Robert Rouse combines Bible geo data with Tableau to produce an interactive map that uses size to emphasize important places and allows you to filter the data by book:
Bible Places 
He ‘s also written a blog post that goes into detail about the map. The blog is about technology and the Bible, so take a look at his other posts if those topics interest you.
This diagram plots the similarity of pericopes (sections) in the New Testament based on their linguistic similarity in Greek:
Blue = Gospels, Purple = Acts, Green = Paul’s Epistles, Red = General Epistles, Gray = Revelation
If you don’t have Silverlight installed (or are reading this post via RSS–I suggest you click through to the original post), here’s a thumbnail:
Download the full-size PDF (300KB) or PNG (22 MB, 12,000 pixels wide).
Do we actually learn anything from this kind of diagram? The most interesting part to me is how the gospels on the right flow primarily through the Gospel of John to the epistles on the left. I wonder why that is.
I calculated the cosine similarity between the full text of the pericopes using the Greek lemmas (after removing about forty stopwords). The pericope titles come from the ESV. I produced the diagram with Cytoscape. The widget at the top of the post comes from zoom.it, Microsoft’s Deep-Zoom-as-a-Service.
Bill Mounce’s excellent free New Testament Greek dictionary served as the source of the lemmas.
The New York Times discusses the latest iPhone trend: apps that provide talking points for the existence of God, pro and con.
In a dozen new phone applications, whether faith-based or faith-bashing, the prospective debater is given a primer on the basic rules of engagement — how to parry the circular argument, the false dichotomy, the ad hominem attack, the straw man — and then coached on all the likely flashpoints of contention….
Users can scroll from topic to topic to prepare themselves or, in the heat of a dispute, search for the point at hand — and the perfect retort.
I expect that, eventually, we’ll just let our phones argue the basic questions of existence among themselves, and then they’ll let us know what they’ve decided.
Let’s say you have text in front of you written in a language you don’t read–worse, no one has understood the language for thousands of years. How can you begin to understand it? MIT researchers have created a way to for a computer to decipher Ugaritic in a few hours without knowing anything about the language besides its general similarity to Hebrew.
One of the researchers says:
The decipherment of Ugaritic [in the mid-twentieth century] took years and relied on some happy coincidences — such as the discovery of an axe that had the word “axe” written on it in Ugaritic. “The output of our system would have made the process orders of magnitude shorter.”
I love that someone felt the need to write “axe” on an axe. Maybe it was the original brand name.
I’m most curious whether the program can help crack the Minoan language on Linear A.
Incidentally, the article What’s Ugaritic Got to Do with Anything? explains why Ugaritic is important to understanding the Hebrew of the Old Testament.
Via.
If you were to name a church, how would you go about it? Let’s see how people have named churches in the U.S. by looking at a random sample of 300,000 church names gathered using the Yahoo! Local Search API.
You might start with the word “church” in your name. About 2/3 of churches in the dataset have the word “church.” (The number of churches with the word “church” in reality is higher, as the dataset often truncates names.) Other popular nouns: center, fellowship, chapel, assembly, ministries (or ministry), temple, tabernacle, and iglesia.
Here’s a wordle of the most common words that appear in church names (excluding the word “church”):
Denominations overpower the raw list. Here’s a wordle of the same data without denomination names:
Here are the most common church names in the U.S. Also download the top 1,000 church names in the U.S. (29 KB Excel document), covering 95,000 churches, if you want more information.
