基于大数据平台的交通数据可视化设计与实现

本文实现是以某市交通事故分析为核心,面向某市交管局指挥中心大屏环境,对交通事故相关综合数据进行处理分析和维护任务,具备优异的数据可视化显示效果,支持大屏、多屏等展示场景,为交通整改、政府决策等提供全面服务,使交管部门工作从规模庞大的交通事故数据中快速直接地检索到重要且需要的数据,最后通过数据可视化和数据分析处理相结合,提升交通事故剖析能力。     

数据可视化大屏UI设计的研究和分析

如今,数据可视化大屏被越来越多地应用在B端企业和政府企业的项目中。与传统的互联网C端产品不同,B端的大屏可视化是一项结合了视觉传达学、用户心理学和计算机科学的学科,不同项目面向各个行业,展示需求错综复杂,不同企业用户对于大屏展示的需求又千差万别。国内没有一套针对于数据可视化大屏相对完善的视觉解决方案,导致众多设计师和产品经理在接触类似项目时无法入手。从可视化图表、用户行为交互、视觉记忆模式、大屏幕显示下用户对界面色彩场景设计的感受,以及字体应用和动态图形动画等多个维度,提炼出一套相对完善和全面的视觉设计理论,以应对不同的大屏业务展示场景。数据可视化大屏便于使用者快速、准确地传达可视化信息。     

智能车间可视化大屏设计与实现

智能化生产和数字化转型成为驱动工业企业高质量发展的有效途径.以某纺织厂智能车间可视化大屏设计与实现为目标,综合考虑政府监管、企业发展不同视角进行了大屏框架总体设计,提出了一种基于"端-边-云"的系统架构,运用大数据技术、3D交互技术、数据可视化技术,对系统进行实现和验证.初步应用表明,该系统较完美地解决了工业生产车间监...     

一种基于数据可视化技术的便携式物联网环境监测仪

本文介绍了一种基于物联网技术、数据可视化技术、Android手机APP的便携式物联网环境监测仪的设计实现方案。设计中通过对STM32以及无线传感器网络的应用,完成了对环境状态信息的监控与上传系统。通过数据可视化技术,完成对数据大屏的实时更新。在本系统的监测下,用户可实时了解环境状态信息,并通过数据大屏,挖掘数据深层价值。     

水库群智能云服务平台可视化系统设计与实现

为加强水利信息化建设,解决海量异构数据管理分散、水利信息化展示平台落后等问题,实现水利信息数字化、规范化、模块化管理的目标,本文设计并实现了一套水库群智能云服务平台大屏可视化系统。该系统基于Vue前端可视化开源框架和SpringCloud微服务后端开发框架,采用WebSocket数据传输协议作为核心驱动全屏信息通讯与交互,以WebGIS地理开发库Cesium.js为依托,结合ECharts、DataV等应用组件库,设计了一套大屏可视化集成方案,为水利成果展示提供了一个多端协同与信息共享的可视化平台,有利于促进流域水资源高效利用及科学化管理。通过在金沙江下游与三峡梯级的应用实例表明,该可视化系统集成技术能够实现流域水利信息形象、生动的全方位展示,具有较高的应用前景和参考价值,能够为水资源高效开发与利用提供技术支撑。     

新冠肺炎疫情大数据可视化平台设计与实现

介绍了新冠肺炎疫情大数据可视化平台的搭建:以大量的新冠肺炎疫情数据为基础,借助Echarts技术以及交互组件,通过可视化图形与地图集成的方式对疫情数据进行可视化展示.实现从多个角度展示国内疫情发展趋势,丰富了疫情数据的展示内容,为广大人民群众了解新冠肺炎疫情提供了便利.     

可视数据组件结合SQLServer实现动态排序等扩展功能

集成开发环境中的可视化设计已成为当前软件开发中的首选.结合可视化组件进行灵活设计,可以大大提高开发效率、降低开发成本.文章通过对可视化程序设计常用数据组件DBGrid的应用研究,给出了在普通数据组件上实现扩展功能,实现对显示数据排序、查询的简便操作.并以SQLServer数据库及DELPHI开发平台为基础,给出了一个详细的实例,对动态排序、动态查询的生成及原理进行了较为详细的描述.     

