When you start your career as a postgraduate student, it is normal that you start collecting your scientific results in a slightly unorganized way. However as time proceeds, some basic rules are needed to keep track of your work. Every scientist has to develop his own systems for keeping organized. Ideally, a minimal set of rules should be used consistently by group members, including staff members and students, to facilitate data exchange. Perhaps some aspects appear trivial, but in my contact with undergraduate and postgraduate students I have seen many shocking examples of (lack of) data management. Here I give an example of how to organize data using a Windows operating system, based on my own set of rules. Again it should be emphasized that this is just one example of an organizational structure, which is aimed at avoiding some of the most common mistakes.

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Over the last 6 months I have been checking regularly the journals to see if anyone has published something in the direction of our research project. This morning, when I was just going online to check some references, the article hit me right between the eyes. There it was, my idea, the result looking exactly as I had expected it to be. Only the names of the authors are different; a leading US research group has apparently pursued the same concept and has already obtained the result we have been looking for during the last months.

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On my desk, right in front of the computer screen, lies a pile of paper. This pile gives me headaches, keeps me awake at night, and is a source of frustration on sunny weekends. It is the pile of unfinished manuscripts, gathered and carried along from earlier positions as a postdoc. Every paper has a story attached to it. Some papers are only in their first version, hardly more than a collection of raw data. Others have seen many revisions, have passed the eyes of multiple co-authors, and have got stuck just before submission, because something just is not quite right. There are papers of PhD students, co-workers, and of myself as leading author. Some contain data taken two years ago.

I am wondering how others are dealing with their unpublished data. Do you have a drawer full of brilliant work yet to be published? Or are you completely up to date with your results? For some people, it may be a reason for boasting: look at how many data I still have on the shelf! For a starting academic, unpublished data can be a life saver in times that you are starting a new lab and you need results to cover the gaps in your publication record. However, the pile also represents months of painstaking experiments, data analysis, and theory, lying there going to waste and most importantly – not being cited.

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