| Church Name | Churches |
|---|---|
| first baptist church | 5,115 |
| church of christ | 2,854 |
| first united methodist church | 2,149 |
| first presbyterian church | 1,960 |
| united methodist church | 1,488 |
| seventh-day adventist church | 1,478 |
| first christian church | 1,309 |
| calvary baptist church | 1,197 |
| church of the nazarene | 915 |
| trinity lutheran church | 892 |
| salvation army | 867 |
| first assembly of god | 744 |
| church of god | 677 |
| faith baptist church | 663 |
| st john’s lutheran church | 601 |
| grace baptist church | 600 |
| first congregational church | 575 |
| assembly of god church | 565 |
| new hope baptist church | 540 |
| zion lutheran church | 523 |
The word “St.” (Saint) is common in more traditional churches, such as Catholic, Episcopalian, and Lutheran. Here are the most popular saint names used for churches:
| Saint | Churches |
|---|---|
| John | 3,713 |
| Paul | 3,210 |
| Mary | 1,832 |
| Peter | 1,362 |
| James | 1,270 |
| Joseph | 1,153 |
| Mark | 1,062 |
| Luke | 1,053 |
| Andrew | 789 |
| Matthew | 724 |
| Stephen | 582 |
| Michael | 532 |
| Francis | 530 |
| Thomas | 511 |
| Patrick | 431 |
| Anthony | 381 |
| George | 329 |
| Ann(e) | 282 |
| Nicholas | 253 |
| Elizabeth | 220 |
Mountains and hills are common names for churches. I suspect that “Spring Hill” and the assorted “Pleasant”s come from the city names where the churches stand.
| Mountain | Churches |
|---|---|
| mt zion | 1,587 |
| mt olive(t) | 1,122 |
| mt calvary | 619 |
| mt carmel | 528 |
| mt pleasant | 475 |
| pleasant hill | 394 |
| mt moriah | 329 |
| mt sinai | 316 |
| zion hill | 200 |
| mt pisgah | 191 |
| mt nebo | 139 |
| mt tabor | 136 |
| mt pilgrim | 112 |
| mt hope | 108 |
| mt gilead | 95 |
| mt bethel | 90 |
| spring hill | 90 |
| mt hermon | 85 |
| mt lebanon | 74 |
| mars hill | 59 |
Here are the most-common two-word phrases (including denomination names) used in some of the more popular denominations. “First” appears in 12% of Baptist church names, 10% of Methodist church names, only 3% of Lutheran church names, and fully 21% of Presbyterian church names.
| Baptist | Methodist | Lutheran | Presbyterian |
|---|---|---|---|
| first baptist | united methodist | trinity lutheran | first presbyterian |
| missionary baptist | first united | st john’s | united presbyterian |
| freewill baptist | chapel united | st paul’s | cumberland presbyterian |
| grove baptist | free methodist | evangelical lutheran | korean presbyterian |
| calvary baptist | trinity united | zion lutheran | westminster presbyterian |
| hill baptist | memorial united | grace lutheran | covenant presbyterian |
| zion baptist | st paul | our savior’s | community presbyterian |
| hope baptist | grace united | faith lutheran | memorial presbyterian |
| creek baptist | grove united | immanuel lutheran | trinity presbyterian |
| faith baptist | wesley united | christ lutheran | orthodox presbyterian |
| mt zion | zion united | peace lutheran | reformed presbyterian |
| bethel baptist | hill united | redeemer lutheran | grace presbyterian |
| new hope | christ united | first lutheran | hill presbyterian |
| grace baptist | bethel united | good shepherd | faith presbyterian |
| bible baptist | faith united | hope lutheran | hope presbyterian |
| chapel baptist | hope united | calvary lutheran | christ presbyterian |
| community baptist | street united | bethlehem lutheran | central presbyterian |
| mt olive | asbury united | st peter’s | valley presbyterian |
| memorial baptist | park united | bethany lutheran | creek presbyterian |
| southern baptist | salem united | messiah lutheran | park presbyterian |
Ray Fowler analyzes Amazon’s Kindle data to find the most-highlighted Bible passages on Kindle.
Ten of the fourteen verses overlap the thirty most popular verses on Twitter, a higher percentage than I expected.
Here’s a visualization of 340,000 Bible cross references:
Larger version (2,000 x 1,600 pixels).
Does anything strike you as intriguing? A few trends jump out at me:
You can also download the full-size image (10,000 x 8,000 pixels, 75 MB PNG). It’s a very large image that could crash your browser. If you want it, I strongly recommend that you save it to your computer rather than trying to open it in your browser.
This visualization uses data from the Bible Cross References project. I used PHP’s GD library to create the graphic.
Inspired by Chris Harrison and Christian Swinehart’s wonderful Choose Your Own Adventure work.
