slide rules (design, build, and archive presentations in the engineering and technical fields) ||...

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Slide Rules: Design, Build, and Archive Presentations in the Engineering and Technical Fields, First Edition.

Traci Nathans-Kelly and Christine G. Nicometo.

© 2014 The Institute of Electrical and Electronics Engineers, Inc. Published 2014 by John Wiley & Sons, Inc.

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Generate Quality Graphs

Researchers tell us that 70% of human sensory receptors are in the eyes [1].

At their core, humans are visual creatures; even the blind “picture” the world

around them. Structuring strong visual information can be one of the most

powerful communication techniques that you have at your disposal.

Harnessing the basic human desire to see pictures is essential to effective

communication strategies.

This chapter covers the most effective ways to display data in various

graphical forms. It also showcases the kinds of visuals that engineers,

scientists, and technical experts use daily. Of course, the examples we

offer provide only models for connecting with your audience. Prepared

and applied with careful thought, your informational visuals will target

your audience in the best possible way.

110 7 GENERATE QUALITY GRAPHS

Portray complexity simply

“Any intelligent fool can make things bigger and more complex…it takes a bit of

genius—and a lot of courage to move in the opposite direction.” While it is often

attributed to Einstein, this thought came from E.F. Schumacher in 1973 [4]. Regardless

of who said it, the core idea remains. The work of technical and scientific professionals

is dominated by complex ideas, detailed technologies, and intricate systems of depend-

ency. We encourage you to communicate technical work in a manner that will reach

your stakeholders best.

Subject matter experts who can step back from the complexities of their material

and see the bigger picture have the most success with their clients, colleagues, and

leadership. And one of the most effective ways to reach audiences is with a good

graphic or visual. Any graphic provides an opportunity for the audience to become, in

effect, an “eyewitness” to the information [5]. As such, creating graphics with care is

essential to strong communication.

Because technical and scientific evidence is often incredibly intricate, visuals

can be the most efficient and effective means of communicating complexities.

Extensive research demonstrates that creating informational visuals increases

people’s ability to understand the information they convey [6–10]. Text is the slow-

est way to reach audiences; graphs are quicker, and pictures the quickest way of all

[11]. So, if your aim is to deliver complexity efficiently, using graphs and pictures in

your slides can serve you well.

An ever-growing set of research links good graphical representation of informa-

tion to the ethos (credibility) of the speaker [12] and demonstrates that a good display

increases in value to audience members when they find it easy to interpret [13, 14].

Thus, doing a graphic well not only promotes the information, but it also can increase

your ethos. Graphics frame rhetorical appeals, even in the most technical or scientific

of venues. Indeed, the beauty, applicability, and novel approaches of these visuals can

even influence whether or not a researcher or practitioner reaches the forefront of the

field [5].

The craft of creating meaningful, accurate, easily deciphered infographics is

not easy to master. Graphs impose serious cognitive load on audiences, so those

visuals must be created with great care. The act of seeing coded information

(graphics), decoding it, and then infusing it with applicable interpretation that

depicts a coherent and logical viewpoint is nothing to take lightly [11, 15]. And

when your graphic gets more complex, audience members may need to see it

more than once to comprehend it [16]. Apply these realities to a presentation,

where graphics may pass by quickly, and the challenge before you and your

audience is great.

Perhaps one of the biggest hurdles that technical and engineering communicators

face is overcoming the general notion that the audience will “get it” if they simply

show a chart or graphic, no matter how complex it is [10]. But we have seen that the

audience does not “get it” for a variety of reasons: the graphic was poorly executed, the

numbers/texts are too small, the speaker does not explain it well, or any number of

other reasons.

The failure of any presentation visual can stem from many sources, but most

often, the problem arises because the technical expert did not take the time to con-

sider the needs of the audience. Even though graphics, charts, and other outputs are

DETERMINE THE RIGHT VISUAL 111

heavily influenced by conventions [17, 18], the creator of those pieces must design

the information for quick and easy visual access, regardless of whatever substandard

norms prevail in the organization or industry. If a visual shows extraneous data points,

if tables bury data in crowded matrices, or if data lies trapped inside graphics that are

nothing more than “chartjunk” [8, 19], then audience members may leave the presen-

tation more confused than when they entered.

Identifying the typical design traps that ensnare even the most well-intentioned

professionals can help us avoid creating junk and, instead, propel us toward an elegance

and simplicity that would make even Einstein proud.

Determine the right visual

Whether the presenter is creating a plot, a chart, or a table, there are a few aspects of

design that can ensure success for the visual. These basic tenets can save you embar-

rassment and your audience frustration if applied well during the planning process.

Start by asking these questions.

1. Is the information included in the graphic suitable for the purpose of the talk? Technical specialists have access to numerous means of visualiz-

ing data outputs from tests, analyses, or models. However, just because

thousands of data points are available does not mean the presenter needs to

show them all in the graphic. Often, when technical speakers share unneces-

sary information/graphical displays with audiences, it is because they want

to prove that they did the work and they did it extensively. However, techni-

cal audiences tend to assume that the job has been adequately completed

already. As the speaker, your audience already regards you as some level

of expert on the information. Be selective when choosing which pieces of

information to present, whether in textual or graphical form. Astute content

integration is a mark not just of someone who has worked hard but of a truly

expert presenter.

2. Is the information suitable for a graphic? Sometimes, the information you

are trying to communicate in a graphic can actually best be presented another

way. Maybe it should be broken down via a series of smaller visuals, rather

than forced into one singular visual display. Consider the purpose and audi-

ence carefully when deciding upon data displays. Each time you start a design,

ask yourself, “What do others need to learn from this graphic?” If you find that

there are multiple answers to that question, you probably need to break down

the graphic into smaller parts or segments.

