Two Row Academic CV

I know I’ve been neglecting this blog lately during my fellowship. But I hope you, my dear readers, can be soothed by another CV template. This one, for once, does not use paracol at all. It is just an article document class with the twocolumn option.

It is fairly simple but can accommodate lots of information which can come in handy for academic CVs. It is relatively classic and basic but still doesn’t look like any other template either.

Since it doesn’t use paracol, however, getting the black rules (cvrule) to line up beside each other might be difficult, if that’s what you want. Usage with perfectly lined up rules wasn’t intended, but could be achieved by changing the twocolumn to a normal article using the paracol package. The colour can be made into grey or whatever you want. It is indicated in the comments where this can be done.

For listing publications, multiple different versions are available (look closely!). You can try out all the alternatives and then stick with what works best for you.

two-row-academic-cv
The github repo is here. Be sure to try it out as a template on Overleaf!

I hope you like it and maybe have use for it in you next applications.

So long and: THANKS FOR ALL THE FISH!

XO

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Simple Modern CV

After a short absence, I thought I’d treat you to another CV template as an excuse 😉 The template is a simple yet modern academic CV with two columns, using the paracol package for the columns. So you would be able to change the colwidth to asymmetric if you wanted. I used to use this template myself, in a slightly different form, a few years ago. But the code was complicated and I found it not optimal, so I combined the old CV’s general idea with the tabulars from the Hipster CV. The old code, for instance, was done using minipages for ‘columns’ which prevented automated column or page breaks. With a long CV, it became quite a nuisance to control this all manually. That’s why I started looking for an alternative and have switched to paracol for good in these matters.

modern-simple-cv
The Simple Modern CV on github.

This template, different from the colour-clashy Hipster CV, has no colour, but still some of the Hipster’s tabulars for vizalizing your skills. So it’s not a completely plain tabular CV either. Let’s say, it’s a tabular CV but better 😉 While the template has no colour, adding logos to your events will still make it relatively colourful and thus, not strictly classic, why I called it “modern”. Actually I somtimes find the logos suffice to make it fairly “flashy” as opposed a very classic academic CV.

The github repo is here. And hopefully, it will be available on Overleaf as a template soon as well.

Hope you like it,

and thanks for all the fish!

The Ninja

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 a Humanist.

Elegant code reads like a human language

Of course, some elements in programming are like learning a real language. For instance, good code should ‘read’ like spoken language. If it sounds too ‘unnatural’, something’s wrong with your code. Or, at least, it’s not very elegant. Elegant code reads like a human language. Ok. But this is only at the surface. To a human. Not to the machine beneath it. After all, in the end the thing about programming is that it’s not a natural language. The ‘natural language looking part’ is only the face your code shows to you as a human. And it is a common opinion amongst programmers that you can’t write good code without understanding the machine. Well, maybe in web programming you can get away with it. But for anything and everything else, you don’t actually.

“It’s like learning a natural language in the way that you need to use it.”

Some people say “It’s like learning a natural language in the way that you need to use it. You can’t learn it theoretically.” Ok, agreed. In that respect, yes. You need a good reason for wanting to communicate and use the language (and actually end up doing it), if you ever want to get good. But this is true of any skill. Of course, you need practice. So is this really a criterion valid for the comparison between learning programming and learning a natural language? They’re both skills. And I think in this case, it’s more about both being a skill to be learned than the ‘language part’ which is their commonality.

A human language requires skills a computer language doesn’t and the other way round

In this discussion, it often happens that people mix up the general skill of programming and the programming language. Like I have mentioned multiple times before.

But the point is that, in my opinion, it’s the ‘algorithmic thinking’ and the specific skill in programming which is difficult with learning to program. The complexity doesn’t come from the language. After all, compared to a human language, computer languages are blatantly simplicistic. The difficult part is understanding algorithmic thinking, algorithms, data structures, having a genereal knowledge of how things work behind the scenes. This skill is not required in human language, I think. You can master you mother tongue (and a foreign language too, by the way) without ever looking up the grammar. You get a feeling for it. When have you ever mastered a (sufficiently complex) function from a library without looking up its arguments?!

No listening or spoken part about programming – communication functions differently

You only read programming languages. There is no spoken or listening part. This makes for a huge difference since this is the part lots of people have difficulty with, especially in attaining native-like level. Getting rid of accents is a never-ending endeavour. What does this compare to in programming?

