learning.understanding.cognition.intelligence.data science

Interactive Science Communication

 by Scott Sievert and Purav “Jay” Patel

Scientific research is still communicated with static text and images despite innovations in learning theories and technology. We are envisioning a future in which interactive simulations and visualizations are used to enhance how complex methods, procedures, and results are taught to other scientists and non-scientists.


Scientists in various fields ask questions about different things, but they share the same basic of communication. Nearly all research is communicated to other scientists, journalists, and the public in the form of static text and images encapsulated in journal articles and conference papers. These papers can be found in print and online for a high price. Recently, the “open science” movement has focused on broadening the number of people who can access these papers by eliminating the access fees for these (often) pricey papers. But there’s a problem. Even if all scientific papers are free and convenient for everyone to physically access, they will still not be cognitively accessible. In other words, the number of people who can understand the meaning of most scientific papers (even superficially) will be low.


We believe that research should be conveyed directly to the public. At the moment, the traditional text and images approach makes it difficult to do so. Because of this, science journalism acts as an intermediary, translating the jargon for the public to appreciate (see physorgnewspapers, and educational videos.

But this is not always a good thing. Science journalism is often misleading (see John Oliver’s takedown) because their focus is to hook the audience and drive viewership and readership. Major change is needed because scientific literacy affects how people understand and affect the environment, their bodies, and
voting. Scientists need better ways to communicate their ideas and learn about other’s work. By one estimate, the total volume of scientific research (measured in the number of published papers) doubles every nine years.

For young and seasoned scientists in any field, this is a major bottleneck toward producing great science. How can the best discoveries be made if scientists are unable to keep up with the latest findings? But how can technical research be communicated effectively without “dumbing it down?” Below, we explore some promising ideas.

Suggestion 1: Interactive Simulations of Experimental Tasks

One problem with traditional research papers is their use of dense text and cluttered visuals to convey the materials used in a study. For example, I led a study during my master’s to understand how typical undergraduate comprehend irrational numbers. This study used four tasks, each including subsections. When I wrote up the scientific papers and sent it to the journal Cognitive Science, there was a constraint – use only text and images. Of course, I have the option of
including hyperlinks to the website hosting my experimental simulations. And I had the option of uploading the simulations to another website (Open Science Framework – osf.io). I did both of these things, but felt that most readers wouldn’t go through the trouble of visiting those website. When I got the reviews back from the editor of the journal, I found clues in their comments that no one actually used these websites. The best way to communicate the experimental tasks and procedures effectively is to directly embed them into scholarly articles. Some programmers, user interface designers, and scientists in computer science have played with this idea. I was particularly inspired by these three examples:

1. worrydream.com/ScientificCommunicationAsSequentialArt
2. ncase.me/polygons
3. distill.pub/2016/handwriting

What do these examples all have in common? In each case, the authors could have used blocks of clearly written text to communicate complex visuospatial relationships. Instead, they chose to bring the concepts to life and allow users to manipulate the information in ways that are more natural. It is as if an expert is besides you drawing and explaining otherwise obscure ideas.

So far, prototypes of interactive scientific papers have focused on math and computing (formal sciences). At the start of my first semester of an Educational Psychology PhD, I wondered how these ideas could apply to psychological papers like the one I wrote for my master’s thesis. With the help of three Computer Science students in a Human-Computer Interaction class, I set about embedded experimental simulations in a webpage containing my scientific article. The paper was titled How the Abstract Becomes Concrete: Irrational Numbers are Understood Relative to Natural Numbers and Perfect Squares. I started by reducing the length of the paper to 10% of the original size (start small!). I helped develop each simulation corresponding to different sections of the tasks.

This is what the original section of my scientific paper looked like. Though it makes sense to most people in the field of numerical cognition, it is hard for people outside of the field to say with confidence that the description is clear.