3. What sort of graphic will make the most sense to my audience? What are

the challenges to them seeing the graphic correctly? Any time you present

information to colleagues outside of your immediate team, reassess whether

complex displays or data-heavy plots will get the point across. Even techni-

cally savvy audience members will get frustrated with plots that are illegible or

difficult to interpret swiftly.

For example, in your daily work, perhaps you use a program that produces a specific

type of graphical output that takes experience to interpret (e.g., Minitab®). Sticking


with the default output of these displays may not make a great deal of sense for your

target audience members if they are not used to seeing those graphical displays. On the

other hand, if you are presenting to an internal working group, perhaps using familiar

visual outputs will serve your purpose, even if those visuals are not particularly lovely

to look at.

1. How will the audience interact with the graphic once displayed? Depending

on presentation logistics, your choices for designing the graphic will vary.

For instance, if you know that the presentation will be in a large room where much

of the audience will be situated far from the projector screen, then choosing a data

display that includes tiny data points in a scatter chart may not work well. Tailor

information so that your audience members can see it—wherever they may be

sitting. Likewise, if there are particular points on the graphic that you want your

audience to focus on, highlight them with a circle, arrow, or other graphical device

to save the audience time and confusion in searching for them.

As well, consider options for layering in portions of the graphic with custom

animations to build the graphic in real time with the audience. In this way, you

can take control of the discussion of the information presented in the graphic

and better anticipate the connections, comments, and questions it will elicit

from your audience.

2. Will all audience members have equal accessibility to the graphic? According

to the U.S. National Institutes of Health [20], at least 1 in 10 men experiences

some form of color blindness. Along with color-blindness issues, consider how

your graphic might appear in grayscale if the slide deck is printed. You will see

more on editing visuals that account for these issues at the end of this chapter.

Here, we will start with the easiest of the chart types and work toward more compli-

cated visual display types. In each section we will present a list of basic guidelines,

with examples, discussions, or case studies. Consider these guidelines as helpful

starting points for your informational visuals.

Design reasonable pie charts

Much maligned and often misused across mul-

tiple media, pie charts are not used often in the

technical fields. But they can also become

wonderful tools when handled well. They can

help us see the context of a larger issue and

understand quantity and quality of the items

that make up that bigger picture. We find that

engineers use pie charts more once they are

inside a job (rather than at school) as they con-

tribute to conversations that affect the bigger

picture. Pie charts do a fine job of showing

parts of a whole. However, their simplicity can

be deceptive; as with any presentation tool,

best practice guidelines apply.

The Value of VisualizationVisualization of technical information is key to its distribution and acceptance in many cases. Rare is the scientific, engineering, or technical topic that is not held up by a scaffolding of various visualizations.

The National Science Foundation hosts a yearly “International Science and Engineering Visualization Challenge” with a mission statement that proclaims “to illustrate is to enlighten.” Participants are asked to create the best graphical representations of their work possible because “illustrations provide the most immediate and influential connection between scientists and other citizens, and the best hope for nurturing popular interest. Indeed, they are now a necessity for public understanding of research development” [21].

DESIGN REASONABLE PIE CHARTS 113

Establishing a baseline of best practices for pie charts enables us to avoid many of

the typical mistakes that can happen with this simple chart type. The following list

provides a good starting point for pie chart creation:

Divide only a whole pie. Check the math and make sure your slices equal 100%.

Aim to have no more than six or seven slices in your pie chart. Any more can

cause information overload and destroy your pie chart’s at-a-glance utility

[14]. If needed, group several small slices into one larger category to

simplify.

Use a rainbow palette, rather than shades of one color. This maximizes quick

interpretation [16].

Test your pie, seeing if it prints well in black and white, if your audience is likely

to print the slides.

Articulate the meaning of the visual in the header and/or in the notes.

Label slices inside the slide, if they remain legible. This eliminates legends that

can cause increased cognitive processing times (a luxury we do not often have in

presentations) [11,13,14,16]. The next choice is to label the slices outside of the

pie. If the labeling becomes cumbersome, consider a well-honed legend to assist

in defining your categories and terms.

Arrange slices in descending order of percentages clockwise, as shown in

Figure 7.1, unless you have a very good reason to organize them according to

another construct.

FIGURE 7.1: Organize a traditional pie chart by descending order (starting at the 12 o’clock position) by percentages. Note that while the “Other” category should

(percentagewise) be placed second after “California,” the creator chose to place it in the 9–12

o’clock position because it is a catch-all category.


Create a pie with the 12 o’clock position as the starting point. If all pieces of the

pie are equally important, even though their percentages may differ, aim to have

a divider line pointing to the 12 o’clock position, top center, as illustrated in

Figure 7.1.

Emphasize a specific slice using one of the methods shown in Figure 7.2,

Figure 7.3, and Figure 7.4.

Use the notes pane (a feature found in slideware programs) to explain the signifi-

cance of the pie graph. Do not assume that anyone will come to the same conclusion.

See Chapter 10 for more on writing notes in order to archive slide information.

Do not insert 3D elements into the pie’s construction, as this distorts rather than

illuminates the actual numbers [7–9]. See Figure 7.5 and Figure 7.6 for a compari-

son. In Figure 7.4, notice how the segments of the pie in the front seem larger than

the ones placed in the background. This visual trick, accomplished by adding 3D

perspective, increases the area of those foreground segments and greatly distorts

the purpose of the graphic. But many presenters opt to use it, incorrectly thinking

that it adds polish to their graphics. However, in this case, the perception of “pol-

ish” actually translates to misunderstanding and additional conceptual work on

the audience’s part. (Read more on this topic later in this chapter.)

Remember, the purpose of a pie chart is to provide a comprehensible overview, quickly,

of the divisions of an entire entity. Check your design and underlying assumptions to

ensure full accessibility and analytical ease for the audience.

FIGURE 7.2: Explode a slice of pie for emphasis. Using the basic charting functions found

in popular presentation applications will allow a presenter to create emphasis where needed. In order

to visually emphasize certain information in a pie chart, emphasizing one slice could be an easy way

to focus attention on that category. However, do not explode the whole pie, as this adds nothing to

comprehension.

