it is impossible for a white person to turn down the opportunity to proofread

two-trick pony, somewhat: focal point in middle of square, and I think that lovely palette is due to high contrast and very slight overexposure

I have been intending to write this essay for months. Why am I finally doing it? Because I finally found some uncommitted time? Wrong. I have papers to grade, textbook orders to fill out, an NSF proposal to referee, dissertation drafts to read. I am working on this essay as a way of not doing all of those things. This is the essence of what I call structured procrastination, an amazing strategy I have discovered that converts procrastinators into effective human beings, respected and admired for all that they can accomplish and the good use they make of time. All procrastinators put off things they have to do. Structured procrastination is the art of making this bad trait work for you. The key idea is that procrastinating does not mean doing absolutely nothing. Procrastinators seldom do absolutely nothing; they do marginally useful things, like gardening or sharpening pencils or making a diagram of how they will reorganize their files when they get around to it. Why does the procrastinator do these things? Because they are a way of not doing something more important. If all the procrastinator had left to do was to sharpen some pencils, no force on earth could get him do it. However, the procrastinator can be motivated to do difficult, timely and important tasks, as long as these tasks are a way of not doing something more important.

Anyone who archives his or her data also would like them to be found, recognized and still usable in the future. That is not a matter of course with electronic data. After all, hardware and software are changing all the time. Making data future-proof can be accomplished by ensuring that data sets and metadata meet certain guidelines. In consultation with large data producers and managers, DANS laid down what those guidelines need to be in its 'Datakeurmerk', which will continue to be developed further. The quality guidelines of this seal of approval for data are intended to ensure that in the future, research data can still be processed in a high-quality and reliable manner, without this entailing new thresholds, regulations or high costs. They may be of interest to research institutions, to organizations that archive data, and to users of those data. The document that lays down the quality guidelines of the 'Datakeurmerk', can be downloaded here.