Telling stories for science


Humans are great story tellers. Always have been and always will be. No matter what happens. Image:

Humans are story tellers. Some might say that is what separates us from other animals. Well, that and IPods. Particularly since even insects have language and it seems that everyone is using tools. Homo habilis is not as impressive as Homo fictus, the story tellers. Unfortunately this message hasn’t gotten through to scientists.

We all have a story, so writers like to tell us and then don’t give us any ideas of how to go about extracting that story. At some point during science education – I blame the PhD – we scientists lose the ability to tell stories. Conversely we become very adept at stringing facts together and critically analysing details.

But stringing together a story is a complete mystery. This is very problematic when it comes to trying to communicate scientific results to a non-scientific audience. I can spot a spelling mistake or inappropriate apostrophe use a mile off, but figuring out the correct sequence of words to turn an idea into a story is a whole different challenge. And it’s the story that most people will remember, not the details.

Practicing is the best way to get better at anything and this includes telling stories. Just telling friends about something that happened on the weekend is a good start – and, of course, this is yet another reason to engage in communal coffee times.

Even when writing scientific papers, having a story in mind helps get the message across. This simple idea makes the paper flow more logically and is easier to follow than the randomly- strewn-together series of facts that is the alternative.

Knowing what the key message of the paper also makes writing the paper easier. Particularly in nominating what is important to include and needs to be dealt with before publication and what can be reallocated to that wonderful section of ‘future research’. This helps keep on topic and to the point and that’s also good for the reader.

Stories are great for science, both for writing articles for other specialists and for engaging non-specialists. We just need to remember how to tell them.

On the brink of greatness

Colombia Nobel Five Things

Research papers can lead to Nobel Prizes, but usually they just lead to more research. Image:   

One of the key things l love about my job as a research scientist is data. Months of slog work in the lab produces great swathes of data and finally getting a chance to process it and understand what is happening is pure happiness. Particularly when combined with varying concentrations of coffee and chocolate.

This is a particular characteristic of all research scientists, I’m sure. (And yes, I am aware of the irony of proclaiming a love of data and then ignoring any such data to make sweeping generalisations about a large portion of the population. But it’s for the good of making me feel more normal so I’m willing to go with it.)

Processing data is the point at which we can see if all our efforts and hypotheses have made any inroads into the unknown. If they have, either by proving or disproving a hypothesis, it is triumphant.

The process involves turning spreadsheets into works of art, although admittedly a peculiar brand of art. I enjoy turning reams of numbers in to very pretty graphs and, ideally, correlations and trend lines. Constructing those is rewarding on a level that is second only to writing the paper.

A research project isn’t finished until it is published in a peer-reviewed journal. At least, that’s my opinion. I know many scientists who disagree with me on this one. For them, the true joy lies in discovering something new and broadening their knowledge but getting the word out there to the broader communities of scientists and non-scientists is nothing but a chore.

But publications are the bread and butter of research and while the peer-reviewed process might be flawed, it is still the best system for ensuring the majority of science is carried out in a reproducible manner and that the conclusions are matched by the data.

Now, after many, many months of producing data, I have finally had a chance to sit down and process it. And it worked! I have evidence that supports my hypothesis and I have made tiny inroads in hitherto unknown regions of knowledge.

Now all I have to do is write the paper, get the co-authors (my managers and other people who helped produce the data) to read it, get them to agree with how it should be written, get the reviewers to agree that the work is of sufficient quality, incorporating all possible controls and blanks, and voila! Another science paper published. Greatness will be mine! I might just go call the Nobel Prize committee and give them a heads up. I’m sure they’ll want to know.

In reality, even without a Nobel Prize, it’s being able to shine a torch onto new knowledge after months of slog work in the lab is what makes all the effort worthwhile.

Post PhD perks


Attending conferences can be hard work but always worth the effort. Image:


The best perks we get as researchers are not actually pens that are shaped like micropipettes. Nor is it syringe-shaped highlighters, sticky-note paper, or any of the other pretty awesome free stuff that I’ve scored from various lab equipment suppliers over the years. It is the chance to attend international conferences.

This notion was brought to my attention very early in my honours degree. If I do really good work, not only might I save the world and get a Nobel Prize but I would also be PAID to present my work overseas somewhere. And, better than that, people might actually want to hear what I have to say and I could travel around lecturing to various universities.

That was the dream. That dream lead me to a PhD and, eventually, to reality. I am becoming increasingly suspicious that my research may not directly save the world and, unless serendipity steps up sometime, a Nobel Prize may not be heading my way anytime soon. But I might contact the committee again anyway, just in case they lost my number.


The micropipette pen is prized among lab-supplier free stuff. Image: Plaid ninja


One thing reality has shown me is that I do have is the real chance to present at a conference. At this time of year many of us start to peruse the conference alert websites and prepare abstracts for faraway places with relevant topics.

Conferences are where ideas are shared and networks and collaborations are formed. It’s also just cool to get paid to travel regardless of the reams of paperwork that inevitably ensues.