DESIGN REASONABLE PIE CHARTS 115

FIGURE 7.3: Color a slide in the pie chart for emphasis. Deploying your organization’s

color branding can guide your color palette and reinforce unity in the visuals.

FIGURE 7.4: Rotate a pie chart for a specific emphasis. Inside most charting formatting

options within slideware, presenters can reorient the default position to emphasize a particular slice

by placing it at the top.


FIGURE 7.5: Avoid a distasteful pie. While it is fun to play with dimension, angles, and 3D

effects when creating charts, doing so can skew or distort data. Notice how the slices in the fore-

ground (like Oklahoma) appear to be larger because of the addition of the edge thickness created

through the 3D effect. Compare this distorted pie with the original pie shown in Figure 7.1.

Representing the statistics accurately, without introducing design distortion, is the easiest way to

maintain the integrity of the numbers, encouraging appropriate interpretation of the facts.

FIGURE 7.6: Apply a shadow if you need dimension. A simple, clean, and creative way

to add some visual interest could be the application of a shadow element, which will not compro-

mise the integrity of the technical information.

DESIGN IMPACTFUL BAR CHARTS AND HISTOGRAMS 117

Design impactful bar charts and histograms

Bar charts and histograms appear frequently in engineering, scientific, and technical

presentations and papers because they provide visual comparison that the user can

digest quickly and easily. Even the most simple bar chart can house a staggering

amount of information, so crafting them with care requires due diligence. From

simple approaches for quick comparisons (Figure 7.7) to complex analyses

(Figure 7.8), bar charts present both an opportunity and a challenge for the informa-

tion designer.

Bar charts are best used when there are few independent variables. As such, bar

charts often represent qualitative information (Figure 7.9) [22].

After you have determined that a bar chart—as opposed to a table or pie—is the

best approach, clearly define the targeted information that your chart needs to display.

Knowing which elements need to stand out to the audience for consideration will

inform the visual approach you choose for a chart. The “Bar Chart Case Study” later

in this chapter provides an example of how chart management can produce various

versions of the same data set, all for different purposes.

As with pie charts, some basic rules guide bar chart creation.

Aim to represent a manageable set of information. If there are too many bars, the

information will still be overwhelming, even in visual format. If necessary, group

several small elements into one larger category to simplify.

Use comprehensible layouts to facilitate understanding. Traditionally, bar charts

plot two variables (the X- or Y-axis). The X-axis is usually the known value, and

the Y-axis is the unknown.

FIGURE 7.7: Get straight to the point. Simple, clean bar charts can make a strong

impact. Combined with a well-worded sentence header, this slide leaves no ambiguity.


FIGURE 7.8: Pop a focus color to aid understanding. In this more complicated bar

chart, the speaker wanted to emphasize the 2010 numbers for part of her presentation. To that

end, she used a bright red color that set apart those pieces from the other more subdued numbers

represented. Graphic by Britta Rowan. Used with permission.

Norming of the wells’ histograms ensures field-

wide consistency and data homogeneity.

After Adding 5 API500

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FIGURE 7.9: Simplify the data sets with a histogram. This histogram works well

because of its simple approach and clear purpose. Graphic adapted from Al-Alfy and Nabih [23].

Used with permission.

DESIGN IMPACTFUL BAR CHARTS AND HISTOGRAMS 119

Begin each axis at 0.

Delineate units clearly.

Create bars of enough length differentiation to provide comparative contrast.

If the scale impedes understanding, rescale.

Space at 1:1.5 scale between the data groups. Most software that creates bar charts

will do this automatically.

Label large bars inside the bar, if legible. This eliminates legends that increase

cognitive processing times (a luxury we do not often have in presentations)

[11,13,14,16]. If the labeling becomes cumbersome, consider a well-honed

legend to clarify categories and terms.

Use a rainbow palette, rather than shades of one color. This maximizes quick

interpretation [16].

Build a bar chart during the actual talk, piece by piece, using the animations fea-

tures in your slideware. Bring in data groups one by one if it will help the audience

achieve a deeper understanding of the material during your presentation.

Test your chart to determine if it prints well in black and white and if it is readable

by color-blind audience members.

Do not insert 3D elements into the chart’s construction, as this distorts rather than

illuminates the actual numbers. Refer to the sidebar about transforming a bad 3D

bar chart, illustrated in Figure 7.10, Figure 7.11, and Figure 7.12.

Articulate the meaning of the bar chart in the header and/or in the notes pane.

Use the notes pane to explain the significance of the graph. Do not assume that

your reader will come to the same conclusion as you did with your graphic. See

Chapter 10 for more on this aspect of archiving information in the talk.

The term “histogram” is used widely to mean almost any kind of bar chart in some

cases. However, for our purposes, these additional guidelines will help:

Use histograms to plot continuous or distributed data, wherein the bars contain

a range of data values. For example, a measurement for one bar might be

25–50 pounds.

Group data values in such a way that they make sense to the audience. They

should be useful take-aways.

Do not separate the bars or stacks in a histogram. They should snug up to each other.

Construct a bar to reveal the frequency density per interval (the frequency divided

by the width of interval).

Keep in mind that the total area contained in the histogram should be equal to the

number of the data.

Transformation: Creating Quality Bar Charts

In this example set, we begin with a terrible version of a bar chart (Figure 7.10)

that has experienced too many enhancements within the software options. Observe

the progression toward clarity between iterations of this chart (Figure 7.11 and

Figure 7.12).

FIGURE 7.11: Simplify your approach. With a few clicks, this chart is somewhat

improved. It still uses 3D without purpose, but the colors are cleaner. The added visual noise of

the pyramids has disappeared. However, the header still fails to describe the overall meaning of

the chart, and the lingering 3D design elements make it difficult to discern actual bar values.