Browse 340,000 Bible cross references. Make the list better by voting on relevant or irrelevant verses.
For example, try Philippians 4:13 (“I can do all things through Christ who strengthens me”) or Isaiah 40:31 (“They shall mount up on wings like eagles”).
The interface is about as bare-bones as it gets: there’s a list of cross references for a single Bible verse, sorted by relevance (i.e., votes). You can browse to related verses, vote on whether each cross reference is relevant, and see (on external sites) the verses in different translations. It also prints nicely. There’s no way to suggest new cross references, though I may add that feature if there’s demand.
The data comes primarily from The Treasury of Scripture Knowledge (TSK) but blends other data, including the Topical Bible and Twitter Bible Search. All the copies of TSK on the web seem to descend from one source; I did some basic cleaning of the data and extracted the references. Then I blended the other data to weight some cross references more highly than others—that’s where the initial vote counts come from. (Incidentally, I only count around 380,000 cross references in TSK, lower than the usual count of 500,000 cross references you find when people talk about TSK. The lower number of cross references on this site–340,000–comes mostly from removing duplicates and combining adjacent verses.)
The 340,000 cross references in this data are a substantial number–most cross reference systems in print Bibles contain 50,000-100,000 cross references. While this list is more comprehensive, the tradeoff is that some of the cross references are less relevant than you find in print Bibles. As people use this site, however, the most-relevant verses should rise to the top.
The main limitation to the data is that the cross references always point from a single verse rather than from a range of verses: in other words, from Matthew 5:3 instead of from Matthew 5:3-11. Broader cross references—references that apply to a complete passage—are therefore missing from the data, limiting its usefulness somewhat.
The lack of an open, high-quality source of Bible cross references on the web has always bewildered me. This project is an attempt to remedy that deficiency. Feel free to download the raw cross-reference data (2 MB .zip, updated regularly with the latest vote counts) and use it in your projects.
Update April 12, 2010: Fred Sanders at Scriptorium Daily has a great introduction to the Treasury of Scripture Knowledge if you want more background on this work.
Here’s a presentation I just gave at the BibleTech 2010 conference about how people tweet the Bible:
Also: PowerPoint, PDF.
I distributed the following handout at the presentation, showing the popularity of Bible chapters and verses cited on Twitter. It displays a lot of data: darker chapters are more popular, the number in the middle of each box is the most popular verse in the chapter, and sparklines in each box show the distribution of the popularity in each chapter. (Genesis 1:1 is by far the most popular verse in Genesis 1, while Genesis 3:15 is only a little more popular than other verses in the chapter.)
Let’s look a little more at some of the data on what Twitterers are giving up for Lent.
As I only track in English what people are giving up, there are concentrations in English-speaking countries.
Size indicates the relative number of Twitterers in each country giving up something for Lent.
These visualizations show the differences (or lack thereof) in what people are giving up among U.S. states.
Size indicates the relative number of Twitterers in each state giving up something for Lent. Sorry, Alaska and Hawaii.
The composition of each state’s categories of tweets shows mostly minor variations among states. Some states (like Wyoming on the far right) have small numbers of tweets. I would have liked to use opacity or width to indicate this disparity but couldn’t figure out how to do it.
This treemap shows how the data changed between 2009 and 2010. The size of the box shows the number of people giving up each category and thing, while color indicates the percentage change from last year: dark blue indicates the steepest drop; dark orange indicates the steepest rise. The second chart shows the same data more conventionally expressed.
I created these charts mostly to explore how the new data-analysis software Tableau Public works. One of its claims to fame is that you can publish interactive visualizations to the web, a feature I didn’t take advantage of here. Tableau doesn’t do treemaps, so I used Many Eyes to create the treemap; the closest Tableau equivalent appears below the treemap.
Unless otherwise indicated, all content is licensed under a Creative Commons Attribution License. All Scripture quotations, unless otherwise indicated, are taken from The Holy Bible, English Standard Version. Copyright ©2001 by Crossway Bibles, a publishing ministry of Good News Publishers. Contact me: openbibleinfo (at) gmail.com.