基于组件技术的地下水资源管理系统开发

组件式的理信息系统(ComGIS)是当前新一代地理信息系统发展方向之一、该文阐述了组件式GIS基本概念,并根据“长江三角洲(南部)地区地下水资源管理系统”的开发,在分析本管理系统需求的基础上,从数据管理、模型建立、专题制图、三维可视化等多方面讨论了组件式软件技术在GIS二次开发中的应用。     

新生数据可视化系统的设计与实现

随着高等教育的普及,高校招生数量逐年递增。对于新生数据的分析有助于帮助学校更好地了解学生情况,有 助于教学、学生管理等工作的开展。基于此,设计并实现了新生数据可视化系统,汇总新生数据,并通过学院大屏进行可视化 的展现。系统基于Python语言,采用前后端分离的技术实现。后端通过Python Flask框架和SqlAlchem y提供数据接口,前后端 通过AJAX 传递数据,前端通过Vue+ EC harts进行数据可视化展现。     

基于GIS的特种设备监测系统研究

本文描述了基于GIS可视化技术的特种设备监测系统的组成结构。概述了组件式GIS的技术特点,并利用组件式GIS可视化技术从软件结构、系统功能、数据库结构等方面完成特种设备可视化监测系统软件设计。     

基于三维GIS的大屏可视化策略

本文分析了三维地理信息系统和大屏展示系统的现状及特点, 以通用性的综合展示平台为例, 选取南宁市数字孪生可视化展示为主题, 从空间信息场景设计、表达对象选取、页面布局、平台色彩设计、符号设计、图表设计、动效设计的角度切入, 提出了基于三维GIS的大屏可视化策略. 并基于上述策略, 对该类型平台搭建的系统架构和关键技术点...     

基于互联网的市场行情可视化信息系统

提出了基于Internet的空间数据和非空间数据分布存储的空间数据仓库模型，并将其与数据挖掘技术相结合，开发了基于Internet的农产品市场行情时空演变可视化信息系统。该系统由来自Web网页的数据源、驻留Web数据自动抓取工具和非空间数据库的服务器以及驻留空间数据库、具有可视化展示和空间数据挖掘功能的客户机组成。为提高系统客户机的运行效率，系统采用了多种策略，如分布存储策略、瘦客户机策略、模糊匹配以及批处理策略等。系统具有界面友好、操作简便、可视化程度高等优点。     

智能数据可视分析技术综述

如何从海量数据中快速有效地挖掘出有价值的信息以更好地指导决策,是大数据分析的重要目标.可视分析是一种重要的大数据分析方法,它利用人类视觉感知特性,使用可视化图表直观呈现复杂数据中蕴含的规律,并支持以人为本的交互式数据分析.然而,可视分析仍然面临着许多挑战,例如数据准备代价高、交互响应高延迟、可视分析高门槛和交互模式效率低.为应对这些挑战,研究者从数据管理、人工智能等视角出发,提出一系列方法以优化可视分析系统的人机协作模式和提高系统的智能化程度.系统性地梳理、分析和总结这些方法,提出智能数据可视分析的基本概念和关键技术框架.然后,在该框架下,综述和分析国内外面向可视分析的数据准备、智能数据可视化、高效可视分析和智能可视分析接口的研究进展.最后,展望智能数据可视分析的未来发展趋势.     

Interactive visibility retargeting in VR using conformal visualization

In Virtual Reality, immersive systems such as the CAVE provide an important tool for the collaborative exploration of large 3D data. Unlike head-mounted displays, these systems are often only partially immersive due to space, access, or cost constraints. The resulting loss of visual information becomes a major obstacle for critical tasks that need to utilize the users' entire field of vision. We have developed a conformal visualization technique that establishes a conformal mapping between the full 360° field of view and the display geometry of a given visualization system. The mapping is provably angle-preserving and has the desirable property of preserving shapes locally, which is important for identifying shape-based features in the visual data. We apply the conformal visualization to both forward and backward rendering pipelines in a variety of retargeting scenarios, including CAVEs and angled arrangements of flat panel displays. In contrast to image-based retargeting approaches, our technique constructs accurate stereoscopic images that are free of resampling artifacts. Our user study shows that on the visual polyp detection task in Immersive Virtual Colonoscopy, conformal visualization leads to improved sensitivity at comparable examination times against the traditional rendering approach. We also develop a novel user interface based on the interactive recreation of the conformal mapping and the real-time regeneration of the view direction correspondence.     

Application of the level set method for the visual representation of continuous cellular automata oriented to anisotropic wet etching

Atomistic models are a very valuable simulation tool in the field of material science. Among them are the continuous cellular automata (CCA), which can simulate accurately the process of chemical etching used in micro-electro-mechanical-systems (MEMS) micromachining. Due to the CCA intrinsic atomistic nature, simulation results are obtained in the form of a cloud of points, so data visualization has been usually problematic. When using these models as a part of a computer aided design tool, good data visualization is very important. In this paper, a minimum energy model implemented with the level set (LS) method for improving the visual representation of simulated MEMS is presented. Additionally, the sparse field method has been applied to reduce the high computational cost of the original LS. Finally, some reconstructed surfaces with completely different topologies are presented, proving the effectiveness of our implementation and the fact that it is capable of producing any real surface, flat and smooth ones.     