Figure 7.12 moves closer to being helpful.

FIGURE 7.10: Avoid this kind of poor chart. When it comes to options for making

charts, remember that just because you can does not mean you should. There is rarely an advan-

tage to showing chart data in 3D (surface plots aside). Indeed, using 3D effects without purpose

can harm your credibility because they make it harder for your audience to understand and

assess the information obscured by your flashy design. Notice, too, that the header in this slide

completely fails as a content indicator (“Analysis” of what, we might ask). Look to Figure 7.11 and

Figure 7.12 for a makeover of this data set.

DESIGN SCATTER XY CHARTS AND SCATTER PLOTS 121

Along with those basic design principles, several other elements can be used in a

presentation to enhance understanding. For example, as discussed in Chapter 6,

applying simple animations will create a slide build; bringing in bars one by one can

control how much information the audience sees all at once, lessening the likelihood

of misinterpretation.

Like pie charts, bar charts can quickly showcase comparative data for an audi-

ence. To ensure greatest success with bar charts, consider how much information your

audience can glean from the graphic at once. Control the flow of information, ensure

accessibility, and communicate the overall point in a full-sentence header for greatest

information transfer.

Design scatter XY charts and scatter plots

As with line charts, scatter XY charts (also known as scatter charts, scatterplots, scatter-

grams, etc.) can house a multitude of data points. They are a classic approach to complex

information because of their ability to show trends in complex statistical environments.

When presenting, however, be sure that you simplify your chart enough or provide

indicators in your visual that will guide your audience as to where to look in order to

interpret the information correctly.

FIGURE 7.12: Create a strong bar chart that allows immediate access to the information. While there is always room for improvement, this version of the bar chart series

makeover makes great strides in the right direction. A flat chart is more honest and usable. This

approach allows for easier comparisons of data sets with no visual noise. Note, too, that the

header’s wording guides interpretation of the chart. There is no longer any question about how to

understand the information provided.


Scatter charts provide a visual representation of a correlation between two or more

variables. Scatter charts provide a convenient way to display relation ships between non-

linear variables; as such, they are often used for quality control visualizations.

Here are some basics for scatter charts.

Start from zero for both X (abscissa) and Y (ordinate) axes to maximize clarity

when at all possible and reasonable. If the values do not lend themselves to a 0

start, mark values clearly in the lower-left corner (Figure 7.13).

Stick to traditional formats that house values on the Y-axis whenever possible.

Label units of measurements on each axis; best practice is to include these meas-

urements in parentheses. Make them large enough for all audience members to see

them when you project the slide.

Pick scale intervals that make sense—not too frequent and not too coarse. As well,

subticks within the intervals should not be too dense.

Use data markers (triangles, squares, circles, etc.) to mark different sets of data.

Make sure that data markers are big enough to be pulled apart visually. They can

also be color-coded, retaining their shapes (Figure 7.14).

Do not connect markers with lines.

Show a general trend using a trend line for ease of interpretation (Figure 7.15).

Insert other graphical overlays to aid interpretation [15].

Indicate a positive correlation with the left side of the chart starting low and rising

to the upper right.

Plot the dependent variable on the vertical axis.

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FIGURE 7.13: Plot dimension as clearly as possible. With this chart, three values were

being gathered for four different inputs. Not only is color used for each input, but different shapes

will still allow audience members to interpret the data accurately if they print the slide in black and

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FIGURE 7.14: Shade and colorize for maximum effect. Scatterplots can house

thousands of data points that can instantly portray complex information in an understanda-

ble format. Be sure to colorize for the highest contrast, as seen here [25]. Graphic used with

permission.

FIGURE 7.15: Use scatter charts with trend line for easy interpretation. Trend lines

help audience members make a quick assessment of the information in the graphic. Although the

axes in the lower left do not start at 0 in this example, they are clearly marked.

DESIGN SCATTER XY CHARTS AND SCATTER PLOTS 123


Place grid lines only if they are necessary. Use your presentation application’s

capabilities to make them fade back to a gray in order to give the data lines

visual prominence.

Make charts large enough to project well during your talk.

Scale and size the graphics so they will be clearly visible during the presentation

and that will also print out well for the audience, if need be.

Place any explanatory comments and citations in the notes pane to enhance

archival quality of the slide deck. Use these notes to explain the significance of

the data and how to interpret it. Do not assume that your legacy audience will

come to the same conclusion as you did with your graphic. For more on notes

and archival slide decks, see Chapter 10.

Transformation: A Chart Grows Up

In this series of visuals (Figure 7.16, Figure 7.17, Figure 7.18, Figure 7.19, and

Figure 7.20), we start with a chart that has too much information in it. Step by

step, we work toward a chart that has focus, clarity, and purpose. Remember, most

of the time, the audience does not want to see every single data point. Rather, the

presentation should emphasize the most important data to facilitate informed

decision-making.

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FIGURE 7.16: Version 1 has too much data. While this graphic delineates each compo-

nent charted for temperature over time with a readily identified unique shape marker, the size,

number, and arrangement of each component line make them extremely difficult to differentiate.

In addition, the slide fails to provide overall point of this analysis, which makes it easy for the

audience to miss it. Finally, the dark background only compounds the problem of readability.

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FIGURE 7.17: Version 2 makes some compelling changes. Adding a concise sentence

heading that explains one point of the analysis adds value to this version. Altering the background

color also adds contrast and sharpness—two elements that were lacking with the gray background.

However, some of the brighter neon colors (yellow, bright pink) become problematic to view on the

white background and should be retouched for better viewing. Overall, though, the point that the

speaker intends to make with this chart seems obvious. Temperature typically increases over time

in any electrical operation; do you really need a graphic to prove it?

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FIGURE 7.18: Version 3 focuses attention. With this version, the speaker has highlighted

a particular region where the audience should focus, indicating that this graphic is making a more

nuanced point than the sentence header currently voices.