You never stop learning a living language

Also, with a human language, you can never fully master it. Which is possible for a programming language, I would say. Of course, there always is room for improvement in general problem solving skills. But, for example, John Sonmez mentions in his book The Complete Software Developer’s Career Guide that after a solid amount of time of being a good full-time programmer, you do reach a ‘glass ceiling’ where he says that, essentially, all who have reached this point are virtually at the same skill level. This suggests to me that a natural language is more complex than programming even with the whole other skill set involved (other than the language itself which is quite obviously less complex). But of course in programming, you can get into many surrounding fields or topics which make sure it doesn’t get boring. Yet here, I really can’t see how natural languages and computer langauges are very much alike.

They are similar, however, in the way that they constantly evolve and you need to learn the new stuff regularly if you want to keep up. This development is maybe even a little bit faster and more challenging with programming languages.

It’s both easier and harder

In programming, you (can) get away with very little vocabulary and grammar. Bad style still compiles most times whereas in real-world situations, really bad style might cause you to not be understood by fellow humans. While it’s noted, of course, that humans usually try to interpret your utterings in a way to understand you when a compiler will just stop and complain something’s wrong. Hopefully with a helpful error message attached.

When judging people’s skills, always take into account (and don’t underestimate) the amount of hours they’ve invested getting to their current level

I feel that it’s quite common when talking about skills that we want to identify some people as geniuses. While I don’t say that there are no geniuses, my experience shows that you need to break down the information very carefully before you judge someone a genius. There are a lot less geniuses around than people want to make you think, especially in the land of Academica where everybody like to think of themselves as a genius.  A genius is someone who gets very good at multiple (!) very different skills with hardly any effort. This is, as far as I remember, a common (scientific) definition of highly intelligent people. Yet in everyday talk, we often assume high IQs in people who are extremly good in their field. But acutally, your general intelligence only gets proven by the ability of easily reaching this level of competence, very fast, in practically any given field (or at least multiple). Often, people hide the fact that they actually put in a lot of effort.

If somebody has spent 10x the hours you spent to learn something and is a bit better than you, is this really a sign for a genius? For perseverence and discipline maybe, but putting in more time and thus ending up being better is not a sign of extraordinary talent. By which I don’t want to minimize anything, I just think we should abstain from jumping to conclusions and generate an inflation of geniuses along the way. Because this actually destrocys what ‘excellence’ means: It’s the one who stands out from the crowd. Yes, the one. There can only be one best at anything. Excellence initiatives therefore really are quite a ridiculous concept, operating on the assumption you could have armies of excellent people. Not in the strict sense of the word, you can’t. Rant over.

What has this got to do with the subject of this blog?

Well, it appears to me that nowadays, we often think people with good programming skills are geniuses. And maybe they are. I’m not saying they can’t be. But I think that especially us in the Humanities should pay very careful attention that we don’t over-value programming skills and under-value our own. But saying programming languages and real languages are the same skill can easily end up in “real languages are inferior” or “skills in living languages are inferior to programming skills”. So I think it’s important to keep the distinction. After all, to a real programmer who understands the machine, it will be quite clear that, in fact, a programming language is really not like a natural language at all.

While this may appear to be simply splitting hairs over the word “language,” I would point out that the stakes over this distinction in educational policy are high. These policies, founded on the false equivalency that “(natural) language = (programming) language,” could result in reduced funding for secondary language programs and further chipping away at their already tenuous curricular footholds. Under this specious rhetoric of substitution, coding courses would be built on time, money, and students siphoned from traditional language programs. This is exactly against the spirit of the trivium. Grammar and logic are not mutually exclusive, but mutually beneficial. (Burns on Eidolon)

Another problem this lack of distinction might entail is, as Burns stresses, the potential loss of funding for language education, with argumentations along the lines of “learning programming and learning natural languages teach the same skill” which is absolutely not true. But in our tech-loving world today, I think there is a real danger of something like this happening in the future.

