week 10

This week, I want to start with visual perception. As we know, vision is one of the channels that we use to understand all kinds of information. Based on the test, 80% of the information that we receive comes from vision, which is an essential condition for our perception of information. Visual is a fundamental basis for the design. By the way, I found a visual book this week called Elements of Design: Rowena Reed Kostellow and the Structure of Visual Relationship(ISBN-10: 1568983298). Although that book is not directly related to this class, it is good to read.

The principle of vision is the foundation of the study of visual imaging. In the field of layout design, visual psychology mainly studies the general rules of people's visual feelings and psychological activities, and thus studies how to make designers and aestheticians communicate and communicate on emotional consciousness through layout design works. The explosion of information flow means that we will only give limited attention to those more beautiful pictures, so visual presentation is more and more critical. For visualization, we only need the core content. Adding some icons to the text title to decorate the page, a certain amount of beautification would be the right choice. 

https://www.pinterest.com/dubbu/data-visualization/

week 9

It's better to keep some essential things at the top of the page when designing compatible infographics for mobile phones. First, we know audiences have a lot of distractions, like texting with friends or reading emails. We need to make sure our content gets in front of them quickly. Therefore, the infographics should be distilled into simple visual forms, the simpler the infographic, the better.

Many smartphones display images that don't exceed 5,000 pixels. Therefore, when we do an infographic on the phone, we need to make sure that our infographic is no more than 5,000 pixels. It's essential to keep it short. Moreover, mobile phones need different widths. We should keep this in mind when designing mobile-friendly graphics.

In my opinion, using contrast colors to appear on opposite sides of the shade would bring better viewing. On the other hand, similar colors make it difficult to distinguish objects on the infographic. The stronger the contrast, the easier it is to read the infographic. Moreover, using contrasting colors can make the infographic more beautiful and stand out from the page.

I found some infographic picture from this link. It might be useful to give us some design ideas. https://www.pinterest.com/digitaliworld/mobile-infographics/

week 8

Because of the COVID-19, I read some first-hand news sources this week.

The first website I chose is Financial Time. What he does better than other artists is he thinks deeply about the design of each picture and explains to readers for each graph. For example, starting with 100 confirmed cases in each country to draw the number of infections in each country. By the way, the author used iNZight to draw his data. The different color scheme can cause some deviation, making the reading speed slightly slower. In color schemes, legibility is more affected by a black background than by a light one, especially if the background is darker than plain white. However, if the interface has a lot of text and requires the user to read it for a long time, using a light background will make the user feel more friendly. The writer uses bright pink makes the screen more breathable and roomy, so it more efficient for readers focused on the copy. https://www.ft.com/stream/e191658e-c66a-45bc-9bad-343bdc4210b3


Our World in Date uses the Data from WHO. The advantage is that we can see the Data from outside Europe and America, and the interface is interactive. What I like about this site is that they animate the confirmed COVID-19 cases. The advantage is that it attracts people's attention; after all, when we see something that can play, most of us want to click it. Moreover, the artcle is easy to read because there are no lots of professional words.https://ourworldindata.org/

week 7

When we are creating, we should always remember that we are not only designers but also editors. If we can't get clear information to our users, I think we've failed. Data warehouse more represents a way of data management and use, and it is a complete set of theories, including interpretation of the theme, color selection, picture application. What is now called big data is more of an increase in data magnitude and an update in tools. There is no conflict, on the contrary, but a better combination. The first skill we need to master is to look critically at graphics. Read newspapers, magazines, and textbooks. Visit websites that display infographics and visualizations; And analyze whether they help you understand what's important.

The problem with visualizing data is so hard to criticize the interpretation of the data, which is critical to the meaning of the data. So I went and looked up the TED talk on visual data, and I thought it was conducive.

https://www.youtube.com/watch?v=5Zg-C8AAIGg

I am focusing on the charts on different websites this week because of project 1. I found out about Best Data Visualizations of 2019 the day before yesterday. One of them, called A Year in Graphic Detail, which posted on The Economist, attracted me. I think the color selection and layout can be a template for my project.

week 6

The most important things to make a visible data are intuitive, interactivity, and real-time. So the steps of the iterative process of visualizing the data are divided into data acquisition, then graph selection (presentation), and finally, graph drawing. After reading the article, I think the whole data visualization can be divided into two directions: the first is to focus on display, and the second is to focus on analysis.

The interface of the data visualization program is like a dashboard of a car. You can get the critical information you want at a glance —— from the amount of remaining fuel to the speed of the vehicle to the range of the car. In short, visual data is the ability to display all the critical information in one view. An excellent data visualization tool should have both of the following features. First of all, it looks cool. Second is a bright yet popular color. Too much white is dull, too many colors feel messy, so the interface should be appropriately balanced. For example, in the screenshot below, our first reaction was to notice the map in the upper right corner because of the color.