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FIGURE 7.19: Version 4 drills down. Two major changes to the graphic dramatically increase

its value and accessibility to the audience. First, the sentence header now indicates the nuanced

detail that it was lacking in previous iterations: the data set records temperature differences among

states of operation that were not easily seen and not discussed in previous versions. Zooming in on

a notable section of the graphic (and adjusting its axis labels accordingly) helps us see those changes

much better. And adjusting the colors to deeper hues than the neon ones used in previous versions

enhances the graphic’s accessibility by adding necessary contrast for easier viewing.

FIGURE 7.20: Version 5 goes one step further. The graphic can expand on the slide

because the legend was eliminated. Labeling the lines directly might increase accessibility even

further by allowing for the graphic to expand due to the loss of the external legend.

CRAFT LINE CHARTS 127

Craft line charts

Also commonly called a line graph, this graphical format is a kind of scatter chart

most often used to indicate correlations between sets of collected data. Deceptively

simple, a good line chart can be difficult to create if basic best practices are not

followed.

Use these guidelines when you begin to construct line charts.

Label starting values for both X- and Y-axes to maximize clarity (Figure 7.21).

Keep numerical values on the Y-axis, when possible, as per traditional formatting

conventions.

Report time factors on the X-axis as a common practice.

Label units of measurements on each axis; best practice is to include these meas-

urements in parentheses or brackets. Make them large enough for audience mem-

bers to see when you project the slide (Figure 7.22).

Differentiate lines of data using distinct data markers (triangles, squares, circles,

etc.). Make your markers big enough that you can pull them apart visually. You

can also color-code them, retaining the shapes for specific data sets.

Connect the markers with lines only if you are trying to show trends (usually

trends over time). If you are not illuminating a trend, leave the markers unat-

tached (whereby it becomes an XY chart or a scatter chart, suited to different

purposes). In some areas, it is customary to show measured data as points along

with modeled or trending lines (with no point labels).

FIGURE 7.21: Label peaks clearly with exact values to assist information retrieval. Notice, too, that the axes are labeled clearly, and the overall point of the graphic is

nicely described by the sentence header.


Use grid lines only if necessary. Use your slideware application’s capabilities

to make grid lines fade back to a gray in order to give the data lines visual

prominence. For most slideware programs, clicking on a grid line will launch

the editing portal where you can specify the grid lines’ color intensity.

Make line charts large enough to project well during your talk.

Use a scale and size that will print out well for the audience, should they choose

to print out your file.

Place any explanatory comments in the notes pane to enhance archival quality of

the slide deck. Use these notes to explain the significance of the data line or lines.

Do not assume that your legacy audience will come to the same conclusion as you

did with your graphic (see Chapter 10).

Map out area graphs

Area graphs are similar to line charts in that they are commonly used to show data over

time. They are often used to track multiple inputs (one or more groups) of related

information that pertain to a whole set. When creating an area graph, begin with the

same best practices for line graphs and alter the visual to impart the most clarity for the

purpose (Figure 7.23 and Figure 7.24).

FIGURE 7.22: Indicate critical information in corresponding data series. When

using both the left- and right-hand sides of a line graphic to showcase a data series, be sure to

indicate which line corresponds to which side. By using small arrows to clearly show that

correspondence (instead of relying on color or other mechanisms that can collapse or elude the

viewer), the overall graphic guides the viewer to the main point of the comparison (also summa-

rized by the sentence header here).

MAP OUT AREA GRAPHS 129

FIGURE 7.23: Construct area graphs carefully, as they can easily become difficult to parse. If your audience is not used to seeing area graphs, they might find them confusing.

The graph in this example does a decent job of conveying the general impact of the data but

leaves the meaning somewhat confusing, despite the sentence header.

FIGURE 7.24: Visualize and interpret information in a way that makes sense to the audience. By reinventing the approach to the information in Figure 7.23 and expanding it,

the graph begins to make more sense. The text balloons help interpret the context even more, thus

presenting the story of the issue in a more direct light.


Think through flow or process charts

Useful in many aspects of technical communication, flowcharts are visual representations

of processes and decisions. Specifically shaped forms indicate operations, and arrows

show the flow of work or decisions. When designed with the audience in mind, flowcharts

can help orient the audience to a process and help participants see where they may fit into

the flow, have an impact, or need to change some aspect of the flow of work.

However, poorly designed flowcharts are notorious for adding unnecessary com-

plexity to a process, overwhelming audiences with too much information, orienting

process information in befuddling ways, and being generally incomprehensible.

Given their bad rap, we need to be especially cognizant of traps to avoid when

brainstorming and designing flowcharts.

Specifically, flowcharts must present clearly any hierarchy within the process or

organization. We recommend starting at the top of the visual with the highest level of

the hierarchy. Readers must know where to begin and how to navigate within the chart

often without referring to a key, so the chart must assign a different symbol to each

type of item depicted and depict connections in a way that indicates both the direction

of the flow and the connection type (Figure 7.25).

To aid in your design, here are few questions to consider as you create your flowchart.

What does my audience need to learn/understand from seeing this flowchart?

Is the structure I’m depicting hierarchical in nature?

Is there a recognizable start point and end point to the flow of information?

FIGURE 7.25: Use traditional flowchart shapes. Applying familiar flowchart conventions

makes it easier to indicate crucial steps and intersections.

THINK THROUGH FLOW OR PROCESS CHARTS 131

Does the structure contain any contingencies such as time, either/or options, and

if/then options? If so, are they clearly represented?

Are there layers, levels, or time distinctions that you could build into the chart

through the use of animations or a slide-build sequence?

Has the chart draft been validated with others who are familiar with the process/

structure?

Has the flow of the chart been tested with others who are not acquainted with the

process/structure?

To signal ownership or indicate responsibility for tasks along with a time frame for

getting them done, adding swimlanes is another option for your flowchart (Figure 7.26).

