For the last two years, I had the responsibility to mentor master’s degree students in the Digital Humanities or to advise those interested in a DH degree. Today I wanted to discuss the most frequently asked question and that is: “Am I ‘techie’ enough for (a) Digital Humanities (degree)?” and partly also “How much math is there in a DH degree?”. This is my Christmas present to you.

I’m hoping to do something LaTeX-related again soon but LaTeX templates are currently a go-to relax thing for times when I really need relaxing. And feeling obliged to write about that takes the fun out of it for me at the moment, so sorry, yet another DH post for now. Let’s get straight to it.

Part of this post consists of the text of an informational video I made in my responsibility as a mentor for the DH degree programm in Graz. You can watch the video instead, if you like. However, this post contains some more information regarding the most frequently asked question regarding the DH degree: Am I techie enough for (a) Digital Humanities (degree)? And also the related question: How much math is in a DH degree?

Am I techie enough for (a) Digital Humanities (degree)?

I’d like to say, short answer: Yes. But actually, no. Not everybody is. And that’s not a judgement about your value or anything, it’s just that in my experience – even though I wanted to believe everybody can do DH – it seems that some people aren’t really made for it. Or they’re not really trying or not actually liking what that would imply (like learning to code because that’s hard sometimes).

However, don’t be deterred too quickly. Many Humanities people shy away too easily because they think of themselves as basically the opposite of “techie”. But that might not actually be true. And remember that most DH scholars actually started out just like you. Most of us don’t come from a place of being confident in our tech skills or math geniuses (although, let’s not get into all that’s problematic with the idea of genius right now).

You have to give yourself the chance to actually try and make sure you have a good idea of what DH actually is before making the call. Which is why I will now share with you the text of the promotional video I made for our DH degree (keep in mind that other DH degrees might have different specializations). Because in order to understand whether you’re “techie” enough (whatever the hell that means), you need to know what the DH actually entail, so here comes the text:

In the master’s degree programme “Digital Humanities”, students learn what advantages the usage of digital tools can have for the Humanities and how they are developed.

The technological advances of the last decades have led to the creation of a new research paradigm in the Humanities: The Digital Humanities operate at the intersection of Humanities and Computer or Information Science. The usage of digital methods offers new ways of analysis of historical sources and changes approaches within Humanities scholarship. 

The teaching modules contain, for example, basic knowledge of computer science, subject-specific approaches (relating to the fields in which students have obtained their bachelor’s degrees), data formats, data standards, web technologies, databases, programming languages and visualization techniques. Among other things, data formalization according to the principles of information science, data modeling, analysis, transformation, processing, administration and long-term archiving of Humanities data are considered in depth.   

Data processing using the so-called X-technologies (revolving around the XML data format) are a key application in many areas of the Digital Humanities. But the Digital Humanities are much more than that!

Tasks usually considered as parts of Digital Humanities jobs include the creation of data. In the example, you can see the Transkribus software being used for the automated machine-transcription of historical print. 

Secondly, the presentation of data, as shown on projects from the GAMS infrastructure where web views are generated from XML data. 

Thirdly, preservation and long-term archiving of data, for example by using appropriate data formats such as XML.  

But also the analysis of data, like for example quantitative text analysis. 

The master’s programme is geared towards students with a Bachelor’s degree in any discipline in the Humanities who want to add practical tools and methods for digital analysis to the knowledge from their previous bachelor’s degree.

Apart from some general “computer literacy”, no specific technical knowledge is required as a prerequisite for enrolling in this master’s programme. Being generally comfortable around computers is advantageous, however.

Many students ask us how technologically adept you need to be to thrive in this programme.

Here, you should keep in mind that the goal is to learn digital tools for Humanities applications. The study programme covers a wide range of topics from data modelling in XML and XML data standards, web design in HTML, CSS and JavaScript or even research software engineering in Python or Java. Students are free to choose which side of the spectrum they want to specialize in, however, students will have to learn the basics in all of these areas which are core elements of the DH.

