15 Sorting Algorithms

Okay, I confess that I found this visualization/auralization of sorting algorithms absolutely mesmerizing, which may or may not reveal something (terribly wrong with or) about me. For those curious, the algorithms are:

> selection sort, insertion sort, quick sort, merge sort, heap sort, radix sort (LSD), radix sort (MSD), std::sort (intro sort), std::stable_sort (adaptive merge sort), shell sort, bubble sort, cocktail shaker sort, gnome sort, bitonic sort and bogo sort (30 seconds of it).

[Link][] for more information.

[Link]: http://panthema.net/2013/sound-of-sorting/

Cartographically-Driven Questions

Lincoln Mullen has developed an interactive map of the United States that allows you to explore the [spread of slavery][] from a little before 1790 to a little after 1860. Based on census figures, I am guessing, the map changes dynamically as counties are added and/or divided. Each county has information for the population of slaves, free African Americans, total free population, and total population, which is rendered either in percentages or in number of persons per square mile.

Working in south Louisiana, I was curious to explore a number of things, that I will perhaps write about one day, but as I looked at the larger map and played with the various views, I noticed something:

EnslavedbyPercentage

I expect to see increased percentages along waterways like the Mississippi, a trend that generally holds true in Louisiana with concentrations of slaves rising near bayous, but I cannot for the life of me immediately explain that crescent of greater enslavement that runs through Mississippi, Alabama, and Georgia. I’m guessing it has to be a geological/geographical feature that I cannot immediately discern.

Check out Mullen’s project. This is good, compelling scholarship, the kind that provokes questions among its users.

[spread of slavery]: http://lincolnmullen.com/projects/slavery/

How We Spent

Bloomberg’s new Data View feature is quite compelling. A recent interactive visualization focused on [changes in consumer spending][bb] over the past 30 years. The most eyebrow-raising thing I noticed while looking over the various graphs was that almost all of them reveal a change in consumer spending about three years before the collapse of the mortgage bubble: some time between late 2005 and early 2006 consumer spending dips significantly and continues to dip until it bottoms out in 2008. I am not enough of an economist to know if this dip helped break the bubble or if it reveals that consumers were, in some way, aware of the bubble and already anticipating the trouble to come.

[bb]: http://www.bloomberg.com/dataview/2013-12-20/how-we-spend.html

Buying Liquor

[Find the Best][] has a [comparison][] of various liquors by price and quality of taste. We’ll levee aside whatever the latter measure is: what I like are the graphs, the dot graphs for each of the categories of liquor (gin, vodka, whiskey, rum, etc.). Price increases along the vertical and taste improves along the horizontal. There is a trend line, and, more importantly, if you hover over a dot you are given its name, its price point, and its evaluation:

[Find the Best]: http://findthebest.com/
[comparison]: http://blog.findthebest.com/lifestyle/why-liquor-prices-mean-nothing/

XKCD’s Now

[XKCD has a live “now” clock][] that displays the time around the globe from the point of view of looking “up from the bottom” of the globe. As always, it’s a great [visualization][].

[XKCD has a live “now” clock]: http://xkcd.com/1335/
[visualization]: http://johnlaudun.org/tags/visualization

Neatline

[John Anderson][] sent me a link to [Neatline][], a [Scholar’s Lab][] suite of plugins for [Omeka][]. (And, if you want one more layer/link: Omeka can run on top of DSpace.) Taken altogether, you have a fairly robust stack for capturing, and preserving archival, a wide variety of information that can then be visualized — I kinda prefer the architectural term *projected* — in a lot of ways.

Here’s the official description:

> What do you get when you cross archives and artifacts with timelines, modern and historical maps, and an appreciation for the interpretive aims of humanities scholarship? Neatline is a geotemporal exhibit-builder that allows you to create beautiful, complex maps and narrative sequences from collections of archives and artifacts, and to connect your maps and narratives with timelines that are more-than-usually sensitive to ambiguity and nuance. In other words, Neatline lets you make hand-crafted, interactive stories as interpretive expressions of an archival or cultural heritage collection. Every Neatline exhibit is your contribution to humanities scholarship, in the visual vernacular.

There’s an interesting collection of images on the site. A number of them are either rich or confusing: it’s hard to tell from an image. That dichotomy does bring up a point: without good design, a rich environment can simply be a confusing one.

I actually wrote about this back in 1989 when thinking about interactive user experiences — yeah, I have been at this for a long, long, *long* time. A couple of quick points to make about all this here:

1. *Design matters.* It matters a lot because the conventions, the generic expectations that help users orient themselves, especially to understand the relationship between content and its representation, are still emergent. *Oh*, but you say, *we don’t want conventions*. We want things to be always new, always surprising. To which I reply: stop. You want conventions. Sometimes you want the form of the content to be as plain as possible so that people only focus on the content — think _Scientific American_ layout in the 90s versus _Wired_ magazine layout. By having conventions, you then have a place to negotiate ranges of surprises with your audience. Without a bare framework of conventions, you have confusion.

