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Navigating interdisciplinarity (as a DH scholar)

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

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The most important book to read if you want to learn Digital Humanities, Computer Science, Maths, Programming or LaTeX

Today I wanted to share a tiny book review of the book I claim to be the most important book you should read if you want to learn any technical topic but are unsure if you are up for it. The book I’m talking about is not Donald Knuth (although his books are highly recommended, especially if you’re a (La)TeX nerd!). It’s not even a computer book! I’m talking about: Mindset: The New Psychology of Success by Carol Dweck (New York: Random House 2006). The fixed mindset versus the growth mindset This will be a short post because Dweck’s message is simple. There are two mindsets, the ‘fixed mindset’ and the ‘growth mindset’ and which one you have greatly impacts your success in learning and self-development. The ‘fixed mindset’ assumes your abilities and talents are fixed. Thus, you are proud of what you’re good at because you link it to your personality (“I’m a person who is good at…”). But

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LaTeX for thesis writing

Having re-read my LaTeX for PhD students post, I realized I hadn’t mentioned a lot of things I would like to impart to you. So here comes LaTeX for thesis writing – a few more arguments in favour of learning LaTeX now. The main points speaking in favour of you typesetting your thesis in LaTeX are the citation management, tables, maths and images which can be more of a hastle in MS Word. In the aforementioned blogpost, I also added that you should take into account that a thesis will yield two PDF outputs with very different requirements from the same document – another reason to use LaTeX. LaTeX for maths, images and the like (in short, everything MS Word isn’t good at) A lot of people say that the “LaTeX is great for maths” argument isn’t that strong anymore nowadays because MS Word has caught up a lot. I couldn’t tell you because I don’t usually use math in

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Learning to program: Debugging – Where to start?

After a long hiatus, I’m back today with a post on how to develop the debugging skill. If you’re new to programming, we refer to the process of finding and solving errors in the code as “debugging”. It can be difficult to acquire this skill as a newbie when you have no idea what you should even look for. This post will help you out with a few hints. Why should I learn debugging? Most people who attend a programming class for the first time get quite the culture shock. Often, their identity had encompassed something like “good with computers”. Then they see what it’s actually like to interact with a computer as a superuser, i.e. someone who interacts with the computer not only in the way intended for users by product designers, i.e. mostly the Graphical User Interface (GUI). Often computer usage the superuser way means it’s entirely text-based (although you can learn the first steps to programming with

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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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Is the Ninja dead? No. But you deserve an update!

I’m not sure if anybody even realized I haven’t been posting lately but this is the longest hiatus we’ve ever had on this blog thus far. It was my normal practice to post pre-scheduled posts only every other week when on fellowships but now I totally went off the (WordPress) grid and I wanted to reconnect with you all. (And also, Easter greetings – if that’s something you care about!) As you might have imagined, I’m quite busy at the moment. I have some typesetting going on (my god, I’m not sure I will ever agree again to typeset a book that I’m also responsible for as an editor, it’s a crazy amount of work!), then I should finish my PhD thesis, I’m on a fellowship where I should finish a translation before heading off to the next fellowship which I hope I can actually get to because it’s in the US. So yeah, busy times. Although I have to

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The most important tip for confident LaTeX newbies: Don’t reinvent the wheel! (and try a Minimal Working Example instead)

Today I wanted to address a common issue I see in troubleshooting LaTeX errors, on StackOverflow and in personal questions. It usually stems from newbies who aren’t yet aware of all the functionality provided by standard packages and thus, try to reinvent the wheel when something doesn’t work the way they expect. Why reinventing the wheel is a problem In my experience, even from me helping people with packages that I’m not all that familiar with myself, it’s always best not to reinvent the wheel (even if you succeed, the result is likely sub-par unless you’re actually really good at what you’re doing). Ask yourself if the functionality you want is something that’s likely to be a common problem. Then maybe somebody has already solved it in a comprehensive way! That’s what packages are for and that’s why they’re (hopefully) maintained by people who have given the problem at hand a good bit of thought. It is very likely that