In this example, you can see how the text of Mary Shelley’s Frankenstein is downloaded programmatically from Project Gutenberg and a few simple operations of quantitative text analysis are carried out. 

Cooperation with and communication between technology and less technologically adept users is an important part of DH work. Programming and understanding the technical backgrounds behind digital applications are also inevitable, at least up to a certain degree. Should you desire to do so, you can specialize in this as well.

Digital Humanities graduates can apply to jobs in a university context, may that be Digital Humanities centres or in the context of traditional Humanities scholarship. Other fields are the conceptualization, dissemination and implementation of Digital Humanities projects, science communication with a focus on digital cultural heritage. In archives or museums, scholars work both on the digitization of historical objects as well as their scholarly interpretation. The combination of Humanities and Computer Science can also lead to positions in the creative industry, in media companies, in data processing as well as in communication.

Further wisdom I wish to bestow upon you 😉

I wanted to express that past experience and past success doesn’t necessarily determine future success. Only because you were never a techie/maths person doesn’t mean you can’t become one! (see this post on the right mindset)

I was always the “girls with the languages” but then I got my first research student job in the DH and suddenly everybody treated me like I must know all the solutions to their (DH-unrelated) tech problems. It’s all about perception and mindset. And, interestingly enough, because your self-perception changes with those changed expectations, you end up learning all or most of those skills people expect you to have. Just so you can meet those expectations. You also start thinking of yourself as someone who’s perfectly capable of teaching themselves such things because that’s who you are now. So just try to use that bias that comes with doing DH to help you. But don’t let it be held against you, especially if you’re a woman!

And watch this BBC video which illustrates really well how “tech/maths/logical talents” – supposedly more common or pronounced in men – are actually very likely the result of years and years of such expectations and, with them, increased exposure to tech learning experiences.

Also, if you’re still unsure about what it means to do DH, consider the following blogposts:

1. What are ‘real’ Digital Humanities and how to get started?
2. Looking at data with the eyes of a Humanist: How to apply digital skills to your Humanities research questions
3. Formulating Research Questions For Using DH Methods
4. For an intro to programming terms: Algorithms, Variables, Debugging? Intro to Programming Concepts
5. Also, the DH Bootcamp and Digital Humanities categories on this blog

How much math/CS is there in a DH degree?

Short answer: No math. Professors interested in defending DH also as a theoretical science will probably dislike me saying this and, of course, some understanding of math can never hurt. Just like I think everybody should absolutely be made to learn Latin to a high degree because I’m a Latin teacher and I love Latin. But do people survive out there in the wild without knowing Latin? To my great astonishment, I hear that some do, in fact! 😉

Unless you’re a Latinist like me or at least someone working heavily with Latin sources (or early Romance-language sources), you’ll hardly ever need your Latin skills. You are likely already aware of that fact. Would it be helpful to have good Latin sometimes? Occasionally. But is it necessary? (I as a Latinist will, of course, say yes but I know that most people, probably rightly so, would say:) No. The same goes for math. If you wanted to dive deeply into Data Science or Machine Learning, it would be helpful for sure. But if that ever happens, you can still learn/refresh some maths when it becomes necessary. Will it be an advantage to those who have already done that work? Sure. (Might also mean that you’ve already forgotten most of it.) But you will only specialize in Data Science or ML as a Digital Humanist if you’re really into it and in that case, you’re also able to muster up the energy to get it done. Apart from that, lots of applied Data Science and ML work can still be done without math. It would be good to have a basic understanding of some stuff for sure – but we’re still talking extremely specialized skills for someone in the DH. Don’t let this be the basis upon which you make your decision whether or not to pursue DH!

So I hope that answers your question. To take it a bit further, maybe we can ask the less heretical question of “Do you need to be good at math to become a Computer Scientist?” In this case, you don’t need to be good yet but you do need to learn math to a higher than average level because it’s not just coding, it’s computer science. Learning that theoretical background even though you might not be able to see straightaway how you’re going to use that in your daily life – that’s what makes it a science and distinguishes it from being a self-taught code monkey. Unless you are a code monkey who’s also crazy about math.

