When designing interfaces for browsing data-driven sites, creating navigation elements that are also visualization tools helps the user make better decisions. Wilson Miner demonstrates three techniques for incorporating data visualization into standards-based navigation patterns.
The affinity diagram, or KJ method (after its author, Kawakita Jiro), wasn't originally intended for quality management. Nonetheless, it has become one of the most widely used of the Japanese management and planning tools. The affinity diagram was developed to discovering meaningful groups of ideas within a raw list. In doing so, it is important to let the groupings emerge naturally, using the right side of the brain, rather than according to preordained categories.
Whether you're brainstorming ideas, trying to solve a problem or analyzing a situation, when you are dealing with lots of information from a variety of sources, you can end up spending a huge amount of time trying to assimilate all the little bits and pieces. Rather than letting the disjointed information get the better of you, you can use an affinity diagram to help you organize it.
All too often companies are focused on their own processes, wrapped up in a type of organizational navel gazing. They simply don’t know what customers actually go through. What’s more, logical solutions can cross departmental lines. Ideal solutions may require crossing those boundaries. An organization’s rigid decision making makes that difficult. Here’s where I believe IAs and UX designers can use our skills to make a difference. We have the ability to understand and to map out both business processes and the user experience. Visual representations can provide new insight into solutions that appeal to a range of stakeholders. Alignment diagrams are a key tool to do this.
It looks like the opening (quoted above) overreaches what the study actually does. The research only looks at backgrounds, but “chart junk” comes in many other forms: pointless 3-D effects, crazy colour schemes, excessive gridlines, cutesy cartoons, and more. The summary of this research in no way provides a scientific basis to argue, “I like the 3-D effect, and science supports it’s easier to read!”
When it comes to graphing data, most professionals show little method or creativity. They typically limit themselves to a small repertoire of graph types and select from it on the basis of habit, if not sheer ease of production. Similarly, the many books on graphing devote much attention to graphical integrity and readability, but little or none to graph selection. We developed a methodology to help engineers, scientists, and managers choose the “right graph” on the basis of three criteria: the structure of the data set in terms of number and type of variables, the intended use of the graph, and the research question or intended message. The first and third criteria allow one to construct an effective two-entry selection table.
Standards for designing data displays—for example, bar graphs, line graphs, pie charts, scatter plots—can be classified into four types: Conventional—emphasis on imitating generic forms that meet readers’ expectations. Perceptual—emphasis on optimizing reader behavior in accessing data visually. Informational—emphasis on transferring information clearly and concisely from designer to reader. Aesthetic—emphasis on taste, cultural values, and expressive elements. While each of these standards has merit, and some overlap occurs among them, they often conflict with each other, leaving the information designer in a quandary as to which standard to follow. Designers can resolve this dilemma by allowing the rhetorical situation—the readers of the display, its purpose, the context in which they use it—to guide the design process, telling designers when to follow, blend, or flout the standards.
If you have ever taken courses in technical writing, creating graphics was most likely addressed. Let's review the fundamentals and then delve deeper into creating tables in a technical document. Graphics, or visual aids, are usually divided into two broad categories: tables and figures. All tables are considered tables; all other visual aids are categorized as figures.
This paper is a critique of current approaches to the development of computer graphing and graph visualization programs. Developers of these programs model the user as an individual problem solver who is reliant on perceptual skills to create and interpret graphed information. Such a model of graphing is ill-suited to meet the complex needs of real users, a supposition that is supported by work in two major areas of graphing theory and research: the sociology of science and the educational research of mathematics and scientific students. These areas have not been traditionally cited when planning computer graphing or visualization programs or when assessing their usability. A review of the literature in these fields reveals that an over-reliance on a user's perceptual skills is unlikely to result in successful graph practices.
Tufte shares Orwell's impatience with doublethink and humbuggery, his insight that bad thinking and bad expression travel in a pair, and his awareness that they are usually deployed in the service of some brand of propaganda.
This PowerPoint file of 40 slides explains the types of graphs (line graphs, column or bar charts, pie charts, and ribbon graphs) that may be prepared with Matlab software. It tells how to choose the right one for the type of data to be displayed, taking into consideration the engineer’s purpose, audience, and context. It also demonstrates the commands used to make the graphs legible and easy to interpret.
Producing effective charts is essential to any document that conveys technical, scientific, or financial data. Here are four suggestions to ensure that your charts are effective and enhance rather than detract from your document.
A chart’s purpose is usually to help you properly interpret data. But sometimes, it does just the opposite. In the right (or wrong) hands, bar graphs and pie charts can become powerful agents of deception, tricking you into inferring trends that don’t exist, mistaking less for more, and missing alarming facts.
This discussion offers participants an overview of what process and procedure flowchorting is in the technical communication's universe of charting. The discussion distinguishes between information for “process” verses “procedure” and from other types of information. The discussion presents standards for using basic symbols and assembling them for effective and efficient communication design. The discussion presents various styles and formats for presenting process and procedures flowcharts, along with tools and techniques for creating and using flowcharts.
El proyecto genoma humano (PGH) genera un volumen de información inabordable sin el uso de medios sofisticados para su tratamiento. La visualización de información tiene aquí un gran campo de aplicación.
Graphite performs two pretty simple tasks: storing numbers that change over time and graphing them. There has been a lot of software written over the years to do these same tasks. What makes Graphite unique is that it provides this functionality as a network service that is both easy to use and highly scalable. The protocol for feeding data into Graphite is simple enough that you could learn to do it by hand in a few minutes (not that you'd actually want to, but it's a decent litmus test for simplicity). Rendering graphs and retrieving data points are as easy as fetching a URL. This makes it very natural to integrate Graphite with other software and enables users to build powerful applications on top of Graphite. One of the most common uses of Graphite is building web-based dashboards for monitoring and analysis. Graphite was born in a high-volume e-commerce environment and its design reflects this. Scalability and real-time access to data are key goals.
Infographics are a visual representation of data. When students create infographics, they are using information, visual, and technology literacies. This page includes links to help you develop formative or summative assessments that have students creating infographics to showcase their mastery of knowledge.
Infographics seem to be the “in thing” in information design these days, and more technical writing instructors are beginning to include them as assignments in their classes. I first became interested in infographics when I started to see how the genre of graphs and charts had shifted from simplistic representations to ones embellished with graphics (as those originally shown in USA Today). I then saw this trend move to even more complex visual and verbal presentations of quantitative and qualitative information in newspapers, websites, and books.
In design, our resources are limited. Priorities become a necessity. We need to ensure we are working on the most important parts of the problem. How do we assess what is most important?