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Dinosaurs eat data, humanists inherit the Earth

Apparently dinosaurs, data, and the digital is a thing around here, dear readers. If that is not your jam, the helicopter is still running. You can hop off this island right now. 

But for the rest of you? 

Hop in, buckle up, and welcome to Cassie’s Park. 

From “A-ha” to “Aaaaahhhhhhh!”

My foray into digital history and digital humanities (which for the remainder of this blog, I will collectively refer to as “DH” for simplicity) started with wonder. Creating digital things had seemed entirely untouchable, especially for a (proud) community college alum who (at the time) aspired to be a High School Special Education teacher. Sure, I could look at interesting DH sites and even learn from them. But when my curiosity helped me land a position supporting the indelible and all-around-fantastic Pam Lach at the SDSU Digital Humanities Center, I had my first “A-ha!” moments with DH. 

A-ha! I could build a site! 

A-ha! I can use KnightLabJS tools!

A-ha! It is ok to make mistakes!

A-ha! We are all really just figuring it out (albeit at different levels- but still!)

But the “A-ha”s began to have more “AAAAHHHHHH!”s sprinkled in. Then it became mostly just…..AAAAHHHHHHH!. Especially when it came to networks.

One major “AAAHHH” moment came during a faculty workshop on the basics of using Scalar, a non-linear publishing platform that allows for multimedia exploration of networks. 

Now, I am a tactile “learn by doing and getting your hands in the dirt” type of gal. And that is how I prefer to structure workshops, when there is time. Scaffold with the “whats” and “whys”, dazzle them with “here’s a cool example”, shock them with “and YOU can totally do it to!”, then turn them loose in a digital sand-box. 

To keep it spicy, I’ll even sometimes hit the group with some shocking jargon, give them a mini “aaahhhhhh” fake-out, only to say “just kidding, y’all literally just did that! See, it’s totally possible!”

But one afternoon after such a workshop, one Professor of DH came for me. This person’s silhouette appeared on the frosted glass of my office. The door handle jiggled. I froze.


“What is your experience with [insert programming languages here]?”

“Can you elaborate on semiotic-symbolic-cymbal-simian-shimming-stegosaurus possibilities of non-linear….”

I did not hear the rest because white noise overtook my hearing and flight-or-fight kicked in.

I chose to fight (with humor, of course). “Self-effacing joke”, “deflecting joke”, “Well, in the digital humanities, my digital is size eight font and the humanities is size 20, bold, and underlined.” Hahahah-aaaaaaaahhhhh-sob.

Being a digital HUMANIST and HISTORIAN

That stuck with me. Until reading Scott B. Weingart’s “Demystifying Networks, Parts I & II.” 

What a refreshing “a-ha” moment!

Weingart’s work clicked with me for three reasons. First, it explains networks in an accessible way that helped me not only understand networks better, but Scalar as well. Second, there is a clear call to reign in any over enthusiasm with networks and meaningful examples of what can be lost when employing that method. And third, because of the first two reasons, it will absolutely be going into rotation for any future workshops or the like that I do.

“The Stuff”

Weingart explains networks in roughly three categories- “The Basics”, “The Stuff”, and “The Relationships”, and introduces technical terms and jargon after. Explaining to someone what a node is and expecting that person to realize nodes are “The Stuff”, or introducing that concept after a technical definition, is a bit of burying the lede for humanists. And fear inducing for some of us (me).

But, dare I say, all of us can understand “stuff” and use it on the regular. So, since “stuff” are the essential “things” that humanists work with and explore, and a “node” is just more of that “stuff”, then a node is what we are working with and exploring. Simple, yet effective.

Structuring the explanation of networks this way supports Johanna Drucker’s call for DH graphical displays and networks to be grounded in humanistic approaches “expressed according to graphics built from interpretative models.” Networks, when explained using Weingart’s language, maintain more of that interpretation and humanistic approach than computer science based explanations. “The Stuff” and “The Relationships” are clear categories for interpretive and nuanced information. When asked to think about “The Relationships” of their work, a humanist may start listing spatial, economic, familial, temporal, and many other relationship possibilities. But when asked to think about the “edges” of their work- the accurate but much more “scientific” term that carries certain connotations- then the list of relationships may start to look much different (especially for students and emerging scholars who do not have a computer background). This, again, reinforces Drucker’s argument that rethinking data by “shifting its terms from certainty to ambiguity” is a critical first step to then finding “graphical means of expressing interpretative complexity” in DH work.

Humanistic data are almost by definition uncertain, open to interpretation, flexible, and not easily definable. Node types are by definition concrete; your object either is or is not a book. Every book-type thing must share certain unchanging characteristics. This reduction of data comes at a price, one that some argue traditionally divided the humanities and social sciences. If humanists care more about the differences than the regularities, more about what makes an object unique rather than what makes it similar, that is the very information they are likely to lose by defining their objects as nodes. This is not to say it cannot be done, or even that it has not! People are clever, and network science is more flexible than some give it credit for. The important thing is either to be aware of what you are losing when you reduce your objects to one or a few types of nodes, or to change the methods of network science to fit your more complex data.

These readings in tandem led me to a major “OOOOOooooo!” and “A-ha!” moment with Scalar. I understand how to use it, how the “whole-whole” and “whole-part” relationships can be leveraged, and the unique power of creating non-linear multimedia narratives. But it still remained a little….confusing. But now I clearly see that it is a graphical visualization of networks that embraces what Weingart and Drucker are calling for- networks of data that emphasize interpretation, nuance, and humanistic methods.

Yea…you can, but should you?


It’s a well known phrase, “when all you’ve got is a hammer, everything looks like nails.” Or, to amend it slightly for students and people who learn new, cool things, “when you get taught how to use a hammer and have access to a hammer, you’ll swing around wildly and enthusiastically thinking you’re hitting nails.”

Weingart offers two clear arguments for keeping the hammer in the tool box, no matter how “neat” it is. One- though everything is arguably in a network and can be networked, networking everything is not only irresponsible but takes away from when it is very meaningful to do so. And two- “borrowing” methods come with a lot of baggage and potential problems, so it should be done carefully, thoughtfully, and sometimes “things” need to be thrown out of the baggage in order for it to be meaningful to DH. Again, this is explored in more depth by Johanna Drucker, though in more technical terms.

Though these cautions are not directly related to the subject of this week- “networks”- they are very important. When considering the creation and exploration of networks (via Scalar or using more traditional network visualization tools), these two points are helpful in my analysis of networks (did this need to be a network?) and potential development of them (is there something else that may better serve the interpretation and research?). Further, these serve as reminders that as a humanist who may incorporate networks and other similar tools into their work, I am not beholden to (and should actively push against) concepts of data as neutral, unsullied points that these methods may (accidentally or on purpose) champion. As long as the approaches and adaptations to the DH methods are part of the conversation, strategically dropping some of the “baggage” of computer science and computation methods can actually enhance the impact and interpretation of the work.

Humanists find a way

The “a-ha” moments about networks specifically, and DH generally, that Weingart and Drucker provided me this week will affect how to incorporate each in public and educational spaces. It seems inevitable that my path in history and DH will include community and teaching, so I am excited to have scholarship not only that I can cite to guide my work but to share with others who may feel intimidated by DH, nodes, and edges.


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