And in meeting other researchers, there is always the possibility that a new idea will spark a stream of thought that leads to a Nobel prize-winning breakthrough, or that a new collaboration will lead to a discovery that will ultimately lead to the world being saved. Hope springs eternal.

At the very least, if all else fails, attending the conference will invariably bring me more lab-supplier-stamped free stuff. And it’s almost worth it just for that.

Making abstracts less abstract

Abstracts are Mini-Me research papers

The abstract is the most important part of any research paper. Ok, yes, the data is also important. As is the experimental design. And the interpretation of results. And conclusions. But in terms of people reading, understanding and citing your research, it is the abstract that needs to be first rate. This is worth spending time on because, in reality, it will be the only part of the paper that most people ever read.

The abstract is meant to be a Mini-Me version of the entire paper. The story of the data should be presented there in all its 150 word glory, enticing readers to delve into the 10,000 word masterpiece that is the full paper. This is certainly not an easy thing to do and I do not at all claim to be a master of the art. Many of my papers, particularly back in the early days, have glossed of the abstract as an annoying and unnecessary add-on to the paper. It’s only now that I have read many hundreds of research papers that I see the value of the abstract.

Here are some points to consider for writing a clear and concise abstract.

What’s the problem?

We as readers need to know why we should care about the data. This is like your 15-second elevator pitch for the project. An opening sentence that states what you’re working on, why it’s important, and what problem this project tried to solve.

What strategy was used to tackle the problem?

The experimental design is critical to the project. Anything that happens downstream of that can be rendered irrelevant if there are not sufficient controls or sample replicates. This is also where peer-reviewers will be most critical and a great deal of details should be included in the paper. The paper, not the abstract. The abstract only needs a sentence naming the methods used and the samples analysed.

What happened?

Really make the findings and novelty of the work stand out. If the title of the paper was “Effect of something on something else”, include that effect in the results. Did it increase the concentration of something? Decrease it? Cause a side reaction? Readers probably don’t already know what effect was expected.

Draw a conclusion

This is the part that is infuriatingly-often excluded from abstracts and yet this is the key to making people understand your data. What do your results mean in the context of the original problem? A concluding statement goes a long way to generating citations. The conclusion also makes for a strong title. Consider something like “A causes B” rather than “the effect of A on B”. Much catchier and again helps readers understand your findings.

The best test of the abstract is to get someone outside the group to read it and tell you what it’s about. It’s amazing how something that makes so much sense when you’re so close to the data can make absolutely no sense to someone not too far removed. All this may seem so unnecessary when the great big paper is finally written, but it is certainly worth the effort.

Writing a new chapter in science. Literally

Books. Like journal articles but heavier

Why do researchers write book chapters? Cutting edge science is clearly in the journal articles and this is always the best place to showcase research. The next best thing is to attend conferences where we can point out our latest research and hope people will find our paper. And then cite our paper.

Yet we spend a great deal of time compiling book chapters whenever the opportunity arises.

The problem with books is that they sit in a library. At my work, that means going all the way down one flight of stairs. I’d then need to carry the book all the way back upstairs. The only real upside is that I’m sure that counts towards a gym workout.

Online journal articles are far easier and more readily available. They are the most current, cutting edge science. In so far as is possible after the months of redrafting.

I’ve heard it said that the amount of effort spent in writing and re-drafting peer-reviewed scientific papers is so great that every ten papers published equates to a writing a novel. Such a great analogy. I think I’m onto about my third book by now.

With journal articles always as the go-to place for the latest research, books may be considered passé. So why do we bother to write book chapters?

Mostly it is because there is something more permanent about contributing a chapter in a book.

The hope that it will make a longer lasting impression than the thousands of journal articles published each year. That someone new to a topic will pick up the book and read the chapter and learn the essential elements required to understand the new papers that are published in a particular field. That the tangible pages – real pages – will hold the knowledge that will resonate through the ages.

And it’s just cool.

Bringing together ancient foes for the benefit of humanity

Uniting the scientific disciplines is almost like uniting ancient enemies

Scientific disciplines have been increasingly segregated for 300 years. This works brilliantly to achieve a deeper understanding of the world around us but it’s less helpful for solving the problems of the world. Collaborations are now essential for moving science forward but how easy will it be to bridge the yawning chasms between disciplines?

Years of study still focuses students in a particular discipline. This is still essential for ground-breaking research in one area and yet the research jobs of the future will have to include more broadly skilled scientists.

The main problem is language. Limited cross-discipline association for centuries has created an almost Darwin-like speciation of narrow-skilled scientists who can scarcely communicate with other scientists.

This is useful for nerd jokes. The funniest jokes are those that you know there are people who just won’t get it.

Pure genius

It is still a mystery as to why people think there is some sort of overriding scientific jargon when the scientists themselves can’t speak to each other. The divide is still evident in my lab with limited associations between chemists and biologists.

Some jokes never get old

On a good day, a synthetic chemist may speak in a similar manner to a natural products chemist and yet these organic chemists will not communicate with an inorganic chemist. Unless the inorganic chemist is surrounded by a cluster of microbiologists speaking in their tongue.

