Remaking An Influential Cross Reference Visualization

When I first began exploring the subject of data visualization, I had no idea how much one piece of data-driven artwork could inspire me. I had collected a lot of bible-related data by then and was looking for ways to represent it visually. Then, I discovered a wonderfully complex, colorful piece of art with a simple message about the interconnectedness of scripture. It struck me deeply and has led to more ideas, some of which you’ve already seen on this blog, and many others which are yet to be created.

Chris Harrison, in collaboration with Christoph Römhild, developed this visualization to show more than 63,000 cross references. The bars along the bottom indicate the length of each chapter. Colors indicate the distance between chapters. Here’s how he describes it:

We set our sights on […] something more beautiful than functional. At the same time, we wanted something that honored and revealed the complexity of the data at every level –- as one leans in, smaller details should become visible.

Initially I stared at it for days. I glanced at it regularly for a long time after that as it sat on my desktop background. Then, I began thinking of how I could do something similar with my unique perspective and skills.

Variations Large and Small

It seems others have had the same thought. I have seen visualizations which follow similar patterns—some a nearly literal copy, others entirely different in form but similar in content and complexity.

The first two images above are from which regularly shares popular data visualizations. The third is a project called Similar Diversity connecting words from the holy books of five major religions. The final image conveys alleged contradictions from Project Reason (note: there is also an interactive version on an unaffiliated site)

An Interactive Remake

Below is my remake using Tableau. Click the bars at the bottom to highlight a book.

This visualization is not compatible with your screen size.

Click here to view it full-size.

I felt Mr. Harrison’s original design needed no improvement other than to add interactivity where practical. Like the visualizations, I am using R.A. Torrey’s Treasury of Scripture Knowledge to analyze over 340,000 connections.

Handling that much data interactively has its challenges. Tableau can easily query it but cannot efficiently display it all at once. To address that issue, verse-by-verse connections are rolled up the chapter level, then filtered down to only show the most relevant connections. One other difference between this and Mr. Harrison’s original is the color choice. I colored each line by book rather than textual distance in order to enhance contrast when highlighting.

How Is This Useful?

Clicking through several books has led me to some very helpful insights about how this cross reference data set is put together and the impact it may have on applications which use it. Anyone who has seriously studied the book of Revelation knows it is filled end-to-end with symbols referencing the Old Testament. However, there aren’t many links to those books in this data.The Gospels, though they describe the fulfillments of many messianic prophecies, have few links to prophetic books. Why is that?

Browsing around some other books and going back to the original index by Torrey gives us a clue. Genesis and Psalms cover the span of the Bible because they cover a full range of topics. By contrast, revelation is very specifically apocalyptic and only shows strong connections to end-times passages. And, there’s our answer: R.A. Torrey based his indexing system primarily on the topic of the passages, not on quotations from or specific references to each other. This also explains how there can be hundreds of thousands of links, averaging close to 11 for every verse in the Bible.

Here, visualizing the data has done its job. We may expect to see links between passages based on the kinds of links normally found in modern study Bibles. But, data visualization isn’t always about showing us exactly what we expect. It’s about showing what’s there and sometimes highlighting the unexpected. With this in hand we can refine the data in much the same way God refines us (see 1 John 1) – by shining light on the situation and rooting out what shouldn’t be there.

  • mcrow99
    Posted at 14:40h, 21 April

    Robert, I like the Tableau implementation of this visualization, and I appreciate that you give credit to the original designer here on your blog. I would suggest adding a credit to the Tableau dashboard and your Tableau Public gallery, as well. Given that those are standing on their own, I think it’s helpful to have the credit in each of those spaces. Otherwise, to people who only see your visualization through those avenues, it might look like you are trying to take credit for Mr. Harrison’s design.

    • Robert
      Posted at 20:08h, 21 April

      Good point. I have updated it based on your suggestion.

  • Liang
    Posted at 03:08h, 18 May

    Hi, Robert, I like the Tableau implementation very much. I am trying to figure out how to get the beautiful viz done with Tableau. I run into a few problems. Could you please help me tell me how you have achieved the following effect?
    First, in your implementation, when a chapter is selected on the dashboard, all the chapters in the same book are highlighted and the book instead of the selected chapter is used as a filter for the arcs, how did you achieve this effect? Is there some aggregation?
    Second, how to keep the rest of the arcs in the view and dimmed while the arcs corresponding to the book including the selected chapter are highlighted? Usually, when a filter is used only those match the filter will be there in the view and the rest will disappear. How do you keep all of them and highlight the ones match the filter?

    Your help will be appreciated very much.

    • Robert
      Posted at 09:39h, 18 May

      The key here is that I’m using a highlight action, not a filter action. The highlight action can be assigned to all fields or just one, so in this case I chose to highlight on the book name instead of the book+chapter. you cna learn more about how that works in Tableau here:

  • Cindy
    Posted at 13:15h, 04 August

    Hi Robert, It’s great visualization. Could you explain how path range bin and arc works? Also why we have to put filter for SUM(number of records) and radius(copy)?
    Also I tried to build the arcs sheet myself. I did everything the same but I the worksheet shows that I have >1M nulls. I have no clue what’s the problem.

    • Robert
      Posted at 14:57h, 04 August

      The path range bin is a way to add points in between the ends of each line for use in calculating the arcs. You can learn more about how to do this by studying this blog post:

      The filters for number of records and radius are just ways to reduce the data points to the most meaningful ones so the visualization can load in a reasonable amount of time on the web.

  • Sean Campbell ن‎
    Posted at 09:59h, 12 February

    I would like to see some one build an inter active schematic based on this idea. If the the Linux software kernel has an interactive map over at then this same thing should also be imminently possible.