Today’s post is something at the interface of rant and rambling. While I love being interdisciplinary, it’s also quite the hassle at times which is why I guess most interdisciplinary scholars sometimes wished they weren’t doing interdisciplinary work. There are so many negative stereotypes, like… “You have it easier being interdisciplinary” vs it’s actually twice the work So do you really think that we have it easier? I hate how we always get this reproach that we’re taking the easy route. Can somebody please explain to me what’s “easy” about having to follow the state of the art in multiple fields at the same time? And then not even knowing where to get published because scholars from discipline A don’t understand half of your research and the same in the other direction. I tend to be somewhat “too historical” for the Digital Humanities but then waaaay to technical for the “normal Humanities”. I think being in the DH and doing
The D and the H
A category indicating reflections on the balance between being Digital and a Humanist and things like these.
The “Should I include Digital Humanities in my grant proposal?” Guide for Humanities people
Many Humanities scholars feel like you can’t get a project funded anymore if it doesn’t include DH. Some even ask me “Do I have to include DH to get funded?” Well, that answer lies outside of my expertise. I can, however, answer the probably even more important question of whether you should include DH in your grant proposal for the main purpose of improving your chances at getting funded. And if you decide to do so, how to do it right. In this post, I will give you my thoughts on the topic and also provide a checklist you might want to use to answer this question for yourself at the end. As I trust you have already figured out, I am not the person granting you funding neither am I in any way involved in the progress (at least as of now). So please take the thoughts I share here for what they are: my two cents. I’m just
List of Resources for getting started with (teaching) digital methods
Having just attended a talk in an event on Digital Humanities and Neo-Latin, I was inspired to share a short list of introductory resources on DH, especially for teachers who feel more like Humanities scholars and don’t have tons of time to learn everything autodidactically. They can use those resources to learn for themselves and pass on this knowledge or pass on this link. But also, since you’ve found this blog, you’re already on a great path to learning DH! 🙂 I’ll try to keep this updated – and it’s not really done yet, so feel free to contribute. Discipline-independent DH dariahTeach: great MOOCs on many topics Source criticism in a digital age DARIAH-EU DH course registry EADH Courses List Digital Classics Article by yours truly in German: Digitale Lernplattformen und Open Educational Resources im Altsprachlichen Unterricht I. Technische Spielräume am Beispiel des ›Grazer Repositorium antiker Fabeln‹ (GRaF). It contains a few resources on digital resources and digital teaching, mostly
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“Learning LaTeX – Why should you care?” Series Part 1: Common Objections against learning LaTeX
Since some common objections why some people think learning LaTeX is not worth it or why the oppose LaTeX generally came up again in the Twitter discussion surrounding the recent post LaTeX for Philosophers? Logic and other Shenannigans, I quickly wanted to discuss the three most common objections agains LaTeX (in my experience) and why I think they’re not necessarily valid. Let’s get straight to it! 1) The “I can’t both be a good [insert job title/area of expertise here] AND spend time learning to code” aka the “LaTeX is hard to learn” objection A common argument used against LaTeX, not only in the Humanities, is “I already need all my energy being good at my job and now you want me to learn a new technology to distract me from it?”, like expressed in the following Tweet. But it’s really an extremely common one. The argument is interesting to me because you also had to learn how to use
Machine Learning for the Humanities: A very short introduction and a not-so-short reflection
Machine Learning is one of those hot topics at the moment. It’s even starting to become a really hot topic in the Humanities and, of course, also in the DH. But Humanities and Machine Learning are not the most obvious combination for many reasons. Tutorials on how to run machine learning algorithms on your data are starting to pop up in large quantities, even for the DH. But I find it problematic that they often just use those methods, just show you those few lines of code to type in and that’s it. Frameworks have made sure that ML algorithms are easy to use. They actually have a super-low entry level programming-wise thanks to all those libraries. But the actual thing about ML is that you need to understand it or it’s good for nothing. (Ok, I admit there are some uses which are pretty straightforward and don’t need to be fully understood by users, such as Deep Learning powered
News on the DH and Gender Equality
A few weeks ago, I posted The Computational Humanities and Toxic Masculinity? A (long) reflection and didn’t know what reaction to expect. It would either be a shitstorm or get ignored, I assumed. It turns out, however, that the timing might have been just right, since I was contacted by the (informal) Turing Institute reading group – they wanted to discuss my blog post. I was honoured that they did and that I could participate. Here I wanted to share some new insights and reflection prompts this discussion has sparked for me. First things first: Thanks for everyone who participated! First of all, I was happy this discussion happened at all. That’s exactly the type of thing I had aimed for with the post, yet I was pretty surprised it actually happened. After all, you normally don’t always get you want. Maybe it’s that help will always be given at Hogwarts to those who ask for it. 😉 So anyway,
Looking at data with the eyes of a Humanist: How to apply digital skills to your Humanities research questions
In my recent post on how to get started doing DH, I basically said that the essence of being DH is looking at data with the eyes of a Humanist and gave some tips on how to get started in just 10 days. However, it’s not that easy. Learning digital skills and the problem of skill transfer A problem I see a lot is that H people fail to transfer their newly won practical DH skills to their own research questions. They don’t know how to look at their own material as data. They don’t know how to leverage digital methods to help answer their own research questions. But if it isn’t compatible with their own research, they’ll never deepen their knowledge enough to actually profit from their DH skills. If you don’t use them, they are forgotten quickly. So how do you make this transfer which I think is, so far, being neglected as a skill which has to
Three typical conflicts between DH and ‘Normal Humanities’
In this post, I wanted to name the three most important sources of conflict between DH and non-DH people, according to me. There would probably be many more things one could mention, but I wanted to discuss those three to show one thing: The first one is (almost) completely avoidable and the second and third ones nicely show the contradictory nature of thoughts which cause conflicts between Digital and ‘Normal’ Humanists. Disclaimer: Since they are written up by someone in the DH, it could sound to you like I’m saying it’s the NH’s (Normal Humanist’s) fault but that’s not at all what I’m trying to say. (Remember I feel like I’m half-NH myself anyway. And see the Epigrammetry discussion of the D and the H.) I’m just starting from the arguments I get thrown at me (thus from the Normal Humanists’ perspective) and respond why I think they’re not universally valid (DH perspective). However, it would work just the same
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Is learning how to program like learning a foreign language?
Is learning how to program like learning a foreign language? Well, it’s a definite “yes and no” from me. I think many people oversimplify this. And then they say that their programmer friends think the same way to ‘prove the point’. Mostly I bite back the question of how many ‘real languages’ the programmer friends have learned or even learned to a native-like level. Because I think that there are some quite important differences. Since I just read this brilliant article The Ancient Case Against Programming “Languages” by Patrick J. Burns on Eidolon (Apr 24, 2017), I thought I could contribute some of my thoughts on the topic as well. They stem less from the interest in not losing funding for second language education, but rather from some of my own experiences in “second language programming education” or whatever one might call it – the act of learning programming (in your 20ies at earliest) after having learned multiple natural languages as
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LaTeX Ninja'ing and the Digital Humanities 