With such deep divisions between disciplines the idea of throwing money at a multi-disciplinary collaboration and expecting outcomes at the same pace as single discipline projects is optimistic. Yet it can be achieved.

Firstly, nothing brings ancient foes together like a common enemy. And, like so much of science, an unanswered communal problem is the best way to motivate the different disciplines to unite.

Secondly, science degrees need to place more emphasis on using a common tongue throughout science. Communicating complex ideas in a simple form is the future of science and will help bridge the great divides between disciplines, and even between scientists and other professions.

With a common enemy and effective communication, the new and improved armies of science can march forth for good of the world and achieve what no one has achieved before. I think there could be a movie about that.

Tips for surviving the peer review

The peer review can be one of the most gruelling processes in science. Months of writing, redrafting, coercing your co-authors to actually read the manuscript and then getting them to actually agree on each other’s changes, before finally, somewhat anticlimactically, submitting it to the journal.

After all that you get some unappreciative reviewer slamming your work from behind a veil of anonymity. But this objective criticism is just what science needs. Here are some tips to make the process go a bit more smoothly.

  1. It’s nothing personal

I got my first masterpiece back from the reviewers and it was destroyed like a 5th grade teacher would mark the bad student’s paper. It was demoralizing. I was convinced the reviewers hated me and wanted to see me fail.

But on a re-read I realised that their comments were fair enough. I needed to add a lot more details for a reader to get why I had used those methods. Some mistakes were just an oversight and were impossible to see when I was in the depths of the manuscript re-drafting.

Look upon the peer review as a great opportunity for objective error-spotting. I’d prefer to see these errors picked up in the review stage than in the published paper.

  1. Reviewers are not always right

Early in my publication career I would always believe everything the reviewer said. Everything. They were all-knowing oracles and I was a mere PhD student. If they said something was wrong it was my comparatively inferior knowledge of the literature that made it so.

Of course, more often than not, they were right. But not always. PhD students also know all the latest literature. It’s important to stand by your knowledge. Reviewers are only human after all.

  1. Reviewers are not always wrong

Researchers are great at details and that makes us awesome at flagging errors in someone else’s work. Not necessarily so great at spotting mistakes in our own work.

Before going down the rebuttal road of “Please refer to ‘Thermodynamics for Beginners’ to explain why we did it that way” or “Actually we already explained that in the introduction, Table 2 and half of the discussion”, have another look over the manuscript.

That screamingly obvious point that dominated the discussion may just need to be reworded to explain the point more clearly. Particularly if the journal of interest is multidisciplinary.

One of the great advantages of the peer-review is getting the input of the journal readership before publication.

  1. We’re in this together

Reviewers are donating their time for the support of science. Their opinions are invaluable for making the conclusions hole-proof. Likewise, the researchers submitting the paper may have just missed something in the document that gives the required clarity.  Mutual respect is what makes the peer-review process much less arduous.

There may be many faults with the peer-review system. But it’s still the best process for keeping science honest.

The art of publishing ‘Stuff That Doesn’t Work’

Sneeze-plot correlations are important too

Sneeze-plot correlations are important too

What do you do when your plotted data looks more like a sneeze-splatter than a straight line? Publish it anyway! The current dearth of Stuff That Doesn’t Work in the scientific literature dooms researchers to repeatedly try and fail over and over again. It doesn’t have to be this way. Publishing null results is possible. It just takes a bit of creativity.

The scientific literature is full of papers with the same format: “Based on the current understanding of this topic, we formed a hypothesis, tested it and it worked”.

Anyone deviating from this formula would be shot down by the peer review process. This leaves many a researcher abandoning reams of data just because the magical statistics program didn’t find the expected correlation.

There is nothing wrong with burying a sentence or two in another, related, paper that says “by the way, tried this and it didn’t work”. It has bought me great joy when I’ve happened upon these little gems of knowledge so I am fully supportive of this strategy.

And yet it can be gut-wrenching that, after months of data collection and interpretation, your whole project is condensed into a single sentence just because A did not lead to B after all.

Things not behaving as expected yield amazingly useful data and as such can and should be published as a stand-alone paper. What these sorts of results need is re-wording the story that the data actually tells.

Firstly revisit the knowledge gained from your experiments. Why have the data not produced the expected result? Maybe current knowledge is based only on model systems and your results are from complex real-world samples. Or perhaps you used a new and improved technique that shows something in more detail than has been previously possible.

Then, with that story in mind, it is easy to alter the wording of the project title to give it a more positive spin. So “Does A cause B?” where the response is “Actually no. It doesn’t.” becomes “Investigation of real-world samples using state-of-the-art technology.”

Writing these sorts of papers can be much more difficult than writing the standard “Oh look, it did exactly what we expected” paper but it can still be rewarding. At least then your data can contribute to the current state of knowledge on a topic and that’s really what research is all about.

And if, after months of work, your results aren’t showing what you expected, then undoubtedly you are operating at the cutting edge of science where the literature is insufficient to properly explain the phenomena. At least that’s what I tell myself.