The State of the Art in Sentiment Visualization

Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, including temporal, relational and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer‐reviewed publications together with an interactive web‐based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization. We expect this survey to be useful for visualization researchers whose interests include sentiment or other aspects of text data as well as researchers and practitioners from other disciplines in search of efficient visualization techniques applicable to their tasks and data.     

复杂战场环境中动态地形的表示及可视化技术研究

多分辨率建模作为解决大面积静态地形实时动态显示的手段,近年来在国内外得到普遍的重视和研究。目前,关于复杂战场环境中动态地形的表示及动态地形多分辨率实时可视化问题的研究在国内外还极不成熟。基于高逼真度虚拟战场环境仿真的要求和前人在这方面的有关研究,论文对动态地形的表示及可视化技术做了初步研究。     

An Overview of 3D Software Visualization

Software visualization studies techniques and methods for graphically representing different aspects of software. Its main goal is to enhance, simplify and clarify the mental representation a software engineer has of a computer system. During many years, visualization in 2D space has been actively studied, but in the last decade, researchers have begun to explore new 3D representations for visualizing software. In this article, we present an overview of current research in the area, describing several major aspects like: visual representations, interaction issues, evaluation methods and development tools. We also perform a survey of some representative tools to support different tasks, i.e., software maintenance and comprehension, requirements validation and algorithm animation for educational purposes, among others. Finally, we conclude identifying future research directions.     

A trajectory-preserving synchronization method for collaborative visualization

In the past decade, a lot of research work has been conducted to support collaborative visualization among remote users over the networks, allowing them to visualize and manipulate shared data for problem solving. There are many applications of collaborative visualization, such as oceanography, meteorology and medical science. To facilitate user interaction, a critical system requirement for collaborative visualization is to ensure that remote users will perceive a synchronized view of the shared data. Failing this requirement, the user's ability in performing the desirable collaborative tasks will be affected. In this paper, we propose a synchronization method to support collaborative visualization. It considers how interaction with dynamic objects is perceived by application participants under the existence of network latency, and remedies the motion trajectory of the dynamic objects. It also handles the false positive and false negative collision detection problems. The new method is particularly well designed for handling content changes due to unpredictable user interventions or object collisions. We demonstrate the effectiveness of our method through a number of experiments.     

Quality metrics in high-dimensional data visualization: an overview and systematization

In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.     

Computer graphics in medicine: the past decade

Clinical applications of computer graphics over the past decade are reviewed. Early distrust of the images provided by computer graphics is discussed. Differences between medical imagery and that for scientific visualization are examined     

The 2012 free and open source GIS software map – A guide to facilitate research,development, and adoption

Over the last decade an increasing number of free and open source software projects have been founded that concentrate on developing several types of software for geographic data collection, storage, analysis and visualization. We first identify the drivers of such software projects and identify different types of geographic information software, e.g. desktop GIS, remote sensing software, server GIS etc. We then list the major projects for each software category. Afterwards we discuss the points that should be considered if free and open source software is to be selected for use in business and research, such as software functionality, license types and their restrictions, developer and user community characteristics, etc. Finally possible future developments are addressed.     

The State of the Art of Spatial Interfaces for 3D Visualization

We survey the state of the art of spatial interfaces for 3D visualization. Interaction techniques are crucial to data visualization processes and the visualization research community has been calling for more research on interaction for years. Yet, research papers focusing on interaction techniques, in particular for 3D visualization purposes, are not always published in visualization venues, sometimes making it challenging to synthesize the latest interaction and visualization results. We therefore introduce a taxonomy of interaction technique for 3D visualization. The taxonomy is organized along two axes: the primary source of input on the one hand and the visualization task they support on the other hand. Surveying the state of the art allows us to highlight specific challenges and missed opportunities for research in 3D visualization. In particular, we call for additional research in: (1) controlling 3D visualization widgets to help scientists better understand their data, (2) 3D interaction techniques for dissemination, which are under‐explored yet show great promise for helping museum and science centers in their mission to share recent knowledge, and (3) developing new measures that move beyond traditional time and errors metrics for evaluating visualizations that include spatial interaction.     

