In this video, you’ll learn about the differences between each one, and see some quick examples, too.

What’s Inside

0:00 Welcome

0:28 Ann’s Diagram re: Your Branding Resources

0:47 Variations by Company/Organization

1:27 Style Guides: What’s Typically Inside

2:07 Dataviz Style Guides: What’s Typically Inside

2:34 Templates for Slidedecks, Reports, and More

2:59 Branding Resources – Designed for YOU

3:16 What Do You Want to Learn More About?

3:31 Don’t Forget to Like, Subscribe, and Share

Transcript

Style guides, dataviz style guides, templates. That is a lot of jargon. In this video, I’m going to break it down for you. I’m going to tell you what’s what, what should ideally go inside each of these. Hi, I’m Ann Emery. Welcome back to Dataviz On The Go, the series where I make jet speed tutorials for you as I’m racing around between workshops.

And speaking of workshops, I gave a half day workshop just last week about dataviz style guides. And one of the things we covered was this diagram, which you know me, it’s made in good old Excel of all places. And I made it to show how all of these things fit together. Okay. So here is the universe, right,

of all of your branding resources that you would ideally have at your workplace. In practice, not every group has all of these. Some of them have really basic guides and templates. Some of them have really elite, really advanced guides and templates. I have seen a little bit of everything. I see about 50 to a [00:01:00] hundred style guides and dataviz style guides every year as part of my private workshop process.

So during the prep, I’ll say, “Send me your this, and send me your that, and send me your style guide and or dataviz style guide in whatever format it’s in. If it’s, you know, beginner, if it’s advanced, just show me what you’ve got and we’ll take it to the next level.” So here’s what I typically see, right.

It’s like a little bit of a few of these things. So out of all of your branding resources, you would ideally have your organization’s style guide. Now, what typically goes in inside there, it’s going to be logo guidance, your colors, your fonts. You might have some photos. You might have some writing tips.

Like, do you capitalize the F in federal government or not? Do you spell out numbers at the beginning of a sentence or not? It might have writing tips like that. It’s going to live in usually a PDF. It might be short. It might be long, depending on how big your organization is, or it might live [00:02:00] online. I see that a lot with universities.

They’ll have a few pages on their website with all of their branding resources, very public facing. Within there, ideally, if you’re a data organization, if you make graphs for any part of your work, you would ideally have a dataviz style guide with sample charts and maps and tables. And, um, And, fingers crossed, in a perfect world, you’d have data specific tips.

“We use color in this way to make sure it’s accessible. We pay attention to color contrast this way. Here’s what we do for binary, sequential, diverging variables,” and so on. Templates are a little bit different. Okay. If you make a lot of presentations, you’re going to need a slide deck template. If you make a lot of reports, you’re going to need a report template.

You’re going to need all the templates. They might live inside Excel, PowerPoint, Canva, Power BI, Tableau. They’re going to live inside that software program. It’s not just a PDF with screenshots. It should be an actual editable template that staff can type in because, after all, all of these [00:03:00] branding resources are designed for you to save you time and help you look professional so that staff aren’t just like creating everything from scratch all the time.

That would be really, uh, really messy. That would be really time consuming, right? Who wants to waste time like that? Alright, you tell me, comment below the video, what would you like to learn more about? Do you want to see sample style guides, sample dataviz style guides? I’ve got templates and rubrics for all of these things to help you take your resources to the next level.

Happy to share, happy to help.

Don’t forget to subscribe and share!

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So you decided your organization needs a style guide to save lots your team lots of time when creating charts, enhance brand cohesion, and improve trust with your stakeholders.

In my previous post I described how to identify if your team needs a Data Visualization Style Guide, how to secure buy-in from leadership and your coworkers, and some great resources to review before you get started.

This post will outline the key components of your Data Visualization Style Guide and how to ask for feedback that will make this new resource actionable.

Every guide might be a little different depending on your field and your data.

Here are the key components of my Data Visualization Style Guide.

Note: The instructions in green type in the pictures below are for style guide users. These instructions help the user better understand the components of each chart type.

Chart Structure

This is a general overview of how charts should look for your team. This includes some of the basics of each chart, such as formatting for figure numbers, chart titles, chart subtitles, and axes.