When depicting systems engineering, swimlanes visually organize actions. Deploy

swimlanes by listing the group or individual responsible for a set of tasks at the top of

the chart in an associated column. Within that column, depict the flow of tasks to be

completed by that group/individual. Use the bottom of the chart to show key target

dates, if desired.

While swimlanes can work well for relatively constrained processes and projects,

they can become cumbersome as projects grow in scope. They also often require the

ability to group people together to assign tasks and time frame to completion. If you

are using swimlanes to depict ownership or resource allocation, be careful to ensure

readability of the processes residing within the lanes as well as clear tracking of con-

nections across lanes. As with all flowcharts, careful use of text is critical to readability

and accessibility.

FIGURE 7.26: Insert swimlanes into flowcharts to add more value. Swimlanes can

be horizontal or vertical. They can indicate departments, individual people, times, cycles, or other

elements that are critical to the workflow depicted.


Address assorted other visual outputs

From Gantt charts to box plots, most slideware tools provide a variety of visual data

outputs for technical findings. For many kinds of quality analyses, software can play a

vital part in collecting, vetting, and configuring outputs, but those outputs may not

always take the most elegant of forms. However, they are all capable of delivering

certain types of data efficiently, and if your audience is accustomed to seeing such

graphics, then use them to convey information.

It would be difficult to outline the ways in which to make each and every one of

these kinds of charts or visual representations perform better in your presentation.

However, take into account these general guidelines, and you will create better visuals

for your target audience.

Perform a goals analysis when creating the graphic. Design the graphic to hit that

goal visually.

Label elements at a size large enough to read, the axes and units.

Deploy a visual cue that will guide the audience toward the relevant spot on the

graphic (insert a circle, an arrow, or a box arrow, or use a markedly different color).

Write sentence headers for the slide, summarizing the take-away point of the visual.

FIGURE 7.27: Insert simple shapes to guide the eye. When test outputs are not beauti-

ful, but still functional, they can be complex for a viewer. In this case, a heavily weighted black

arrow directs any audience member to the exact area that needs discussion. The sentence header

is key as well. Can you image how badly this slide would fail as an informational piece if the header

just said “Results” and had no arrow?

GRAPH ETHICALLY 133

Eschew headers altogether when necessary to allow the visual to fill the screen.

It will be crucial, however, to use your notes feature to provide information if you

use this approach (see Chapter 10), as shown in Figure 7.27.

Treat less than lovely graphical outputs with attention; they may need deep expla-

nation for some audience members to unpack (Figure 7.28).

Use the notes pane to house materials, references, and explanations in order to

create better legacy items (see Chapter 10).

Reference longer help resources, such as those listed in the “Further Reading” at

the end of this chapter.

Graph ethically

Perhaps one of the most remarkable discussions about graphics began in 1983

when Edward Tufte published his groundbreaking book, The Visual Display of Quantitative Information, discussing best practices and new insights on quantitative

I-MR Chart of Vacuum

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202

200

198

196

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1 4 7 10 13 16 19 22 25 28

UCL=202.62

UCL=5.489

LCL=193.68

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FIGURE 7.28: Work around less-than-stunning visual outputs. In some cases, the

output mechanisms of statistical workhorses are not pretty, but they may be the most beautiful

thing in the world to the technical experts that work with them every day. When we cannot

change the backgrounds or the colors of the lines, we work with what we have. In this case, while

the red and green lines fail for color-blind viewers, we see clear indicators of their meaning on the

right side. Remember, too, that while some of your audience sees outputs like this every day and

is comfortable interpreting them, others in the audience may need your expertise to unpack the

high level of information being presented.


graphical design from a practitioner’s point of view [6]. While Tufte alone did not

initiate scholarship on the ethics of graphics, his beautiful books and his excellent

examples pushed readers to a new level of sophistication and clarity in their visual

designs.

The power of graphics (graphs, charts, visuals) can also affect the subject matter

expert’s ethos [3]. Indeed, using charts and graphs can build an “ethos of rigor” for the

speaker (or writer) and should be tended to carefully [24].

Theorists have offered fascinating viewpoints about the intersections of science,

definitions, accurate data, visual representation, and the reliability of interpretations of

data from visuals [25]. In order to produce an accurate and responsible graphic, a pres-

entation designer must complete the requisite steps: choosing the correct data visual

output, designing the graphic, labeling the graphic, and then testing the graphic to

ensure that the audience interprets the data as the presenter intends. These are rare and

ideal practices indeed, especially when time is a factor and managers are pushing to

move up your presentation by five days. But if pictures are indeed worth a thousand

words, then we must craft our work to ensure that those thousand words are the ones

we choose.

When turning data into visuals in order to reach audiences, you run the risk of

presenting the data in a way that your audience may construe as manipulating that data

to serve a particular agenda. For instance, should you leave out an outlying data point

because it skews results that are otherwise consistent? Do you put an angle on a pie

chart that emphasizes a compelling percentage at the expense of clarity for the other

percentages? Technical professionals prefer to believe that graphics are “just the

facts”—nothing more, nothing less. However, the very construction of a graphic is an

activity that necessarily puts filters and perceptions on data. Translating raw data into

graphical form means that the idea of what that data represents is being reformulated

by the translator.

Even by using company-branded colors in your graphics, you impose a kind of

influence on the data. Often, it is a benign influence. The larger concern is when data

is skewed deliberately in order to push an agenda, a perception, or an argument. For

example, this simple pie chart (Figure 7.29) is a classic example of using 3D effects in

bad faith.

A more fair and balanced view of this would be to flatten the pie chart, leaving the

slices to represent the data more accurately (Figure 7.30). For more discussions about

pie chart design, refer to the section earlier in this chapter.

The larger point is this: treat your audience members as equals, not people who

need to be manipulated. It is all too easy to misrepresent data when using visual tools,

but you should never compromise the integrity of the information you are presenting

in order to secure certain outcomes.