The term has clear roots in the the formal languages of mathematically minded logicians from Leibniz to Frege. Yet, in the earliest stages of what we would now call computer science, these instructions were referred to by a matrix of words such as calculus, system, assembly, scheme, plan, formula, and, sure enough, code. “Machine language” appears early, but widespread adoption of the word would take time. Certainly, by 1959, the development of COBOL, or Common Business-oriented Language by the Committee on Data Systems Languages (note the plural) suggests that this was the default term. The exact process of its popularization is difficult to trace. Noam Chomsky’s algorithmic “descriptions of language” clearly exerted influence, but it may also have been spurred on by Grace Hopper’s introduction of English keywords and syntax to computer programming as she sought to replace math-heavy commands. Hopper’s instincts were correct and coding has moved increasingly towards human-readable “languages.” ALGOLSNOBOLSQLTclHTML, and perhaps Perl— they all hide the victory of “language” in their acronymic ells, and it is this victory that has given policymakers license to exploit semantic slippage for their own curricular ends. (Burns on Eidolon)

Humanists’ special talent for living languages?

Another thing I’ve come to observe when teaching which is maybe a relief to Humanists trying to learn programming even though it’s a slow process for them. My friend the Noob always calls it ‘an adventure’. Which is a better way of putting it, I think. Learning something new is beautiful. Even when it hurts at times. So back to the argument:

Sometimes in my DH classes, I teach those brilliant programmers who are in their very early semesters and I’m awestruck. Until I hear them speak English that is. Then I’m awestruck too, but in a bad way. I often see this with people who went to Austrian HTL (Höhere Technische Lehranstalt). They leave this institution with an impressive knowledge in technology; if they were good students. So good, in fact, that I’m usually quite blown away as a self-taught programming Humanist.

But then I observe that the Humanist students who seemed quite untalented with programming are really good at English. And then I remember that learning a living language to a certain level of mastery just takes years. These are years they did not invest in learning how to program. But the programmer did. Yet they often aren’t as good with living language in general (punctuation, grammar, spelling, etc – let alone foreign languages). Many have difficulty expressing themselves in ways which serve to communicate with humans. Of course, there are exceptions. But the rule fits quite well for most. And this suggests to me, very strongly so, that programming and natural languages are in fact very different.

Also, another comforting thought for Humanists. Yes, I know it’s hard to acquire programming skills if you’ve never done anything of the like before you were 20 (or even older). And doing so beside your real work in the form of life-long learning. It’s just not the same thing as having all the time in the world to intensively learn a new skill at school. Learning completely new skills just gets more difficult with age. But you can learn new skills. Whereas it becomes less and less likely you’ll master a foreign (natural) language if you haven’t acquired one to a high level before you’re 20 where ‘language-learning window’ is still open. So this might be a consoling thought to end with 😉

So really, my point is that we should avoid subconsciously shifting our view of what ‘intelligence’ is to a completely digital and non-Humanist perspective. We should also avoid getting sucked into the idea that all programmers are geniuses or intellectually superior (thanks to popculture for that). Not at all to begrudge them the success but because #HumanitiesMatter too 😉 And also, if you’re feeling bad about yourself compared to a programmer, be sure to check if they still look as genius-y as they would like when you go check for certain flaws. So if you’re a Humanist and can’t program – don’t let people tell you you don’t have valuable skills.

I would be happy to hear your opinion on this matter,

until then,

best,

the Ninja

References

John Sonmez, The Complete Software Developer’s Career Guide, 2017.

The Ancient Case Against Programming “Languages” by Patrick J. Burns on Eidolon (Apr 24, 2017).

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I need a training progression for academia and programming

As some of you might know, I am currently a fellow, aka at my personal writing retreat at Wolfenbüttel. And I decided to combine this with some sort of a training camp for my bouldering progress because you do need to have some breaks from writing during the day anyway and I can’t always watch Bones or create CV templates. You might have been following some of my bouldering on epigrammetry, the blog, or epigrammetry, the Twitter.

 

Training progressions in sports

Also very few of you might know as well, I used to train a lot for long-distance running (10k) during my teens. So I know what training progressions are. I used to have detailled training plans, eating regimes, supplements to take and all that jazz. I stopped at some point because my immune system kept bullshitting me and as an ambitious person, I couldn’t take the idea of having to start from scratch after a half-year of being very sick and weak. I’d had it with having to arrange my whole life around my training. Yet the principles I’d learned over the course of the years, plus the high level of discipline required in those persuits, have helped me a lot during my early university studies.