Chart Typography

I used Amy Cesal’s Sunlight Foundation Data Visualization Style Guide and Jon Schwabish’s Urban Institute Style Guide as my starting points for choosing font size for different components of our charts. I was redesigning our reports at the same time I was making my style guide, so through trial and error my team determined what font sizes worked for different kinds of materials, e.g., reports vs. PowerPoints.

Color Palette

If you have agency colors, you should use those as a starting point.

The picture of the color palette below shows the different colors assigned to my public health programs for HIV, STDs and HCV. Each program is encouraged to start with their main color and then use the other colors in the palette as needed.

Your Data Visualization Style Guide should start with the same fonts and colors from your organization’s existing branding guidelines, if they exist.

If you need to create your own color palette or add colors to your agency’s color palette, here are some great tools:

• For inspiration on color combinations used by other businesses: https://brandcolors.net/
• To test out your color combinations, adjust your palette, and identify tints (lighter versions of your main color) and shades (darker versions of your main color): https://coolors.co/.

Identifying Tints and Shades

Here is how I identified the tints and shades for each color in my color palette.

Step 1: Once you have your color palette identified, select the symbol inside the yellow circle below:

Step 2: Then use a system to select the additional tints and shades for your style guide. By system, I mean I selected every other color (see the arrows and instructions in the picture below) for my tints and shades. I repeat steps one and two with each color in my color palette.

Check for Sufficient Foreground/Background Color Contrast

To ensure your colors are contrast compliant based on the Americans with Disabilities Act, here is an accessibility checker: https://webaim.org/resources/contrastchecker/.

Including Lots of Color Codes

Ideally, a Data Visualization Style Guide should be user friendly with several different kinds of chart-making software.

By including all the different color codes, it minimizes the number of steps a person has to take to convert a color into the code they need (e.g. from RBG to HEX).

Also, maybe your whole team just uses RBG and CMYK color codes now, but by including all three, you are increasing the sustainability of this style guide if your team adds new software that uses a different color code in the future.

Recommended Color Combinations

This was really important to my team members. Some people don’t want to spend lots of time making decisions about colors. Providing color combination recommendations in the style guide saves my coworkers lots of time, but still allows room for creativity and autonomy.

Fewer decisions to make = timer saver.

Map Color Palette

We determined through trial and error that the overall color palette in the style guide could not be applied as is to maps because we needed colors with higher contrast between one another.

The viewer has to be able to tell the difference between the colors when they are in close proximity to one another.

I adjusted the colors slightly for my map color palette to ensure they would be distinguishable from one another when the colors are close together.

Map labeling is tricky. We ran into many different opinions about how maps should be labeled. It’s easy to over label a map, especially when you are dealing with small spaces, such as counties in a state. Also sometimes there are limitations with the mapping software when it comes to colors and labels. The maps above were made in GIS.

It’s important to ask yourself if the audience is really going to look for the label on each county, or do they just need to get a sense of the color scale.

Ask the question, what do I want my audience to understand from this map? How will the map be presented? Presentation? Report? Online? Interactive?

Example Charts

This is one of the most important sections!

This section can feel like a big undertaking. Start by looking at your organization’s existing data documents. Identify the chart types that your colleagues use regularly and then consider adding a few other chart types to increase chart variation options for your staff. For example, include a lollipop chart in addition to a bar chart, and a waffle chart in addition to a pie chart. This section can include as many or as few charts as you see fit for your organization.

This is another example where the trial and error process is so important. Because we created this style guide while redesigning large data reports, we were able to test different sample charts for the style guide. We adjusted line and dot thickness, label placement, chart sizes, and font size to figure out what worked best. Then we used the style guide to standardize our decisions for future data deliverables. Our decision process was a balance of data visualization best practices, the story we were telling with our data, and my colleagues’ input.

Other Data Visualization Resources

If you think your team is interested in other data visualization information, then you could include additional resources at the end of the document.

How to Ask for Feedback about Your Data Visualization Style Guide

**This is really important.**

About halfway through the development process of my Data Visualization Style Guide, I sent the guide around for feedback from coworkers I knew were going to use it. I asked for specific feedback on what is working and not working. Am I on the right track? Is this resource useful and clear?