Visualizing visualizations. User interfaces for managing andexploring scientific visualization data

The process of scientific visualization is inherently iterative. A good visualization comes from experimenting with visualization, rendering, and viewing parameters to bring out the most relevant information in the data. A good data visualization system thus lets scientists interactively explore the parameter space intuitively. The more efficient the system, the fewer the number of iterations needed for parameter selection. Over the past 10 years, significant efforts have gone into advancing visualization technology (such as real-time volume rendering and immersive environments), but little into coherently representing the process and results (images and insights) of visualization. This information about the data exploration should be shared and reused. In particular, for types of data visualization with a high cost of producing images and less than obvious relationship between the rendering parameters and the image produced, a visual representation of the exploration process can make the process more efficient and effective. This visual representation of data exploration process and results can be incorporated into and become a part of the user interface of a data exploration system. That is, we need to go beyond the traditional graphical user interface (GUI) design by coupling it with a mechanism that helps users keep track of their visualization experience, use it to generate new visualizations, and share it with others. Doing so can reduce the cost of visualization, particularly for routine analysis of large-scale data sets     

Visual requirements analytics: a framework and case study

For many software projects, keeping requirements on track needs an effective and efficient path from data to decision. Visual analytics creates such a path that enables the human to extract insights by interacting with the relevant information. While various requirements visualization techniques exist, few have produced end-to-end value to practitioners. In this paper, we advance the literature on visual requirements analytics by characterizing its key components and relationships in a framework. We follow the goal–question–metric paradigm to define the framework by teasing out five conceptual goals (user, data, model, visualization, and knowledge), their specific operationalizations, and their interconnections. The framework allows us to not only assess existing approaches, but also create tool enhancements in a principled manner. We evaluate our enhanced tool support through a case study where massive, heterogeneous, and dynamic requirements are processed, visualized, and analyzed. Working together with practitioners on a contemporary software project within its real-life context leads to the main finding that visual analytics can help tackle both open-ended visual exploration tasks and well-structured visual exploitation tasks in requirements engineering. In addition, the study helps the practitioners to reach actionable decisions in a wide range of areas relating to their project, ranging from theme and outlier identification, over requirements tracing, to risk assessment. Overall, our work illuminates how the data-to-decision analytical capabilities could be improved by the increased interactivity of requirements visualization.     

基于小波分析的时间序列数据挖掘模型

论文提出一个基于小波分析的时间序列挖掘模型TSMiner,它支持时间序列数据挖掘的整个过程。该模型由5部分组成:原始数据的可视化、数据预处理、数据约简,模式发现和结果模式可视化。该模型应用小波实现数据的多层次可视化表示、数据约简和多尺度模式发现。它可以帮助用户观察高维数据,理解中间结果和解释发现的模式。     

Collaborative Exploration and Sensemaking of Big Environmental Sound Data

Many ecologists are using acoustic monitoring to study animals and the health of ecosystems. Technological advances mean acoustic recording of nature can now be done at a relatively low cost, with minimal disturbance, and over long periods of time. Vast amounts of data are gathered yielding environmental soundscapes which requires new forms of visualization and interpretation of the data. Recently a novel visualization technique has been designed that represents soundscapes using dense visual summaries of acoustic patterns. However, little is known about how this visualization tool can be employed to make sense of soundscapes. Understanding how the technique can be best used and developed requires collaboration between interface, algorithm designers and ecologists. We empirically investigated the practices and needs of ecologists using acoustic monitoring technologies. In particular, we investigated the use of the soundscape visualization tool by teams of ecologists researching endangered species detection, species behaviour, and monitoring of ecological areas using long duration audio recordings. Our findings highlight the opportunities and challenges that ecologists face in making sense of large acoustic datasets through patterns of acoustic events. We reveal the characteristic processes for collaboratively generating situated accounts of natural places from soundscapes using visualization. We also discuss the biases inherent in the approach. Big data from nature has different characteristics from social and informational data sources that comprise much of the World Wide Web. We conclude with design implications for visual interfaces to facilitate collaborative exploration and discovery through soundscapes.     

Visualizing production planning data

Visualization of production planning data for decision making in manufacturing is nearly nonexistent. The planning problems at the Electronic Card Assembly and Test plant (ECAT) at IBM Austin, Texas, prompted the research project reported in this article. The project studied the characteristics of this type of managerial data, then developed special visualization techniques for constructing visual representations to support planners in developing superior production plans. A visualization prototype called VIZ planner was designed, implemented and empirically evaluated in a laboratory setting. Using this tool, hundreds of products, thousands of components, and many other factors can be visualized to provide planners with production planning insight