 

Systematic progress needs training goals

Looking back now, I used to approach studying and my ‘university progress’ just like I would have had planned my training progression. And it worked. I was really productive, things were going well. For me, at the time, this consisted mostly of getting all the translation homework done, reading a lot of Latin and Greek (at least an hour every early morning before starting my day) and getting through all the classics. Because I was fucking motivated.

This might have been due to there being actual goals to be achieved daily which I could measure my progress on. Like the speed, and thus number of pages, I would get through during my early morning reading practice. Back then, by the way, I also used to combine physical exercise with mental workouts like I have taken up again for this summer’s ‘training camp’. It works quite well. I should probably continue with it back home.

 

How do you create a training progression for programming?

My problem is now: Over the years, I seem to have gotten out of the habit of approaching progress systematically. Or, well not exactly, but – let’s say – I follow academic learning goals with a lot less zeal ever since I got my degree. Which probably is the case for mostly everyone else. Because it’s quite a bit harder to find time and motivation for non-goal oriented learning after a hard day at work than when you had all the time in the world to study. I really envy my youger self for having all this time for learning. I love learning. But life-long learning isn’t exactly the same and doesn’t end after your degree, espeically not if you’re an early career scholar. Now I have a vague idea of some skills I want to improve in. But I am very good with training progressions and thus I know that the common advice ‘just program a lot’ or ‘do a private programming project’ just really is crap advice. Of course, it’s true. You just need a lot of practice. But there still are ways of approaching this effectively or ineffectively.

There are some good books out there which actually provide some learning progression. There is John Sonmez’s Software Dev Career Guide which is the single only thing close to a book providing a progression to systematically get better at programming. And, who would have thought, he is an athlete too. I always thought I was the only one who wanted a systematic training plan. But apparently, he felt that need, too. And for good reason. I have already complained many times about why people don’t approach learning like training and still expect to get reliable, constant results. With learning, this systematic training approach is called ‘curriculum’. In the post linked above, I mentioned that I thought online programming platforms were the answer.

 

Which tools or medium can actually provide curriculum?

At the moment, I am at the point where I have let those online trainings slip again, a long while ago already. As it has happened to me multiple times over the years. If I can deduce from experience, I am likely or restart eventually and go crazy at online programming workouts for a while, then drop it completely again. But what you really need is consistency and daily workout. Plus, I can’t just do the apps. I always have a lot of books to read as well, which is quite important to me so they can’t be neglected either. But then I often end up only spending half of the time I would want to spend, read the book or, if you want to call it that, finish my ‘reading time’ and get tired after that. Also, I should already be at work, so I skip the programing workout.

While something surely is better than nothing, I should probably focus more on the practial work if I want to make faster progress. But in programming, that’s different from bouldering. In bouldering, it’s easy to see which routes I am capable of doing or whether I nailed a particular route. Or count how many pushups and pullups I can do (not enough, I have to admit). So I can measure progress easily. But with programming, this just isn’t the case. And in addition to that, for bouldering, there are tons of youtube gurus with mulitple videos each on how to get over plateaus and make progress, what you can work on, etc.

 

Willpower alone isn’t enough

For programming, most of the advice isn’t too good in my opinion because it’s often too generic (“get a project”). Bouldering tips are concrete like “Perfect your flagging technique”. It’s easy to look up how you do that. It’s easy to notice when you’ve got it, physical feedback makes sure of that. So I decided I’ll have to look at my programming workouts the way I approach my pushups for now (they need to get done no matter what and no whining around). But it’s not really a solution to the problem to rely on willpower alone. Willpower alone will ultimately fail once you get stressed or anything comes up. And when that happens, I have a really hard time getting back into the routine. Which I hate. And then I hate myself for not managing to and then the vicious circle goes on. It’s really annoying.

 

We need curriculum for systematic and swift progress

Of course, even with a good curriculum or a training plan, there will still be plateaus. You will still get stuck. But a good curriculum can help you over that last edge of the boulder. It can help you re-gather yourself after a failure or after you’ve let it all slack for a few weeks.

So this subject also makes me think with regard to this blog, it’s all the more important that curriculum gets developped for learning advanced LaTeX, so a willing user can make rapid progress. Rapid progress is good. It keeps you motivated. Plateaus are really dangerous because the can make you lose motivation and give on up the goal alltogether. So let’s find ways of measuring progress and collecting tips of what you can do to actively and systematically improve if you’re willing to.