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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

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LaTeX for Philosophers? Logic and other Shenannigans

Today, I wanted to share LaTeX resources for philosophers with you in a short post. I was included in a Twitter discussion yesterday about whether there wasn’t a post like that and I remembered there was – because a fairly long time ago I had been planning to write a post like that myself and already had a draft lying around in the depths of my WordPress account. So this is it, a short review of resources regarding the question: Should philosophers use LaTeX and what resources are there? Personal backstory which is totally irrelevant to the actual post: Funnily enough, one of my degrees is actually a Master’s degree in Philosophy, so you could say I know the field. However, I would think of my time at the Philosophy department more like a “field trip”, so to say. (Uh-oh, today is one of those bad-pun days.) I felt like getting to know the field to broaden my horizon or

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The question of questions: Am I ‘techie’ enough for (a) Digital Humanities (degree)?

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,

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Where can I *actually learn* programming? (as DH and otherwise)

To my great surprise, lots of people regularly ask me where I learned to program. I have lots of posts on the subject and even multiple categories on the blog concerning the topic but maybe they’re “too disguised” under obscure titles for willing learners to actually find them. So I decided to give you a short summary with the key takeaways of what I’ve written on the topic so far and the most important links – boths to my other detailled blogposts and also on the resoures I would recommend as of now. However, before the “short summary” of takeaways and suggestions for willing learners, let me start with a deep dive into the very personal side of the question “Where did you actually learn to program?”. Now where did I actually learn to code? A Disclaimer To answer the question “Where did I actually learn to program?”, we need to talk about my journey first. And.. Well, in order

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I finally finished my own #100DaysofDH – Here’s the wisdom!

Like the title says, I finally finished my own #100DaysofDH challenge. And I haven’t kept my promise to you guys. I (think I) said I would continue blogging every second week but now I’ve left you hanging for a whole month! I’m so sorry. I will try to get back into a regular posting schedule (still reduced until the dissertation is done but I’ll try to at least post every once in a while). Anyways, as I’m nearing the end of my #100DaysofDH challenge (and having declared myself as the worst challenge founder ever in history), I’m starting to get philosophical and the wisdom is coming in. Since I couldn’t deprive you of that, here it comes. (It really isn’t that bad, actually!) Wisdom 1: Read error messages, it works! This one is kind of self-explanatory but once you’re in those long coding sessions, you sometimes forget to do the most obvious stuff. I just recently coded on some stuff

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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

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Easy and quick strategies to #scicomm your DH project

Your digital project is great, I’m sure of that – but does it even exist if nobody knows about it? Science communication is the answer to avoid this philosophical dilemma. In this short post, I wanted to share a list of quick-and-easy-to-implement ideas to add some science communication to your projects. This is just a short post to give you some ideas, not tutorials on how to do it. However, I am open to any tutorial requests you might have on the topics involved. As for the Twitter bot, there is a short post available already. So let’s get to it! Quick and easy strategies to #scicomm your DH project Create a better / thematic / facetted search interface. Maybe people aren’t using your data because the interface is not intuitive and they can’t find things or don’t know what to look for and where to look. This is the basic building block to build all the following things on.

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Create your Tweepy/AWS-powered Twitter bot in a day

This post wants to convince you to try out creating a Twitter bot using Python Tweepy and AmazonAWS Lambda because it’s easy and fun. Of course, you can use any other utilities but Tweepy and AWS Lambda are the ones I tried. This is not a full tutorial but I can make one if anyone is interested. Inspired by the #100DaysofDH challenge In this post, I will just give you some basic Twitter knowledge, links for what you need to know to get it done and a link to the github of my #100DaysofDH challenge for which I implemented such a bot. If you want more guidance, please let me know. Also, read the post on the challenge because I noted down some restrictions I realized the Twitter automation guidelines impose on bots as I went along. In my example, I think I’m in fact doing one or two things which you actually shouldn’t do (I think bots shouldn’t like

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