Human factors in visualization research

Visualization can provide valuable assistance for data analysis and decision making tasks. However, how people perceive and interact with a visualization tool can strongly influence their understanding of the data as well as the system's usefulness. Human factors therefore contribute significantly to the visualization process and should play an important role in the design and evaluation of visualization tools. Several research initiatives have begun to explore human factors in visualization, particularly in perception-based design. Nonetheless, visualization work involving human factors is in its infancy, and many potentially promising areas have yet to be explored. Therefore, we aim to 1) review known methodology for doing human factors research, with specific emphasis on visualization, 2) review current human factors research in visualization to provide a basis for future investigation, and 3) identify promising areas for future research.     

A Survey of Visualization for Live Cell Imaging

Live cell imaging is an important biomedical research paradigm for studying dynamic cellular behaviour. Although phenotypic data derived from images are difficult to explore and analyse, some researchers have successfully addressed this with visualization. Nonetheless, visualization methods for live cell imaging data have been reported in an ad hoc and fragmented fashion. This leads to a knowledge gap where it is difficult for biologists and visualization developers to evaluate the advantages and disadvantages of different visualization methods, and for visualization researchers to gain an overview of existing work to identify research priorities. To address this gap, we survey existing visualization methods for live cell imaging from a visualization research perspective for the first time. Based on recent visualization theory, we perform a structured qualitative analysis of visualization methods that includes characterizing the domain and data, abstracting tasks, and describing visual encoding and interaction design. Based on our survey, we identify and discuss research gaps that future work should address: the broad analytical context of live cell imaging; the importance of behavioural comparisons; links with dynamic data visualization; the consequences of different data modalities; shortcomings in interactive support; and, in addition to analysis, the value of the presentation of phenotypic data and insights to other stakeholders.     

Web3D graphics enabled through sensor networks for cost-effective assessment and management of energy efficiency in buildings

The past decade has seen the advent of numerous building energy efficiency visualization and simulation systems; however, most of them rely on theoretical thermal models to suggest building structural design for new constructions and modifications for existing ones. Sustainable methods of construction have made tremendous progress. The example of the German Energy-Plus-House technology uses a combination of (almost) zero-carbon passive heating technologies. A web-enabled X3D visualization and simulation system coupled with a cost-effective set of temperature/humidity sensors can provide valuable insights into building design, materials and construction that can lead to significant energy savings and an improved thermal comfort for residents, resulting in superior building energy efficiency. A cost-effective hardware-software prototype system is proposed in this paper that can provide real-time data driven visualization or offline simulation of 3D thermal maps for residential and/or commercial buildings on the Web.     

生物特征信息处理开发包BITK及其应用平台

由于人类固有的生物特征能用来进行可靠的身份认证和识别,近10年来生物特征识别已经成为研究热点.为了对生物特征识别研究提供软件支持,设计研发了生物特征信息处理开发包 (Biometric Information Processing Toolkit,BITK).BITK是一个C 软件开发包.它以非线性数据流模型来组织整体计算流程,提供了一个可扩展、可重用的框架来整合生物特征识别领域的算法和数据结构.BITK还设计了一个精干的可视化框架以及一个管理各种生物特征采集仪的一致性框架.此外,在BITK基础上研发了生物特征信息处理平台 (BITK-based Application Platform,BITKAPP).该平台通过灵活的plug-in架构和友好的用户界面,充分发挥BITK的功能,并降低了BITK的使用门槛.在实际应用中,BITK和BITKAPP向研究人员提供了一套高效率的研究、实验及开发手段,并且作为支撑平台完成了第一届生物特征识别竞赛(the 1st Biometric Verification Competition)的多模态数据采集任务.     