Then I incorporated their feedback and created an almost final draft of the guide.

When I had an almost final draft I asked for even more feedback! What doesn’t make sense? What would make this resource more useful to you? What should be included to make this useful to a future new employee of our team?

In this final feedback stage, it was important to share our evolving style guide with team members who hadn’t seen earlier drafts and maybe were only going to make charts occasionally. These folks could provide feedback on what made sense and where guidance was missing. Ideally, a new employee could pick up our new Data Visualization Style Guide and use it to make charts that align with the program’s brand without needing additional guidance.

Reminder: Don’t ask for feedback unless you plan to use a good percentage of it. It wastes people’s time and sends a message that you don’t value their opinions. Not using their feedback at all could reduce the number of people who use your guide because your colleagues don’t feel invested in it.

How We’ve Used Our Data Visualization Style Guide

Here are some examples of data materials created using our Data Visualization Style Guide:

1. Wisconsin HIV Annual Data Report
2. Wisconsin HIV Data Two-Page Summary
3. Wisconsin Hepatitis C Annual Data Report
4. Wisconsin Hepatitis C Data Two-Page Summary

Key Takeaways for Creating Data Visualization Style Guides

Here are three lessons learned.

• Before you create a Data Visualization Style Guide it is crucial to secure buy-in from leadership and the majority of your colleagues who will be using the style guide. This buy-in will help ensure this document is relevant and will be used for future data-intensive materials.

• Before you start creating this resource, ask future Data Visualization Style Guide users: “What should be included in our style guide that would make this resource useful to you and increase the chances that you will use this tool to guide chart creation?” This is key because it ensures that you include what is important to your data team.

• Create a style guide as you are redesigning data documents. Don’t try to create a style guide and then apply it to lots of documents. Working on the style guide and data materials side by side will ensure you create a resource guide that actually works. This will set you and your new tool up for success.

The Benefits of Having a Data Visualization Style Guide

Designing a Data Visualization Style Guide may sound like a lot of work, but the benefits for your organization are enormous.

You will:

• Save your colleagues valuable time when designing data deliverables
• Enhance your organization’s brand, communications, and professionalism
• Increase the accessibility and communication of your data to key stakeholders because of your consistent use of data visualization best practices.

Bonus: Purchase Our Guide

The ideas and examples shared here and my previous post should give you all the tools you need to get started.

Or, save time and download our guide.

Is this you?

• Different members of your team are working with data and creating charts.
• All of your charts look a little different.
• You would like to redesign or improve your upcoming data reports, presentations, and dashboards to better align with data visualization best practices and your agency’s brand.
• You would like to build trust with your stakeholders and tell clearer stories using your data.

A Data Visualization Style Guide is a great tool to enhance brand cohesion and save you and your co-workers lots of time in the long run. This resource will reduce the number of decisions your team members have to make about font, font size, line thickness, color, and chart size each time you make a chart. Maybe creating a Data Visualization Style Guide sounds really exciting to you (like me!) or maybe you would prefer to put it at the bottom of your to do list right after scanning and filing all your paper documents (nice in thought, but really never going to happen). I am here to tell you, if you follow these steps and create a Data Visualization Style Guide, the payoff will be incredible for both you and your team.

Benefits of Creating a Data Visualization Style Guide

1. Time Saver: You won’t have to spend 15 minutes trying to decide what colors to use in your latest chart, what font size your title should be, or the line thickness in your line chart. This style guide will already have clear recommendations on all the data visualization steps that eat up your time.
2. Get everyone using data visualization best practices: If you are reading this blog, maybe you and some of your team members are excited about how thoughtful data visualization can improve your communication skills. However, a style guide can help get the rest of your colleagues on board to create effective charts that are accessible to a variety of audiences.
3. Tell great stories: Incorporating data visualization best practices using a cohesive look for all your charts will improve your professionalism and help communicate your message to all your stakeholders more effectively.