Now let’s have a look at the interactive simulation that enhances the text:

Traditional scientific papers give users a third-person glance into experiments, whereas we aim to provide users a first-person view into what the authors did. From a technological perspective, this change is fairly simple. Existing experimental code can be embedded into digital documents, saving authors valuable time. Moreover, any extra effort required can pay off significantly down the road. The enhanced paper is now easier for scientists, friends, family members, potential employers, collaborators, students, autodidacts, and many others to understand.

Currently, most experimental tasks live inside hard-to-access supplementary materials documents that are usually not accessed. The work that goes into creating these documents often doesn’t bear fruit. By directly embedding experimental simulations we can “show and tell” what happened and rescue authors from wasting time on supplementary materials.

It is not difficult to imagine how to extend this to other kinds of tasks with different kinds of input. In the interactive article mentioned earlier, the complexity of the tasks varying from simple keyboard responses (Z or M key) to mouse clicks and text input. It is also not difficult to consider embedding simulations of experimental tasks in fields like neuroscience and education. Health science fields like physical therapy and surgery may benefit from videos and simulations to practice new therapeutic procedures.

Suggestion 2: Interactive Data Visualizations

Interactive visualizations are useful because they allow the user to see the results of some experiment or function as parameters under their control are changed. This is super useful for data exploration and explanation and it’s picking up a lot of steam. These tools can allow users to interact with the results of scientific experiments or analyze how a particular method performs. Examples of tools that can create these interactive figures are ipywidgets and Holoviews.

These tools allow simple creation of interactive tools in Python, a high level language. These tools allow easy data exploration and can be embedding in a variety of contexts. In the future, one could imagine generating visualizations that show group level trends with the option to quickly change the visual so that individual differences across participants are transparent. For instance, consider an interactive visualization showing a density plot of participants’ scores on a cognitive task. By clicking buttons of dragging a slider, the user could abstract out more general information in the form of a violin plot, then a boxplot. Abstracting out even further, the user could change the original plot to a bar plot or table. Given that journal and conferences
adhere to strict (and problematic) word and page limits, creative interactive data visualizations capable of communicating vast amounts of information in small spaces would improve the quality of scientific articles. Authors would not need to question which one of a dozen analyses and results to focus on. By using rich multimedia, more information can be presented without overwhelming users.

One scientific journal that utilizes interactive graphics heavily is Distill. In this, the team at Distill works with the authors to create a set of interactive graphics for their article that highlight certain points. This has lowered the barrier to reading and understanding any of their papers. Interactive media can convey subtle points that are not immediately obvious.


This example can be extended easily. Communication in science is critical, but surprisingly difficult. Scientists need to communicate their methods, results and experimental design so other scientists can reproduce their results. Allowing quicker and more accurate communication between scientists can yield more robust experimental results and fuel collaboration. These ideas are espoused by arxiv, a digital, open-access scientific publication platform developed by physicists. More recently, website like the Open Science Framework (OSF) and Authorea have offered tools that enable open-access disseminate of scholarly research. The OSF archives preprint, experimental materials, and data across different fields for anyone to access. Authorea is a new digital authoring tool for scientists to collaborate online and embed interactive figures into their manuscripts. This tools also helps format manuscripts for the needs specified by journals and conferences, saving tedious editing. It is possible that one of these platforms (or another
like it) will play a large role in developing the scientific documents of the future.

Extend Your Learning

In addition to the sources listed above, consider checking out the
following examples of multimedia-enhanced scholarly communication:

1. Distill.pub description of benefits: https://distill.pub/about/
2. “Building blocks of interactive computing”, the introduction of Jupyterlab: https://www.youtube.com/watch?v=Ejh0ftSjk6g
3. Jupyer widgets, which has live (!) examples of ipywidgets and other libraries: http://jupyter.org/widgets.html
4. Explorable Explanation: http://worrydream.com/ExplorableExplanations/
5. Interactive PhD Thesis: http://tomasp.net/coeffects/
6. Journal of Visualized Experiments: https://www.jove.com/