Tag: read

How to Read Scientific Papers

How to Read Scientific Papers

Cover image via wikihow.com/Read-a-Scientific-Paper

Reddit is a treasure trove of random stuff. However, every now and then, in the better groups, quite valuable topics pop up. Here’s one I came across on r/statistics:

Particularly the advice by grandzooby seemed worth a like, and he linked to several useful resources which I’ve summarized for you below.

An 11-step guide to reading a paper

Jennifer Raff — assistant professor at the University of Kansas — wrote this 3-page guide on how to read papers. It elaborates on 11 main pieces of advice for reading academic papers:

  1. Begin by reading the introduction, skip the abstract.
  2. Identify the general problem: “What problem is this research field trying to solve?”
  3. Try to uncover the reason and need for this specific study.
  4. Identify the specific problem: “What problems is this paper trying to solve?”
  5. Identify what the researchers are going to do to solve that problem
  6. Read & identify the methods: draw the studies in diagrams
  7. Read & identify the results: write down the main findings
  8. Determine whether the results solve the specific problem
  9. Read the conclusions and determine whether you agree
  10. Read the abstract
  11. Find out what others say about this paper

Jennifer also dedicated a more elaborate blog post to the matter (to which u/grandzooby refers).

4-step Infographic

Natalia Rodriguez made a beautiful infographic with some general advice for Elsevier:

Via https://www.elsevier.com/connect/infographic-how-to-read-a-scientific-paper

How to take notes while reading

Mary Purugganan and Jan Hewitt of Rice University propose slightly different steps for reading academic papers. Though they seem more general pointers to keep in mind to me:

  1. Skim the article and identify its structure
  2. Distinguish its main points
  3. Generate questions before and during reading
  4. Draw inferences while reading
  5. Take notes while reading

Regarding the note taking Mary and Jan propose the following template which may proof useful:

  • Citation:
  • URL:
  • Keywords:
  • General subject:
  • Specific subject:
  • Hypotheses:
  • Methodology:
  • Results:
  • Key points:
  • Context (in the broader field/your work):
  • Significance (to the field/your work):
  • Important figures/tables (description/page numbers):
  • References for further reading:
  • Other comments:

Scholars sharing their experiences

Science Magazine dedicated a long read to how to seriously read scientific papers, in which they asked multiple scholars to share their experiences and tips.

Anatomy of a scientific paper

This 13-page guide by the American Society of Plant Biologists was recommended by some, but I personally don’t find it as useful as the other advices here. Nevertheless, for the laymen, it does include a nice visualization of the anatomy of scientific papers:

Via https://aspb.org/wp-content/uploads/2016/04/HowtoReadScientificPaper.pdf

Learning How to Learn

One reddit user recommend this Coursera course, Learning How to Learn: Powerful mental tools to help you master tough subjects. It’s free, and can be taken in English, but also Portuguese, Spanish, or Chinese.

This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. We’ll learn about the how the brain uses two very different learning modes and how it encapsulates (“chunks”) information. We’ll also cover illusions of learning, memory techniques, dealing with procrastination, and best practices shown by research to be most effective in helping you master tough subjects.

https://www.coursera.org/learn/learning-how-to-learn

One year of paulvanderlaken.com

One year ago, I registered the domain paulvanderlaken.com with three reasons in mind: (1) I wanted an online environment to store and showcase my pet projects, (2) to share and promote some of the great blogs and research others had been writing, and (3) to show others what I was doing on my path to “data science“. The year has been just amazing. I could not have imagined the amount of positive sentiment I received from friends, family, acquaintances, and old classmates. But, most of all, the nice reactions from complete strangers across the globe! Thank you all so much for the positive response.

To my surprise, some of my stuff actually got read!

Some random stats:

In one year, I wrote 103 blogs which got over 42,000 views by nearly 30,000 visitors. 97.5% of these views occurred in the last six months. Most referrals came via Google (45%), reddit (18%), LinkedIn (8%), Facebook (8%), and Twitter (4%), and my blogs were shared a total of 241 times. Now, 51 people follow my blog, which is best viewed on Tuesdays (31%) and around 15:00h CET (6%).

views.png
My views between January 2017 and 2018, made with ggplot2 in R.

Although my personal learning is still the main reason I maintain this blog, I am very glad people seem to enjoy tagging along. Hopefully, I can continue to discover and write about data (analysis) during the coming 12 months. For now, I’d want to thank my readers for their continued interest and, in particular, my girlfriend for coping with the numerous evenings and weekend I have wasted on my pet projects. Nonetheless, it was definitely worth the effort!

Hope to see you again soon,

Paul