Step one probably is to get the people to shut up who sneer at systematic approaches like this one. “Learning to program just doesn’t work this way”, they repeat time and time again. Yet I think this is not true. Getting better at programming is like learning any other skill. There is a systematic approach to it and when we have a systematic progression and training goals, we can figure out the steps we need to take.

That was it for now,

best,

the Ninja

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The Simple Academic Resumé. A play in 3 acts

Dear all,

you might already know the Simple Academic Resumé/CV from Twitter or GitHub. It is available as a template on Overleaf now, so I wanted to take this occasion to formally introduce it to you again. It also has a new third style which you might not be familiar with yet.

simple-acad-cv
This new version is quite colourful with the rules. Or at least it can be. You can just choose black or grey as a colour. With all of this colour, it probably doesn’t really qualify as ‘academic’ anymore. 😉 Try it out here on Overleaf.

I don’t know if if love the name. Thinking back now, I might have called it something else but since has already been out there on Github quite a while, I didn’t want to change it anymore. My second thoughts now stem from the fact that I would like to make a template which really deserves the title ‘academic’. This one was named academic only because I published it the day after the Hipster CV and  somebody on Twitter noted that they would think it very bad style to use such a template in a academic context. That’s why I got inspired to make a more simple template and called this one ‘academic’. But there’s nothing especially academic about it really. 😉

Simple_Academic_Resume
The Simple Academic without picture. Try the template on Overleaf!

Aaaand the last available option:

Simple_Academic_Resume__with_picture
The Simple Academic with image. Try it out directly here on Overleaf.

Well, I hope you enjoy it anyway.

Best,

the Ninja

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Don’t call it a database!

When I started this blog, one of my promises and goals, apart from LaTeX-Ninja’ing, was to demystify the Digital Humanities for non-DH people. For a long time I have watched and I think one of the big mysteries of the DH still persists in Normal Humanists’ heads and thus, really needs demystifying. You might have guessed it, I want to explain why DH people will cringe if you call digital resources ‘databases’ which are not, technically speaking, databases.

Is it ok to call any digital resource / corpus a ‘database’?

We know, that’s what you tend to call a digital corpus. But in most cases it’s not correct, it’s a pars pro toto. A database is just one possible technical implementation, but the term is used more broadly for any ‘digital base of data’. By laypeople, at least. A pars pro toto stylistic device is a Humanities’ thing, right? You do get stilistic devices. So you can also understand why you shouldn’t use imprecise terminology. You don’t like it when people misuse your fields’ terminology either and probably make quite a religion about it.

If you want to work with the DH, you need to understand their terminology and respect it by using it correctly. Even though it might initially feel unintuitive to you. Believe me, you will adapt quickly if you give it a try.

I’ve caught myself so many times now, educating my Normal Humanist friends about digital resources and why my (DH) colleagues won’t take you, as a Humanist, very seriously if the word “database” slips out your mouth at inappropriate moments. It’s kind of like the Tourette’s of NH-moving-in-a-DH-world. Which probably is not a politically correct analogy. No offense to people who actually have Tourette’s, I don’t want to devalue or disrespect your struggle in any way! It’s just analogical in the way of spluttering out inappropriate words at inappropriate moments.

Everybody has their cringe-prone terminology item, right?

To be honest, I am not sure how strict the English speaking DH world is in this, but I can guarantee you that this distinction is very valid concerning the German language use of “Datenbank”. When a quick web search yielded this result, I wasn’t sure anymore if it’s actually a thing in English too. Digital Humanities at King’s College define a database as follows:

Database is the term we use for any large collection of online material.

( https://libguides.kcl.ac.uk/dighum/dighumdbase )

This, however, is exactly the way I don’t suggest you use this term. I am aware that this is the association linked with it in many people’s minds. But hey, you are Humanists. You do have a sense for the intricacies of terminologies, right? I, for one, really hate it when people use the wrong gender on the term corpus (in German: neutral (!) for a collection of documents, so always neutral, unless you mean an actual body like that of a musical instrument). You probably have a thing like that, too, where you get furious at laypeople saying it wrong, don’t you? Well, the DH equivalent of this thing is the misuse of the term database.