Getting Started with a Data Visualization Style Guide

Here are the first steps to create a user-friendly Data Visualization Style Guide:

Identify a need for a Data Visualization Style Guide

My public health team had to redesign all our major data reports and create new data one-pagers for a variety of audiences, including the general public, nurses, doctors, and other public health professionals. Several team members analyzed the data and created charts. Our team wanted to make sure all the reports looked cohesive, while also using our limited time efficiently. I proposed creating a Data Visualization Style Guide to better align all of our upcoming reports. This avoids one person having to make all the charts or edit all the charts so they look cohesive.

Secure Team Buy-In

Before you create a Data Visualization Style Guide, it is crucial that you secure buy-in from majority of your colleagues who will be using the guide. Make sure your leadership team is also on board. Getting buy-in before you start will help ensure this document is relevant to your coworkers and will be used to create future data reports.

For example, to get buy-in, I coordinated multiple meetings with several data experts and project teams would be creating charts for our annual reports and future data presentations and dashboards. It only makes sense to create this resource if your team is generally on board and can see the benefit of developing this new tool.

In these meetings, I shared some of the existing charts from various reports to illustrate the current lack of cohesion among all our charts.

I also showed some examples of Data Visualization Style Guides from other organizations, and explained how this kind of resource might benefit my team.

Then I asked our future Data Visualization Style Guide users: “What should be included in our Data Visualization Style Guide that would make this resource useful to you and increase the chances that you will use this tool to guide chart creation in the future?” This question is key because it ensures that you include what is important to your team of data users in this document.

Timeline

It took seven months to go from project proposal to completed resource guide because I created this document while also redesigning several data reports.

Creating this guide was a trial and error process. This meant that when I sent out the completed style guide, it had already been used to create six different published materials, which proved that it made sense and was applicable to my colleagues and their work.

A key takeaway is to create a Data Visualization Style Guide as you are editing data documents. Don’t try to create a style guide and then apply it to lots of documents. Working on a new guide and data materials side by side will ensure you create a new tool that actually works and not one you think will work with your data and the materials your team creates.

Software Used to Create a Data Visualization Style Guide

I created the charts for my style guide in Microsoft Excel and did the layout of this document in Microsoft Publisher. However, this style guide could be created in whatever Microsoft program you feel most comfortable working in, whether that is Word, PowerPoint, Excel, or Publisher.

Researching Existing Data Visualization Style Guides

Once it was clear my team was on board with using a Data Visualization Style Guide, I went to work researching the best ways to create this new resource. This research phase was extremely helpful and outlined the process for creating my guide. Here are my favorite resources to check out before you start:

1. Amy Cesal’s presentation on why you need a style guide. Her presentation has some great tips that helped me get started, including the advice to update documents while creating my guide.
2. Policy Viz’s list of Data Visualization Style Guides. Take a look at how other agencies approached style guides and see what components you want to include in yours.

Coming Soon

In my next post, I’ll outline the key components of every Data Visualization Style Guide and show you how to ask for feedback, so your new resource is immediately applicable for you and your team.

I do a lot of evaluation work as a consultant, but it’s usually more evaluation training, preparation, and capacity building than it is evaluation report writing.  

Once every few years, I get a contract for which I have to produce a report. And I love to write, so they tend to get long. Of course, I have to put in every last detail, as a detail person. Don’t I?  

And along comes Ann who says it can be done all differently.  

What??? Ok. Open your mind, girl, and see what you can learn. Turns out you can teach this 53-year-old consultant new tricks, Ann!  

I will show you how much better I am at presenting my results after taking the course, and I’m not even all the way through it yet.  

There is so much left to learn still in Great Graphs, and I’m signed up for the Ann’s Excel course so I need to get started on that too.   

One of my favourite evaluation instructors is Kylie Hutchinson, who wrote a great book about evaluation failures. In the great tradition of showing my past failures and also my ability to learn, here is some evidence of my progress.  

I have organized the changes into three main areas: report style and colour schemes, graphs and qualitative data and I will show my work from three different evaluation reports I wrote (2012, 2018 and 2019).  

Change #1: Report Style and Colour Schemes 

Here’s what my reports’ styles and colour schemes looked like in my reports from 2012, 2018, and 2019. 

2012 

This image below is from an evaluation report I did in 2012 evaluating a domestic violence treatment program on two First Nation reserves.  

