Writing an Abstract

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Writing is an important part of everybody’s scientific work since we all like to share our findings and discoveries. I have taken several writing courses over the years. My approach to writing has thus been by these courses, plus some of my own experiences. Is it great now? Surely not, but better than it used to be! No approach works for everybody. However, I hope that you might find some interesting things in my opinion on how to write an abstract.

The abstract

The abstract of a paper is the first exposure a reader usually has with the manuscript. It often decides if the reader keeps on reading or simply gives up. The abstract thus should convey a very brief summary of the paper and point out the major findings.


In my opinionk, an ideal abstract structure is as following:

ForewordContextOptional: Show the importance, discuss the missing part of the puzzle
NeedWhy is what we do important
TasksWhat was undertaken in order to fulfill the described need
SummaryFindingsWhat did we find, what are the major takeaways
ConclusionWhat are the conclusions of this work
PerspectiveOptional: Beyond this work, what are the limitations, potential future work

The first and last parts (context and perspective) will be very dependent on the topic you are writing about and might not be necessary.

Who is the abstract for?

The abstract is literally for everybody! It is what people read, expert might go on to read the full paper, but most people are happy with the abstract. Therefore, it is important that you bring your message across.


  • The course and book I was referring to that most of this is described in can be found here.
  • Another fantastic resource is the book “How to Write and Publish a Scientific Paper”. All parts are highly digestable and can be read very selectively. Plus, there are many more things in there on how to write letters of recommendations, applications, etc.
Reto Trappitsch
Reto Trappitsch

Experimental astrophysicist / cosmochemist with ties and interest in code development and numerical modeling.