Using terminology correctly is a sign of respect towards the DH community. It shows you respect us as researchers and don’t think of us as the ‘idiot who does the tech stuff’

Well, to be exact, it’s not even a misuse. You sure can use the term database in this way and it’s not, strictly speaking, completely incorrect. It’s just misleading, and – most importantly as the subject of this post – it is a strong pointer to the fact that you are not very tech-savvy and either unaware or else disrespectful of digital terminology. It will be seen as either a lack of respect and esteem towards the digital field or, I don’t know which is worse, a lack of competence in general. You would deem it impolite, too, and probably take it as a sign of general incompetence or lack of intellecutal ability/openness  if a DH person came along and persistently misused your terminology, right?

Edit/addition 2019/06/04: I think this issue is less about whether it is technically or theoretically correct to use a term like this or like that. It’s a question of being ‘politically correct’ and of not hurting people’s feelings. To show the point on an extreme example (which is maybe exaggerated applied to databases but illustrates the point): you could theoretically argue that the term ‘nigger’ has been used historically to mean ‘person of color’, ergo it would – terminologically speaking – not be incorrect to use it, right? Wrong. In this case, it’s obvious (to everyone, hopefully) that it would be extremely rude and not ok to call a person of color a ‘nigger’ nowadays. Nobody would be confused if people’s reaction to this was to feel insulted because the above explanation does not take connotations into account.

Like you could say that before the advent of the DH, it maybe wasn’t a big deal to throw around the term ‘database’ to mean any digital ‘base of data’, but since the DH is starting to be established as a discipline and not only as a tool like it might have been in the beginning, things have changed. DH people sometimes feel like their competencies are not taken seriously because their part of the job is seen as the ‘handiwork’ whereas the non-DH input data is the actual research. I think that this latent inferiority complex, or maybe rather some sort of struggle for recognition, is the reason non-precise use of DH-related terminology is sometimes taken bitterly.

So ultimately, it’s not about being right or wrong. It’s about being respectful and not hurting other people’s feelings. Also, non-DH people insisting on using the term in a non-DH way while simultaneously wanting to participate in a DH project will cause a clash of terminology. It might be ok for a non-DH person to use the term like this, but DH people are kind of bound to use the term in a strictly technical way or else they might be seen as incompetent of their own field. In this case, I think the non-DH person should give in because even when they will not be judged by their use of DH-specific terminology, a DH person will. You don’t want your imprecise language to reflect negatively on your cooperation partners.

Since the initial publication of the post, I received the feedback that some people with technical backgrounds are quite open to non-technical uses of the term ‘database’. But from my own experience of the DH overall, I feel this is not necessarily representative. And only because people will accept that it is theoretically valid to use the term to one’s own judgement, that doesn’t mean people will condone it in practice.

If you want collaboration, start actually collaborating by learning about DH terminology

Especially if you are trying to get a collaboration DH or label DH project, I suggest you prune your language a little bit here. After all, DH people usually have lots of people queueing to get a project with them. They will tend to take the ones interesting for them (in terms of subject) and/or those where the applicants seem nice. And it is deemed base politness to research your collaboration partners’ field so you don’t draw a complete blank. You want your partners to be understanding and reasonably well-educated on the baseline of your field too, right? And you probably catch yourself sometimes, secretly saying to yourself in indignation or disbelief ‘How can any academic not know that?! This is completely basic!’

Well, it happens to DH people, too. Often concerning so-called ‘databases’ which are not, in fact, databases. If you persistently use the term wrong, it’s seen as lack for trying or plain incompetence. Don’t be rude. Now you are aware of the problem, you have no excuse to continue saying it wrong.

How to know if it’s ok to call it a database?

Two questions to ask to get a feel for whether what you mean might actually be a database:

  1. Would it make sense to represent this data in an (Excel) spreadsheet? Then it is likely someone chose a database format to represent it digitally.
  2. Are there any other fitting means to represent it? Only because it outwardly looks like it stores spreadsheet-formatted data, this doesn’t mean it’s they way data is stored “behind the scenes”.
  3. In case of any doubt whatsoever, just refrain from calling it database. Just say ‘digital resource’, ‘digital corpus’ or basically anything else which seems half appropriate. Anything else is way less stigmatized and cringe-worthy than the misuse of ‘database’.
  4. So to be on the safe side: Just don’t call it a database unless you’re sure it is one (technically speaking). When not 100% sure, just term it a digital resource or digital data collection. I know you just mean a ‘digital base of data’. But please respect that the wide category ‘digital base of data’ doesn’t mean the same thing as the narrow term of ‘database’ in a technical field.