Like you having a basic understanding of Latin is/was/should still be a prerequisite to be a Humanities person, at least if you’re working on stuff before 1800. But do most people actually have a good command of Latin? No, absolutely not. I even know people who work with Latin sources and don’t actually know Latin (mostly from Anglophone academia). If they dare to do that, you shouldn’t doubt your DH aptitude on the basis of your math skills! (Although I wouldn’t recommend working on Latin sources without knowing Latin.)

To bring the conclusion back to the DH: Like I say in the promotional text from the promotional video – there is more than one way of being DH. Liking math certainly isn’t an obstacle if you want to dive into Numerical or Computational Humanities or however you might want to call the more “techie” side of DH. But is liking math a requirement? Hell no.

Have I ever needed math in my DH life? Maybe to count to how much my beverages consumed at the conference dinner add up to or so I knew if I had enough money upon leaving after work events. Related question: Do you need algorithms? Well, it would probably be good to have some knowledge about algorithms. But in my honest experience, even with algorithms, most DHers don’t (or maybe they would ideally need them but I think if you asked most if they know stuff about algorithms, they’d politely decline). So please, don’t be scared away because of that – it would be a false expectation.

If you need any Computer Science style skills, you will be taught those skills in the programme you study. Usually, for DH programmes, technical skills are not required to have before entering the programme. You will learn the ones you need. Will you have to do some self-directed learning? Yes. Do you need to web-research your own error messages? Yes, please. Do you need to experience failures while learning to code? Yes, you need to be up for that. No learning without failures. But you can make those mistakes while no one is watching and you need to know that everybody makes lots of mistakes while programming. Even experienced programmers spend a lot of their time web-searching solutions to coding problems they’ve encountered.

So is disliking math and having no previous tech/coding experience a reason for you to shy away from DH? Absolutely not!

Also, please be sure to check your chosen programme whether it has math if that’s really a big issue for you. There are some specialized programmes which might actually have a little bit of math, especially if it’s more in the direction of Computational Linguistics. But I don’t know of any but I’m also actually not very well-informed about that. Please do your own research in that case.

Do I need a degree at all? Many blogs about coding say you don’t need a degree to work in CS nowadays…

Short answer: Yes, you need a degree to work in DH. Most DH jobs are in academic contexts and they don’t usually hire based upon your github portfolio, no matter how good it is. Sorry. (But also, please do build a github portfolio over time – it will be a great asset in job talks). Furthermore, since most DHers see DH as research/scholarship (as opposed to just being tech guys for the actual Humanties people), you need to have that theoretical part/grounding which is a necessary requirement for something to be considered a science (as opposed to just coding).

Just be aware that, like I say in the text, DH is a broad field and if you want to get a degree, you will indeed need to take a peek into many of those more ‘theoretical background’ aspects – that also means learning some theoretical computer science maybe or learning a technology you’ll never use again. That’s what makes a research degree programme different from a code bootcamp. The code camp is shorter and you’ll probably be launced into the practical track much faster but there likely also isn’t time for you to build up experience with the theoretical stuff (because this needs a while to set in).

And since DH jobs mostly are in academic contexts, chances are, you’ll need a degree – unlike with coding where many argue nowadays that you don’t need to actually get a degree to work in computer science. University law likely will not allow you – or at least make it extremely difficult – to get hired for a real position if you have no master’s level degree. (Although if you already have a Master’s level degree in some other Humanities field, as of now, you should be set. You can get away with just a “DH bootcamp” or github portfolio to prove your DH skills. I’m not sure this will work in the future though if you want to apply to jobs explicitly labelled as DH jobs.)

So yes, you’ll have to go through some theory you might think pointless. That’s university. You’ll appreciate how it made sense in a few years time.

Hoping you are well this special Christmas,

happy holidays,

the Ninja

(peeking out of her dissertation hole just to quickly deliver this post to you) 😉