability study that evaluates the strengths and weaknesses of our design approach

title: Organic data memory using the DNA approach
abstract: For very long-term storage and retrieval, encode information as artificial DNA strands and insert into living hosts. As vectors, bacteria, even some bugs and weeds, might be good for hundreds of millions of years.

title: Multivariate Visualization with Data Fusion
abstract: We discuss a fusion-based visualization method to analyze a multivariate climate dataset and its metadata. The primary difference between a conventional visualization and a fusion-based visualization is that the former draws on a single image whereas the latter draws on multiple see-through layers, which are then overlaid on each other to form the final visualization. We propose optimized colormaps to highlight subtle features that would not be shown with conventional colormaps. We present fusion techniques that integrate multiple single-purpose visualization techniques into the same viewing space. Our highly flexible fusion approach allows scientists to explore multiple parameters concurrently by mixing and matching images without frequently reconstructing new visualizations from the data for every possible combination. Although our primary visualization application is climate modeling, we show with examples that our fundamental design - fusing layers of data images for multivariate visualization - can be generalized for other information visualization applications.

title: Rate estimation for H.264/AVC spatial resolution reduction
abstract: The emergence of wireless networks has posed new challenges for multimedia content providers. In particular, many existing video contents have bit-rates and resolutions far exceeding the capability of wireless networks and mobile devices and they need to be adapted before transmission. In this paper, we propose a technique using /spl rho/-domain information to estimate the bit rate of down-sampled video in the H.264/AVC format. The bit rate is estimated in two stages. In the initialization stage, we use a low-complexity algorithm to estimate the /spl rho/-domain parameters for half and quarter resolutions, respectively. In the refinement stage, the estimation error is feed-forwarded to improve the estimation accuracy. Experimental results show that the proposed technique can estimate the bit rate accurately at a wide range of down-sampling ratios.

title: Fast multi-block selection for H.264 video coding
abstract: The JVT/H.264 is the new video coding standard which achieves higher coding efficiency than previous standards such as H.263 or MPEG-2. The improvement in the rate-distortion performance in H.264 is mainly due to accurate motion estimation with different mode decision including multiple block size and multiple reference frame motion estimation. However, full exhaustive search of all block sizes is computational intensive with complexity increasing linearly with the number of allowed block size. In this paper, a fast multi-block motion estimation (FMBME) is proposed for H.264 video coding. Experimental results show that the proposed FMBME can efficiently reduce the computational cost by 58% with similar visual quality and bit rate.

title: A capacity estimation technique for JPEG-to-JPEG image watermarking
abstract: In JPEG-to-JPEG image watermarking (J2J), the input is a JPEG image file. After watermark embedding, the image is JPEG-compressed such that the output file is also a JPEG file. We use the human visual system (HVS) model to estimate the J2J data hiding capacity of JPEG images, or the maximum number of bits that can be embedded in JPEG-compressed images.  Watson's HVS model (Proc. SPIE Human Vision, Visual Process., and Digital Display IV, p.202-16, 1993) is modified to estimate the just noticeable difference (JND) for DCT coefficients. The number of modifications to DCT coefficients is limited by JND in order to guarantee the invisibility of the watermark. Our capacity estimation method does not assume any specific watermarking method and thus would apply to any watermarking method in the J2J framework.

title: Performance Analysis of a Pull-Based Parallel Video Server
abstract: In conventional video-on-demand systems, video data are stored in a video server for delivery to multiple receivers over a communications network. The video server's hardware limits the maximum storage capacity as well as the maximum number of video sessions that can concurrently be delivered. Clearly, these limits will eventually be exceeded by the growing need for better video quality and larger user population. This paper studies a parallel video server architecture that exploits server parallelism to achieve incremental scalability. First, unlike data partition and replication, the architecture employs data striping at the server level to achieve fine-grain load balancing across multiple servers. Second, a client-pull service model is employed to eliminate the need for interserver synchronization. Third, an admission-scheduling algorithm is proposed to further control the instantaneous load at each server so that linear scalability can be achieved. This paper analyzes the performance of the architecture by deriving bounds for server service delay, client buffer requirement, prefetch delay, and scheduling delay. These performance metrics and design tradeoffs are further evaluated using numerical examples. Our results show that the proposed parallel video server architecture can be linearly scaled up to more concurrent users simply by adding more servers and redistributing the video data among the servers.

title: CRL: A Context-Aware Request Language for Mobile Computing
abstract: This paper introduces an XML-based generic Context Request Language (CRL), whose construction is part of a web services framework in the domain of mobile context sensing. The paper describes an implementation of the technique that is in accordance with the formal mathematical representational model, using first-order temporal language . The language is an attempt to introduce intelligence into context-aware computing by defining context-sensing elements into logical entities. The use of first-order calculus in this language definition serving on web service technology allows users to utilize context aggregation and to embed user control in contextual information. By carrying out on-the-fly context inferences at the middleware level, we can achieve a complete separation of concerns between user application and context sensing. Moreover, the declaration of contextual knowledge based on situations and events within the predicate domain allows users to express changes in contextual information and to quantify these elements among times and durations.