The verb "to ninja" means "to act or move like a ninja, particularly with regard to a combination of speed, power, and stealth." LaTeX adventures, demystifying digital tools for Humanists, one tutorial at a time.
A category to post “beginner level” posts to make them easy to find. The topics get specified by other categories and tags.
Modelling is central to the Digital Humanities. Even so much that some claim it is what unites the DH as a field or discipline! But what is modelling? What do we mean by it anyway? This post will hopefully provide you with the primer you need. Sorry for the very sporadic blogging lately. I still haven’t figured out how to include blogging into my PostDoc life. I think I want to get to a rhythm of around 1-2 posts per month. More than that is absolutely not realistic but, as you may have realized, I didn’t even manage that consistently over the last year. Then again, it’s not like I’m not producing teaching materials anymore. Most of my efforts this year have gone into all the classes I have been teaching (I’m hoping to share slides and teaching materials for all of them once they are cleaned up) – I have taught an intro to text mining, my usual information
Today’s post is a short introduction to digital scholarly editing. I will explain some basic principles (so mostly theory) and point you to a few resources you will need to get started in a more practical fashion. I’m teaching a class on digital scholarly editing this term, so I thought I could use the opportunity to write an intro post on this important topic. How does a Digital Edition relate to an analogue scholarly edition? Unlike analogue scholarly editons, digital editions are not exclusive to text and they overcome the limitations of print by following what we call a digital paradigm rather than an analogue one. This means that a digital edition cannot be given in print without loss of content or functionality. A retrodigitized edition (an existing analogue edition which is digitized and made available online), thus, isn’t enough to qualify as a digital edition because it follows the analogue paradigm. Ergo: It’s not about the storage medium. A
Today’s post is a quick introduction to version control as a concept and version control systems. It explains what they are and why you should be using them. I was just sending one of my best old-timey blogposts to a friend (How to quit MS Word for good), ended up re-reading it and realized that therein, I had promised that I would write a blog post on version control some day. And, if I’m not mistaken, I never followed up on that. So here you are, a short post on version control just to keep things going on the blog. What is Version Control? So I read this book a few years ago. The Complete Software Developer’s Career Guide: How to Learn Programming Languages Quickly, Ace Your Programming Interview, and Land Your Software Developer Dream Job by John Sonmez (Simple Programmer 2017). While I’m not that fond of its author anymore since I realized that he uses his platform to
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
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
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 starting to learn LaTeX now. Just to sum up what has already been said in the last post: 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. But there are many more things to take into account. 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”
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
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
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.
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
I have been following the #100DaysofCode community for a while now and thought that it was sad that there didn’t seem to be a connection with the DH community. 100 Days of Code is such a great project which is motivational for those willing to learn but also a great way to foster a community. So I thought, why not start #100DaysofDH and I did. Looking forward to your contributions! The main activity around this will be happening on Twitter (account is @100DaysofDH, hashtag #100DaysofDH) but there is also a minimalist github.io page: https://100daysofdh.github.io/ On the github, you can also find the current state of the Tweepy and AWS-powered bot. The story behind the creation of this challenge Before getting into the details of how the challenge works, let me share some thoughts that I had in mind for the adaption of the 100 days challenge to the DH (skip this part if you just want the rules which can
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
In the feedback forms I did on the DH classes I have taught over the last years, I got one feedback I didn’t expect: People were extremely grateful I had practiced with them how to formulate valid research questions which, apparently, no one had ever (really) done with them before. I found that quite astonishing because the DH are all about methods and methods are like specizalized tools. You need to know what you can use them for. So here’s the crashcourse. The Hammer and the Nail I want to start off with an analogy. A hammer is a specialized but not an extremely specialized tool. You can use it for a range of tasks, however, not all tasks are going to work equally well. Some might work but would actually require a more specialized tool if you had one. You can really use the hammer on about anything and almost always, something is going to happen. For example, you