2. *Design takes time.* And time means people and that means people are using their time to create projections of data when they might otherwise be creating new data or representing the data in more traditional forms. What it comes down to is that the system of rewards will need to be revised to give people incentive to experiment, pioneer, this landscape. Some universities and academics get this. A lot don’t. (Both administrators and faculty bear responsibility for the lack of conversation on this topic.)

An interesting new study on how academics don’t recognize some activities has been announced by Indiana University: [link to press release](http://newsinfo.iu.edu/news/page/normal/24336.html). The direct link is there because I really haven’t had a chance to read through the release yet, let alone the study. Thoughts and comments are welcome. I’m happy to link to others’ considerations.

[John Anderson]: http://plus.google.com/103113688090803889207
[Neatline]: http://neatline.org/about/
[Scholar’s Lab]: http://scholarslab.org/
[Omeka]: http://omeka.org/

Going (Back) to School

There are so many new avenues of exploration opening up right now, and so many ways to pursue them, that I really do wish I could put my career on hold for a mere few months and just spend some time rolling in all the educational opportunities that are now offered and that could give me the kind of education I have always, always wanted. I can’t, of course, put things on hold, but I can take time here and there to teach myself things like:

* **linear algebra** and **statistics** for better understandings of how to transform complex realities, like texts, into numerical descriptions in order either to verify already intuited patterns or to discern new kinds of unanticipated patterns,
* **Python** in particular, and perhaps **R** too, so that I could both do things with the texts themselves or with the numbers into which they have been transformed, and
* **data visualization** concepts and methods both to realize results as well as, possibly, to glimpse new results through the design and development process (plus, I really like pretty pictures — as a sometimes nonverbal thinker, I depend on diagramming quite often as I work).

And part of me is still interested in old-fashioned **database design** because, in the end, you gotta find some way to keep and account for all this stuff, and it really, really helps others if you have done a decent job upfront and not stuffed everything into an idiosyncratic box of your own devising. And that is why I was so happy to discover the Institute for Historical Research’s [Building and using databases for historical research][bud] course. You can sign up for a free module, or you can enroll in the full course for £99.

I’m not quite flush $150 at the moment, and so I will have to make do with reading the book, but I appreciate the resources being there.

For data visualization, see World of Data’s [Going to Data Visualization School][wod].

[bud]: http://www.history.ac.uk/research-training/courses/building-databases/
[wod]: http://worldofdata.org/2013/01/11/going-to-data-visualization-school/

150 Years of Hurricanes

Nick Felton has done a lot of great graphic design work. He also a Tumblr [blog][] where he posts some of the most curious things. One that caught my eye is this visualization of the [path of hurricanes since 1851][path].

Nick Felton's Visualization of Hurricanes Since 1851

Nick Felton’s Visualization of Hurricanes Since 1851

Where’s he get the data? Does NOAA have lat/long data for that far back? Fascinating, and amazing, work.

[blog]: http://feltron.tumblr.com/
[path]: http://feltron.tumblr.com/image/30367918577

The Big Bang and Religion

The HuffPo has an [infographic][] that details the stance of various U.S. religions on scientific cosmology. Most of the details are in rollovers. But the larger graph also gives you a view of the percentages of religious practitioners within the U.S. population.

[infographic]: http://www.huffingtonpost.com/max-tegmark/religion-and-science-distance-between-not-as-far-as-you-think_b_2664657.html

LinkedIn Network Visualization

[LinkedIn][] now offers to visualize your professional networks. A brief glimpse of mine reveals that the components are, themselves, heterogenous:

My LinkedIn Network

That is, the components are fairly mixed, which, I guess, reveals that a number of people with whom I’ve connected on LinkedIn are themselves involved in a number of communities. The only clear standouts here are my colleagues in folklore studies across the nation. Perhaps the upshot of this is that I have too many local connections and too few national? Or that a number of the national and international scholars don’t participate in LinkedIn, which I think is equally true, especially among my colleagues in network studies, quantitative analysis in the humanities, and computational folklore. Most of them are on Twitter. Interesting split.

[Daniel McLaren has a nice write-up][dm] about downloading your LinkedIn information in a JSON file and then using Protoviz to do improve the visualization. (His principle edit was to remove himself from the center of the graph.)

[LinkedIn]: http://www.linkedin.com
[dm]: http://danielmclaren.com/blog/2011/02/08/visualizing-linkedin-connections-using-protovis

[NASA has interactive flood maps](http://flood.firetree.net/) using Google Maps as the backend. The maps let you see how a rise in sea levels effects various parts of the world. I checked, and it looks like up to about 13 meters (about 45 feet), we’re good where we are in this part of Lafayette, but we beachfront property by then.

Here’s Louisiana with a sea level rise of 5 meters (about 15 feet):

Louisiana's Coast with a Five Meter Rise in Sea Level

[Rear Window Timelapse.](http://vimeo.com/37120554). Jeff Desom has not only compressed the film into two minutes, but he has also set everything in the constant frame of the view from the window: really, just watch the first fifteen seconds to see what he does here. It’s brilliant.