I thought I was doing well having a fancy title page (meaning it had some coloured lines on it in a fancy box) and header/footer.  

The whole thing was black and white except for the headings that were in green font.  

I used a 100point font and single line spacing. It was very dense and wordy. So many words.  

There was not a graphic or visual in the entire 39-page report.  

Report style and colour scheme? What are you talking about?  

2018  

I started the Great Graphs course in the fall of 2018, so I was a few lessons in when I had to write my first evaluation report.  

I had a sense from Great Graphs of colour scheme, using the agency’s colours, and making graphs look better.  

But we hadn’t yet reached the detail in how to actually DO these gorgeous things that Ann was showing us, so this report is better than I used to produce but it was still sort of half-baked in terms of data visualization.  

It was an evaluation of a national conference on drug use and drug policy; there was no agency or organization behind it except a planning committee, so there was no agency colour scheme to emulate.  

The conference colour was the hot pink you see in the graphs below. I tried to use the hot pink as the main report colour at first, but it looked like bubble gum exploded all over the page, so I switched the main colour to blue and used the pink in the graphs.  

You can see from the image below that I got a little better with the report colour scheme, using more colour than I did in the 2012 report.  

Honestly, I revamped the conference report over and over, changing the shade of blues and pinks repeatedly I wanted to stick with their original pink but finding a lighter pink that wasn’t hideous was difficult. I couldn’t make up my mind and what worked in a simple graph got uglier when I added more elements to the graph. Or I would show it to someone and their feedback made me go change it all again. This is definitely where a style guide for the project would have come in very handy! 

2019 

But then I had to produce another evaluation report this summer, after having completed much more of the Great Graphs course.  

This is an evaluation of a mentorship program for First Nations people on reserve who are involved in the criminal justice system and who have Fetal Alcohol Spectrum Disorder.  

For this report, I made a Style Guide that included the five RBG colour codes from the agency logo, text hierarchy, chapter divisions by colour, icons for each study population, rules for tables, etc.  

The Style Guide took me a long time to make because I had to learn so much, but then it saved so much time as I was actually writing the report.  

I added the Noun Project to my software and bought a subscription so I could access the icons that I wanted to use.  

I used the eyedropper tool to obtain the RBG codes from the logo, and I learned how to change the colour of the icons to the right RBG codes.   

I went searching for a font and downloaded it to my software.  

I made up a new colour and design template for this client in Word.   

I also searched for free images for the report and each chapter title page, and followed Ann’s instructions on how to make it fit the page, how to put the text box over it in white font, and how to overlay a colour transparency in the same colour as the chapter.  

And now that I have made one Style Guide, they will be simpler to make going forward, I think.  

Here are a few screenshots from the Style Guide.  

Now, for the glory!  

Here are a few sample pages from the report I just submitted using this Style Guide, complete with colour schemes from the agency who commissioned the evaluation.  

Each of these screenshots below are from a different chapter – one from a blue, one from a green and one from a red chapter.  

I hope you will agree that I have come a fair distance in report colour schemes and formatting. 😊 

Change #2: The Graphs 

Here’s what my graphs looked like in reports from 2012, 2018, and 2019. 

2012 

Again, in that 2012 report, not a single graph. Only tables. Table after table.  

2018 

In the 2018 conference report, I got better!  

I put in tables with as much as I had learned from Ann at the time.  

I knew what I wanted to do but I didn’t know how to do some of it and, apparently, I forgot that I could actually google some of the things I couldn’t figure out.  

First, you can see that I wasn’t quite ready to get rid of the whole “Figure 9….” title thing so that’s still there.  

Second, I was pretty happy with how I presented three pieces of outcome data in one table with one heading that summarized them.  

But, one thing I couldn’t figure out was how to change the heading to a text box like Ann uses in her samples. I had played around with making it dark blue fill with white font but in the end, I decided I didn’t like it so I left it like this.  

Now I think the right justify is just weird. Why did I do that?  

Third, I could not for the life of me figure out how to change the response text on the left from centred to right justified. I know how to do that now because I remembered recently that google is a miracle of the modern age and I would probably find the solution there.  

Fourth, I wasn’t quite ready to give up the outside border of the graph or maybe I couldn’t figure out how to do that; I don’t remember anymore.  