Just a little thought – hope this helps!

Best,

the Ninja

PS: Can someone tell me whether you think it is valid to inform people they should not use the term database or would it be ok with you when they use the term in a non-technical way? I only know that people around me react quite aggressively when you do and will think you’re a technical layperson, thus not trust you much once you did. You’d basically be ‘disqualified’ after that unless you really have some very interesting other assets or extremely good grant acquisition records or splendid networking connection value.

 

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Your 24 hours. Time management or How to get to know yourself while organizing your life. Part II

Today, I am yet again happy to present the second part of the latest LaTeX Noob guest post:

 

Last time, I told you about four important steps to organizing your life. They were:

  1. Know your priorities.
  2. Learn to say “no”.
  3. Leave your comfort zone.
  4. Never back down.

If you want to re-read the last post, you can find it here!

So, time management.

You will need a calendar, let’s start with that. Take your phone, open your Google calendar. Start. It is actually that easy. You have to know the most important basics. When do I work, what are my main working hours? Do I like a silent or slightly more lively environment for my work? Am I a morning person or a night owl? When will I need a break, when do I want to go to sleep?

When am I meeting my friends, when do I spend time with my partner or my family? What do I do for relaxing? How often? Exercise? Any activities? When and where?

What is there to do on household chores (you know, cooking, cleaning, gardening etc.) and when are they due?

Just write those things down. Think about it. It is creepy at first sight, I know, but hey…

Labyrinth-Girl

I am a morning person, I like to start early with my work.

I love good instrumental or orchestral music during work. I like other people around me while I work, because of the swift “office-noise”.

For relaxing, I like reading, listening to music, going climbing, watching TV, taking long walks, photography, writing, people-stuff (friends and family).

Basic week:

  • 4 work days, Monday to Thursday = 30 hours of work
  • 1 “thesis day” (also called somehow home-office)
  • 1 university course to teach and prepare
  • 4 university courses to attend and prepare
  • one evening to go climbing
  • (at least) one evening to have dinner with my partner

An example week

I will give you my five days of my working week in my calendar now, just as an example and to show you how I work on my organization and how I try to plan my days. You may have got it until now – it is all about your own rhythm: find it, then stick to it.

Monday

7:00 start work

15:00 short coffee break with friends

17:00 back home, dinner

18:15 climbing (1.5 to 2 h)

  • hair day, bathroom cleaning

  • prepare courses

22:00 bedtime

Tuesday

7:00 start work

10:00 Coffee break with colleagues

18:00 back home, dinner

  • washing clothes

  • prepare courses

  • TV/Dinnertime with my partner

22:00 bedtime

Wednesday

7:00 start work

10:00 teach my university class

12:00 lunch with friends

15:15 university course 1

18:45 university course 2

20:30 dinner with colleagues

22:00 back home

23:00 bedtime

Thursday

7:00 start work

13:00 end work

13:30 university course 3

15:00 prepare next course (learning a new language for work)

17:00 university course 4

19:00 back home

22:00 bedtime

Friday

7:00 morning routine

  • Thesis Day

  • kitchen cleaning

  • washing clothes

  • shopping supplies

14:00 lunch with my partner

15:00 beginning of my pre-weekend

Weekend

Normally spend with family and/or friends and /or partner – and sometimes spent with reading texts or papers connected to my research field

Conclusion

So I actually do have some kind of private life, but I have to organize it in a very strict way and I have to be very strict with myself sometimes. I am a morning person and I am in the possession of a “daylight alarm clock” – you know, it starts with deep red light approximately one hour before your actual alarm time and continues getting brighter like the sun rising, so your body can wake up before you actively open your eyes and wake up in your head. It works! At least, for me.

I need my bedtime set earlier now, so around 10 pm I am really grateful for a warm and cozy bed and sleep. I enjoy resting in my bed on the weekend, this is a fact, but it is like a reward I promise to myself.

I am still meeting my friends and I have still a lot of other things to do in my life, things which I enjoy and which are keeping me relaxed and sane.

It’s worth the hard work. You just have to start.