And here is an excellent website to teach you how to select a color. https://www.webdesignrankings.com/resources/lolcolors/

week 5

The significance of the scatter plot is when X and Y are collected: (x1, y1), (x2, y2),... and (xn, yn). Each pair of Numbers (xi, yi) is marked on the coordinate plane. From the scatter diagram, we can observe the overall pattern and correlation of data distribution.

The correlation between two data, X and Y, is observed from the scatter graph. When the value of one data is higher than the average, the amount of the other data tends to be higher than the average. When the amount of one data is lower than the norm, the value of the other data tends to be smaller than the average, then the data X and Y are said to be positively correlated.

The sample points will be inclined from the bottom left to the top right. If the value of one data is higher than the average, the value of the other data tends to be lower than the average. If the value of one data is lower than the norm, and the value of the other data tends to be higher than the average, the data X and Y are said to be negatively correlated. The sample points will be inclined from the top left to bottom right.

I think the scatter graph shows the direction, pattern, and intensity of the correlation between two data sets. The linear relationship is especially important because it is the purest form, but the light of the eye does not quickly determine the intensity of the correlation. If the dispersion diagram shows a strong linear correlation between two numerical data, a line can be drawn in the dispersion diagram to give an overview of the direct relationship. The least-square method is a way of finding such a line, which is called the optimal line or the regression line.

When we have a lot of scatter graphs, to make it easier to distinguish, we can use different colors to identify each picture. Using color to determine the graph has the advantage of giving a quick idea of the strength of each graph.

week 4

We've been using data visualization for a long time, and images and charts have proven to be an effective way to convey and teach new information. Studies have shown that 80% of people remember what they saw, but only 20% remember what they read! It can even pass on ideas and events to future generations. The development of technology has further improved the opportunities brought by data visualization.

Perhaps the most crucial benefit of using data visualization is that it helps people understand data faster. We can highlight a large amount of data in a chart, and people can quickly spot critical points. Besides, this ability to display large amounts of data is another advantage of data visualization. A graph may highlight several different issues, and people can form different opinions on the data. Chart naturally opens up new avenues for business. One might find something unexpected in the data.

Visual presentation of data improves the ability to interpret information. It's not easy to find connections from vast amounts of data and information, but graphs and charts can provide information in seconds. Easy to see, can offer the required information.

week 3

People are used to starting from the top left corner of a chart or slide. When we are working with tables is to bring the design into context and the data to the core. We can not compete with users' attention with heavy borders and shadows and data. Instead, use narrow limits or remove the edges to highlight the data. It displays all the data in the form of points on a rectangular coordinate system to show the degree of interaction between variables. The value of the variable determines the position of the point.

A scatter plot shows the data correlation. If there is no correlation between the variables, it will appear as discrete points distributed randomly on the scatter chart. If there is some correlation, most of the data points will be relatively dense and presented in a particular trend. 

What I think is scatter plots are more research-oriented charts, allowing us to discover the hidden relationships between variables and make important guidance for our decisions.What struck me most was that we were able to represent Scatter plots in 3D, and this is the 3D Scatter plot video I found on YouTube yesterday.https://www.youtube.com/watch?v=lusJoN63jFY

second week

When I was reading this intro and the first chapter, I always thought I was reading a psychological book. The reason is that both sections mention a lot of sensory phenomena. For example, everything said about our senses is transformed. Deep down, our thoughts become simple or textured. The brain doesn't just process information through the eyes. It also creates mental visual images that enable us to reason and plan actions that help survive.

Many things I read in the second week are similar to what I read in the first week. For example, using color to express data is the right way. Because colored pictures can easily attract viewers, graphics, charts, and maps are not just tools for viewing, but tools for reading, double-checking, and double-checking. But we also need to be transparent while focusing on aesthetics. Making data beautiful is not just for eye-catching, but for people to understand. The relationship between visualization and art is similar to the connection between news and literature. An excellent way to find the correct data is to go to official websites, such as the UN website.

But I think that many times, it is easy for us to first consider setting colorful colors to achieve a neat appearance without considering whether these colors have practical significance. Obviously, colorful charts may help advertising performance, but distract readers from the precious data itself. In most cases of visualizing the data, we need to make the color matching easy to identify and distinguish. The second line is a counterexample. The recognition between colors is too low.

The role of an information architect is to anticipate this process and generate information graphics and visualization design information before the human brain attempts to make an essential part of the order. Visualization should be seen as a technology.

First week reading

Using statistical charts to analyze data and turn data In pictures, people can read the original data faster through visual symbols. Comparing charts present the statistical charts to improve people's understanding of data.

One of the most important conclusions I've learned in two chapters is that any chart, no matter how well designed, can mislead us if we don't pay attention. If we want to read the graph well, we have to pay attention to the nature of the content of the chart. In a nutshell, a figure is a way of turning symbols into language.

The core element of most charts is its visual coding. My favorite graph is bar graph. The reason is that most people know the bar graph and can understand what it means. The bar graph is very straightforward and gives us accurate information — the number of different lengths used in the bar statistics. Then the bar in a particular order. It's easy to see how many there are in the bar chart, so I think kids can understand that.

YEAH