Information visualization and visual data mining

Never before in history has data been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data is becoming increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization and visual data mining techniques which is based on the data type to be visualized, the visualization technique, and the interaction and distortion technique. We exemplify the classification using a few examples, most of them referring to techniques and systems presented in this special section     

A review on time series data mining

Time series is an important class of temporal data objects and it can be easily obtained from scientific and financial applications. A time series is a collection of observations made chronologically. The nature of time series data includes: large in data size, high dimensionality and necessary to update continuously. Moreover time series data, which is characterized by its numerical and continuous nature, is always considered as a whole instead of individual numerical field. The increasing use of time series data has initiated a great deal of research and development attempts in the field of data mining. The abundant research on time series data mining in the last decade could hamper the entry of interested researchers, due to its complexity. In this paper, a comprehensive revision on the existing time series data mining research is given. They are generally categorized into representation and indexing, similarity measure, segmentation, visualization and mining. Moreover state-of-the-art research issues are also highlighted. The primary objective of this paper is to serve as a glossary for interested researchers to have an overall picture on the current time series data mining development and identify their potential research direction to further investigation.     

音乐可视化及其研究进展

随着计算机技术的发展,音乐的形象化出现了新的手段,这就是音乐可视化技术.作为听觉艺术与视觉艺术的结合体,音乐可视化已经得到了广泛关注.文章介绍了音乐可视化的概念与研究内容,从可视化音乐模型、可视化视觉模型、可视化系统、可视化的交互性四个层次着重分析和评述了目前国内外音乐可视化技术的研究进展,并分析了当前亟待解决的问题,展望了其未来的发展趋势.音乐可视化作为一种新型的可视化技术,仍存在许多问题需要解决,其研究具有很强的理论意义和实用价值.     

音乐可视化研究综述

随着计算机技术的发展，音乐可视化日益得到研究机构和公司的重视，出现了各种音乐可视化系统。作为一种新的可视化技术，音乐可视化更多地关注音频和图形、图像的关系，是跨音乐、数字音频、图形学、图像处理、虚拟现实等领域的又一新的研究方向，在娱乐、教育、艺术和商业中具有广阔的应用前景。本文介绍了音乐可视化的概念和分类，探讨了音乐可视化的研究内容与国内外研究进展，分析了当前亟待解决的问题，并展望了未来的发展趋势。音乐可视化是一种新的概念系统，但也存在很多问题需要解决，其研究具有很强的理论和实用意义。     

Visualization and finite element techniques for seismic interpretation

Computational seismic modeling (CSM) is beginning to play an important role in the geophysical industry all over the world. People now realize that CSM can be a new and effective aid to seismic interpreters. One of the most important factors that has accelerated the development of CSM has been the rapid progress of supercomputers. With the increase in data obtained by the CSM research, the importance of visualization of the computed results began to be recognized.

The idea of visualization is not new; because massive amounts of numeric data are far more comprehensible when converted into graphical form, visualization is becoming an intimate part of many areas of research. Techniques for visualization, however, are still being developed, and visualization research is just beginning to be recognized as a cornerstone of future computer science. As scientists bring increasingly complex problems to computer science, visualization will become an even more essential tool for extracting science out of numbers.     

State of the Art of Sports Data Visualization

In this report, we organize and reflect on recent advances and challenges in the field of sports data visualization. The exponentially‐growing body of visualization research based on sports data is a prime indication of the importance and timeliness of this report. Sports data visualization research encompasses the breadth of visualization tasks and goals: exploring the design of new visualization techniques; adapting existing visualizations to a novel domain; and conducting design studies and evaluations in close collaboration with experts, including practitioners, enthusiasts, and journalists. Frequently this research has impact beyond sports in both academia and in industry because it is i) grounded in realistic, highly heterogeneous data, ii) applied to real‐world problems, and iii) designed in close collaboration with domain experts. In this report, we analyze current research contributions through the lens of three categories of sports data: box score data (data containing statistical summaries of a sport event such as a game), tracking data (data about in‐game actions and trajectories), and meta‐data (data about the sport and its participants but not necessarily a given game). We conclude this report with a high‐level discussion of sports visualization research informed by our analysis—identifying critical research gaps and valuable opportunities for the visualization community. More information is available at the STAR's website: https://sportsdataviz.github.io/ .