Finally, I didn’t know how to get the data inside the line, make it bold, etc. I needed to learn so much more about Excel.  

But, it’s still better than all those tables in the 2012 report.  

Here is another table.  

It’s pretty busy.  

At the time I thought it was interesting that business representatives felt most strongly that they learned new skills. It’s still kind of interesting.  

Normally I would have probably combined the scores for agree and strongly agree, but that would completely blur that distinction for business representatives.  

Next time I would probably use a stacked bar showing all of the response categories for each audience type.  

2019 

Here are some graphs from the 2019 report.  

I have the heading in a coloured text box with white font, but I still have to improve on the content of the chart titles.  

I got rid of the outside border, got the data inside the end of each data line, figured out how to right justify the response text, and I altered the gap width as well as the scale. What I still need to do is get rid of the scale; why is that still in there?  

What I did in the main body of the report (example 1 below) was present all of the outcomes together in one big table.  

Then, in the Appendix of the report, I presented all of the data tables for each question relating to an outcome (See example 2 below).  

The example 2 table shows the detailed results for the two questions that made up the second outcome (caregivers and relatives report increased knowledge of FASD and how to care for a person with FASD) in the example 1 table.  

Example 1:  

Example 2:  

In the example 2 table, I used two of the main report colours (dark blue and dark brown) for the strongly agree and strongly disagree, used grey for neutral, and lighter shades of the blue and brown for agree and disagree.  

I went back to Ann’s video on how to put the white lines in between the colours. I had originally started using dark blue and red as the two outside colours, but it didn’t work in greyscale, so I had to keep trying it with different colours and seeing how it looked in greyscale on the screen and when printed.  

Unfortunately, the mistake I made was making about 30 tables in the original colour scheme before I realized it didn’t work in greyscale.  

Sadly, I did this twice; I did and re-did all the tables in both the 2018 and 2019 reports.  

Note I hope I remember for next time: make one chart, test the colours, then make the rest of the charts. You can also see that I left in the original axis explanation; I couldn’t figure out how to make it look like Ann’s example below. Something to improve for next time…  

Change #3: Qualitative Data 

Here’s how I presented qualitative data in 2012, 2018, and 2019. 

2012 

The main challenge I had in the 2012 report was that I was brought in at the end of a three-year project to complete an evaluation based on an evaluation framework and data collection plan for the project that had never been implemented.  

There were few program files and no data collection mechanisms in place, so no reliable data.  

The best we could do was interview people on how the project went, based on their recall.  

I ended up presenting some items in paragraph form such as the image below, as well as quotations from interviewees as data.  

Based on what I know now, I would probably take those items separated by a semicolon in the paragraph below and put them into some sort of table that makes the information easier to read.  

2018 

For the 2018 conference report, I had a lot of qualitative data to report, but I was still pretty boring about it.  

I organized it into theme areas, summarised the theme after the subheading then dumped in some quotes illustrating the theme.  

I now know that I could have put them in a table, using colour, with icons symbolizing the theme area.  

2019 

In the 2019 evaluation report, I really stepped up my qualitative data presentation game.  

I organized qualitative results into theme areas and put them into different types of tables organized by theme areas, with icons and colour coding.  

The first example is the first two rows of a longer table.  

Many of the same themes kept emerging from the three study populations in response to different questions, so the icons for themes were used repeatedly throughout the report.  

The first example is from a chapter where the colour scheme was brown.  

In another area, I had asked interviewees a yes/no question with follow up questions for explanation.  

This time, I made a table that included the quantitative yes/no results as well as examples of the qualitative explanations.  

One final example to share.  

I needed to present some quotations/explanations from two different categories of respondents, so I made a table as follows.  

It’s not all that fancy but I think it improves on what I did in 2012 and 2018.  

While it was embarrassing and somewhat amusing to show the series of reports like this, I am actually quite delighted with what I have learned and am happy with this last report.  

I haven’t finished Great Graphs yet but I have learned so much.  

I have gone into my notebook and screenshots from the course over and over as I try to do better work.  

I am grateful to Ann and my clients have commented on the improvement in what I am presenting to them.