It bears repeating that any professional in the engineering, scientific, or techni-

cal fields should be aware of the ethical guidelines that shape the profession. For

anyone working with statistics and data, the “Ethical Guidelines for Statistical

Practice” deserves a look and can be found at http://www.amstat.org. Engineers can

review ethical codes at the National Society of Professional Engineers at http://

www.nspe.org. Other professional organizations offer ethical guidelines as well;

there is a nice clearinghouse of those conduct codes on website of the Illinois

Institute of Technology’s Center for the Study of Ethics in the Professions (http://

ethics.iit.edu).

GRAPH ETHICALLY 135

FIGURE 7.29: Do not misrepresent your data to make your graphic work. In this

example, the 3D effects lead viewers to a wrong conclusion: the green slice aligned with the asset

of “property” is nearest to the audience and is pulled out from the rest of the pie; it is worth 11%.

Compare the green slice with the “equipment” slice, just to the right of it, worth 22%. Visually,

the 11% slice clearly covers more acreage and is positioned to capture attention because it

seems to be a large concern.

FIGURE 7.30: Flatten the chart to represent the data more accurately. In this case,

the presentation was about securing property to start a new firm, and the presenter wanted to

highlight the property costs. Thus, the green property slice is rotated to the top, providing empha-

sis for the speaker’s point.


Create accessible graphics

If technical experts are earnest in their efforts

to reach as much of the audience as possible,

all of the input should be produced with

thought and care. One aspect that presenters

often overlook is the particular needs of our

colleagues that have color-blindness issues.

It is estimated that around 10% of some

populations are affected with color blindness

of some sort or another. Of those, most have

difficulty with distinctions between red and

green. Despite the prevalence of color-blind-

ness issues in the population, presentation

visuals, and technical communications in gen-

eral, still frequently make the mistake of

assigning meaning with the use of color.

In the technical fields, careless use of reds and greens to establish or contain

meaning can be particularly problematic—even dangerous—when applied to safety

messages. When a visual of any sort relies solely on color coding for interpretation,

the chances for misinterpretation or mistakes increase. Look at Figure 7.31, where

color coding is in place for a heat indicator; this same graphic will fail for a color-

blind participant, as shown in Figure 7.32.

For anyone who is not affected by color blindness, the screen shown in Figure 7.31

would make sense. The trouble comes when a color-blind colleague tries to interpret the

same graphic: the visual collapses (Figure 7.32). A solution lies in adding a layer of visual

indicators. In this case, simple labels or secondary indicators will do the trick (Figure 7.33).

FIGURE 7.31: Be alert to possible problems when working with a red/green set of indicators. Here, there is no secondary indicator to show where green critically turns to red.

See how this visual looks to someone with a color-blindness impairment in Figure 7.32.

Testing Graphics for Color-Blindness AccessibilityTo test your graphics for potential problems, you can run your graphic through programs that check for color-blindness issues. Here are a few:

Vischeck, found at http://vischeck.com, is a project coming out of the Wandell lab at Stanford University. Some of the examples in this section were created using this program.

The experts at Etre LLC also have a convenient and quick graphics tester, found at http://www.etre.com/tools/colourblindsimulator/.

For more information on creating accessible slides, visit http://office.microsoft.com/en-us/powerpoint-help/creating-accessible-power-point-presentations-HA102013555.aspx.

CREATE ACCESSIBLE GRAPHICS 137

FIGURE 7.32: Check visuals in an online color-blindness checker to deter-mine if there is a communication problem. Using Vischeck® online, we can quickly

determine that this graphic will fail as a communication tool for color-blind audience

members.

FIGURE 7.33: Use secondary indicators when green and red hold meaning. Simple accommodations in your figures can assist for color-blind users and also when printed in

black-and-white mode.


Of course, another way to avoid these problems is to eschew red/green pairings

altogether. For full discussions and examples of how color-blindness awareness should

play a part, do a bit of research online and run your graphics through a color-blindness

checker.

Along the same lines, it is extremely important to anticipate if your work will ever

be used in black and white only. If there is a chance that your slides or visuals will go to

grayscale, then design proactively for that contingency. In grayscale, any meaning that

you have assigned only by color can completely collapse; your pie chart can become one

large black dot, or the bars in your bar graph may become indistinguishable from one

another.

Frequently asked questions about graphs

I took my graph from a source rather than creating my own. How do I reference it?Any time material, whether it is a quote, a chart, or any kind of visual, you should

reference it. To keep the slide as clean as possible, use the notes pane to house

referencing. Citation systems that are commonly used for technology and scientific

purposes are APA, IEEE, and CSE. Resources abound on the Web, guiding users

through the process of proper attribution of sources.

Can I take numbers from an outside source and make my own graph?It is perfectly acceptable to take statistics or other gathered data from another source

and translate it into a usable graph of your own. Be sure to reference the original

source and provide the wording “adapted from [source]” in the notes pane as part of

your attribution/citation efforts.

Instead of using shapes or arrows to get audiences to look at the right spot, I want to just use my laser pointer. What is wrong with that?Laser pointers have limited use during a talk, even though many people seem to use

them with impunity. If you think you need a laser pointer to guide people’s attention,

then your slides have already failed. If you need to emphasize something on a graph

and you need a laser to do it, then your slide is probably too complicated. If you plan

on using the laser to emphasize text, then you have too much text on the slide. A feeble

dot of light will not make your presentation better.

We certainly know how much many speakers love their laser pointers, but often

they are a hindrance and add little to the talk. Before turning on the laser, think

carefully about these issues.

1. Laser pointers are difficult for audiences to see. While it is very apparent to the

speaker where the laser’s dot is on the screen, it takes a few seconds for audi-

ences to locate it and focus attention on the marked area. By then, the speaker

has usually moved on.

