Discussion on the visualization of web data in the era of big data

Source: Internet
Author: User

Data visualization technology can help people to understand the large amount of data information and discover the laws hidden in the data, so as to improve the efficiency of the data using the visual thinking ability of the human brain. In the face of big Data's profundity, it's no doubt that visualization is the most effective way to make a large data set more approachable and comprehensible. Research on data visualization applications in the context of big data will help us develop and innovate data visualization technologies.


Opportunities and challenges in the big data age


IoT, Cloud computing, mobile Internet, mobile phones, Tablet PCs, PC and all kinds of sensors all over the earth, none of them are either data sources or bearer methods. With the popularization of social networks, it is possible to make a detailed measurement of people's behavior and emotions. Mining users ' behavior habits and preferences, messy data behind to find more in line with user interests and habits of products and services, and products and services targeted adjustment and optimization, which is the value of big data. Big data is also increasingly emerging as a driving force for various industries. The strategic significance of big data technology lies not in mastering the vast data, but in the specialized processing of these meaningful data. In other words, if big data is likened to an industry, the key to profitability in this industry is to improve the "processing power" of the data and "add value" to the data through "processing".


 Data visualization technology and main features


Visualization of data ( Data Visualtechnology refers to the theory, method and technique of using computer graphics and image processing technology to transform data into graphic or image display on screen and interact with it. It can provide a variety of simultaneous data analysis of graphical methods, reflecting information patterns, data associations or trends, to help decision-makers to visually observe and analyze the data, to achieve direct information between people and data transmission, so as to discover the laws hidden in the data. The basic idea of data visualization technology is that every data item in a database is represented as a single element, a large number of data sets constitute the data image, and each attribute value of the data is represented in multidimensional data, and the data can be observed and analyzed in detail from different dimensions.


  The main features of data visualization technology are:


(1) Interactive, user can easily manage and develop data interactively;


(2) multidimensional, you can see a number of attributes or variables representing the data of an object or event, and the data can be categorized, sorted, combined, and displayed by its value in each heap;


(3) visibility, the data can be displayed with images, curves, two-dimensional graphics, three-dimensional bodies and animations, and can be visualized analysis of their patterns and interrelationships.


based on A Reference model for WEB-based data visualization


based on There are four types of reference models for data visualization of the Web:


(1) generate a graph describing the data on the server side, and then display the graph on the client, the client is displayed by the browser;


(2) After visualizing the server side, output VRML(Virtual Reality Modeling Language, abbreviated VRML ) into Java3d format of 3D model, back to customer, client leveraging support VRML or Java3d browser to draw and manipulate 3D model, the interaction of this way is confined to the drawing stage;


(3) customers can download visualization software bydownloading data, executing visual pipeline on client, using javaapplet to realize visualization calculation. Although the client can control the visualization process completely, the hardware and software resources of the client are high, and the control of the large-scale process is required.


(4) The server side provides the visual control page in htmlforms or javaapplet Way, the browser customer downloads the control page, Implement control of the visualization process.


Model 2 and model 3 require a Java drawing program for specific applications, model 4 Using the complex visual computing in server-side processing, avoid the client's high resource requirements, while the client can also complete the interactive rendering of visual results, with good interactivity and compute load sharing advantages, but the same programming complex. While model 1 uses the Tee Chart Pro aetivex control, it can be installed directly on the server side, dynamically generating graphics files on the server side (JPEG format), then pass the graphic back to the client and display it in the browser, which can be applied to any popular client browser.


  of Big Data Web Data visualization method Flow


  ① Discovery Problems


data visualization is all about solving a problem. Therefore, in the face of huge amounts of data, first of all, we should consider how to solve the problem of appropriate data extraction. When we ask questions to create information visualizations, we should focus on data-centric issues as much as we can. the questions that begin with "where", "What Time", "how many" or "how often" are usually good start-up, which allow us to focus on finding data within a particular set of parameters, and are more likely to find data for visualization. The question of "why" should be taken with extreme caution, which means that your more formal description of the data begins to turn into rewrite data analysis.


  ② Collecting data


data collection and collation is the most serious of data visualization. However, it is a very difficult task to find exactly what data is needed. In general, it is better to start with the data already available and try to find a way to portray it instead of trying to collect the data yourself. After the original data is obtained . The data can be re-processed by analyzing, organizing, grouping, or modifying it.


  ③ choose a visual representation of the data


after clarifying what you want to show, you need to use visual elements, color selection, dynamic and so on to give the chart a better visual experience. The process of visualizing data always revolves around the core goal of data visualization: To help readers understand the data better and more accurately. Common Web visualizations are: map, timeline, Network Diagram, tree, matrix, scatter, bubble, flowchart, line, label cloud, data table, radar chart, Heat force diagram, parallel axes, and so on.


 of Big Data how Web data visualization unfolds


  ① Size: This is the most commonly used visual presentation method. When identifying two objects, we can quickly differentiate them by size comparison. In addition, the use of dimensions speeds up understanding the difference between two sets of unfamiliar numbers. such as Baidu statistics, this application refers to the website traffic through the professional analysis, to help users constantly from the site traffic data Mining valuable information to guide the operation of the site. such as the number of visitors to the Web directory chart, the use of bubble area visualization, through the bubble size contrast, visually show the number of visitors to each page directory.


  ② color: Color is a great way to show big data sets, and we can identify many levels and tones through color. This makes color a necessary choice for presenting macro trends. When using color for visual creation, it is important to ensure that readers can distinguish between 45% and 55% data points.


  ③ Location: Location-based presentation is about associating data with certain types of maps, or associating it with a visual element that is relevant to a real or virtual place.


  ④ Network: The network presentation method shows the data points between the two-dollar connection, in view of the relationship between these data points is very helpful, online network visualization in the view of the site has been widely used, such as QQ has an application, you can use the network to view their networks.


  ⑤ time: Data that changes over time is typically depicted by the timeline. Many forms of expression need to be presented through a variety of means, which are mainly implemented by program algorithms on the computer. Designers in the choice of form of expression must also consider whether the audience can be very good to accept and absorb information, designers need to understand the visual psychology of the impact of user browsing. With the development of the Internet, the future of data visualization will also develop many new forms and features to help people understand the data and harness the data.


data visualization through image, graphics technology to image data processing, through information technology to accurate, real-time, automated and highly transparent processing. In the actual project, the large amount of data is displayed on the Web page in the way of graphic people , which helps to analyze the data and reveal the internal laws of the data. With the need of computer graphics, multimedia technology, man-machine interaction technology and various application fields, data visualization will have a wider development space.


Source: Paper Net Original address:http://www.xzbu.com/8/view-4852538.htm

Discussion on the visualization of web data in the era of big data

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