2. Lasers are very hard for anyone with visual impairments to see [28].

REFERENCES 139

3. They do not work on a phone conference or webinar. Because so much techni-

cal work is done live, but online, with colleagues in different localities, lasers

are useless in these situations.

4. Lasers do not become part of the archive of the talk. Anything you point to

during a talk with a laser will not be reflected on the archived slides. This could

cause a good deal of emphasis and important focus to be lost in slide decks

preserved for future use (see Chapter 10).

5. They call attention to any hand tremors you may have. Often, due to nerves, a

speaker’s hands will shake during a talk. Using a laser magnifies this issue.

6. Many speakers who use laser pointers do not control their motions well.

They circle items multiple times, zip around the slide, and dash here and

there. It can become a bit of a circus for the audience, trying to track the

small red or green dot.

References

[1] J. M. Jacobs, R. Hammerman-Rozenberg, Y. Maaravi, A. Cohen, and J. Stessman,

“The impact of visual impairment on health, function and mortality,” Aging Clinical and Experimental Research, vol. 17, no. 4, pp. 281–286, 2005.

[2] C. Hanaford, Smart Moves: Why Learning is not all in Your Head. Arlington, VA: Great

Ocean Publishers, 1995.

[3] P. Wolfe, Brain Matters: Translating Research into Classroom Practice, 2nd ed. Alexandria,

VA: Association for Supervision & Curriculum Development, 2010.

[4] E. F. Schumacher, “Small is beautiful,” The Radical Humanist: UNESCO Publications on Education, Science, and Culture, vol. 37, April 1973.

[5] D. Hutto, “Graphics and ethos in biomedical journals,” Journal of Technical Writing and Communication, vol. 38, no. 2, pp. 111–131, 2008.

[6] E. R. Tufte, Visual Explanations: Images and Quantities, Evidence and Narrative.

Cheshire, CT: Graphics Press, June 1997.

[7] E. R. Tufte, Envisioning Information. Cheshire, CT: Graphics Press, 1990.

[8] E. R. Tufte, The Visual Display of Quantitative Information. Cheshire, CT: Graphics

Press, 1983.

[9] E. R. Tufte, The Cognitive Style of PowerPoint, 2nd ed. Cheshire, CT: Graphics

Press, 2006.

[10] W. Winn, “Contributions of perceptual and cognitive processes to the comprehension of

graphics,” in Comprehension of Graphics, W. Schnotz and R. W. Kulhavy, Eds. pp. 3–27.

Amsterdam: Holland Publishers, 1994.

[11] P. A. Carpenter and P. Shah, “A model of the perceptual and conceptual processes in graph

comprehension,” Journal of Experimental Psychology: Applied, vol. 4, no. 2, pp. 75–100,

June 1998.

[12] B. Latour, “Drawing things together,” in Representation in Scientific Practice, M. Lynch

and S Woogar, Eds. pp. 19–68. Cambridge, MA: MIT Press, 1990.

[13] S. M. Kosslyn, Elements of Graphical Design, New York: Freeman, 1994.

[14] S. M. Kosslyn, “Understanding charts and graphs,” Applied Cognitive Psychology, vol. 3,

pp. 185–225, 1989.

[15] N. Kong and M. Agrawala, “Graphical overlays: Using layered elements to aid chart read-

ing,” InfoVis 2012. UC Berkeley Computer Science Division, October 2012. Available at

http://Vis.berkeley.edu/papers/grover (accessed on 21 December 2012.


[16] R. Ratwani, J. G. Trafton, and D. A. Boehm-Davis, “Thinking graphically: Connecting

vision and cognition during graph comprehension,” Journal of Experimental Psychology: Applied, vol. 14, no. 1, pp. 36–49, 2008.

[17] C. Kostelnick and M. Hassett, Shaping Information; The Rhetoric of Visual Conventions,

Carbondale, IL: Southern Illinois University Press, 2003.

[18] C. Kostelnick and David D. Roberts, Designing Visual Language: Strategies for Professional Communicators, Boston, MA: Allyn & Bacon, 1998.

[19] B. Weidenmann, “Code of instructional pictures,” in Comprehension of Graphics,

W. Schnotz and R. W. Kulhavy, Eds. pp. 29–42. Amsterdam: Holland Publishers, 1994.

[20] National Center for Biotechnology Information, Color Blindness, 2009. Available at http://

www.ncbi.nlm.nih.gov/pubmedhealth/PMH0001997/ (accessed on 18 November 2012.

[21] National Science Foundation. International Science and Engineering Visualization Challenge, 2011. Available at http://www.nsf.gov/news/special_reports/scivis/challenge.

jsp (accessed on 12 November 2012).

[22] G. R. Bertoline and E. N. Wiebe, Technical Graphics Communication, 3rd ed. New York:

McGraw-Hill, 2003.

[23] I. M. Al-Alfy and M. A. Nabih, “3D slicing of radiogenic heat production in Bahariya

Formation, Tut oil field, North-Western Desert, Egypt,” Applied Radiation and Isotopes,

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[24] O. Ersoy, E. Aydar, A. Gourgaud, and H. Bayhan, “Quantitative analysis on volcanic ash

surfaces: Application of extended depth-of-field (focus) algorithm for light and scanning

electron microscopy and 3D reconstruction,” Micron, vol. 39, no. 2, pp. 128–136,

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[25] M. Olabarrieta, J. C. Warner, B. Armstrong, J. B. Zambon, and H. Ruoying, “Oceanic

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ocean–atmosphere-wave-sediment transport (COAWST) modeling system,” Ocean Modeling, vol. 43, no. 44, pp. 112–137, November 2012.

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Further reading

J. Bertin, Semiology of Graphics: Diagrams, Networks, Maps, Translated by William

J. Berg. Madison, WI: University of Wisconsin Press, 1983.

W. Schnotz and R. W. Kulhavy, Comprehension of Graphics, Amsterdam: North Holland, 1994.

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