Image courtesy of Destination NSW.
A picture tells a thousand words. And no one knows this better than Digizyme-cofounder, Gael McGill. Doctor McGill is an academic who has worked as a research fellow at the Dana-Farber Cancer Institute and Harvard Medical School. He has also specialised in producing scientific 3D and vector-based visualisations, something that is becoming increasingly more important as our world is driven by big-data.
Gael McGill will be speaking and teaching at the Data Visualisation masterclass at Sydney’s Vivid festival in June. He will be joined by Tamara Munzner, a professor at the University of British Columbia’s Department of Computer Science. The AU Review sat down with Dr. McGill to learn more about idiosyncrasies in the human visual perception system and how visualisations can help people understand the ‘big picture’ summary of a complex process.
Can you tell us a little bit about yourself and your background?
Cell and molecular biology have been my passion since my middle school days in Paris and my dream was to be involved in cancer research. I came to the USA for my undergraduate studies specifically for molecular biology but was also interested in combining art & design with my passion for science, so I graduated from Swarthmore College with highest honors in Biology, Art History and Music.
I did my Ph.D. and postdoctoral research at Harvard Medical School and the Dana Farber Cancer Institute (focusing on cancer signal transduction pathways and apoptosis). During my PhD years, having identified a need in the local academic, medical, biotech/pharma communities for “scientifically-informed” graphic design, programming, animation and data visualization services, I started my company Digizyme (www.digizyme.com) in 1999 while completing my degree. Since then Digizyme has grown to offer a variety of services and products for high profile clients such as Apple, Genenech, Novartis, WGBH, and many other biotech/pharma companies – projects include digital textbooks, multimedia for museums, marketing/communication for life sciences companies, science curricula and visualization software tools and training. Our team members all combine graduate-level training in the life sciences with industry-leading skills in design and animation – this allows us to innovate at the intersection of science, technology, art and learning/education.
Currently I am also a faculty/principal investigator at Harvard Medical School where I do educational research on design in scientific visualization and, since 2006, I have also been teaching the scientific visualization curriculum I created and have made available on the website molecularmovies.com. In June 2015, I will launch a new scientific visualization portal called Clarafi.com which offers high quality training and software tools for scientists interested in creating their own visualizations.
What can audience members expect to learn at the Data Visualisation masterclass?
In my section – ‘The Power & Danger of Storytelling in Scientific Visualization’ – I will provide many examples of how visualization can help us gain an intuition for otherwise complex and messy processes. In many cases, visualizations ‘seed’ our mental models of science and, in doing so, impact the very questions we ask and the research we do. It is therefore important to recognize both the power and potential danger in crafting scientific visualizations. Practically speaking, I also hope to introduce participants to some of the great tools and techniques that we have borrowed and repurposed from the entertainment industry.
In your opinion, what are some of the biggest mistakes people are making with visualisations and their treatment of big data?
It’s hard to generalize since design decisions are so specific to the data at hand, the goal of the visualization and the target audience… Perhaps one example, especially in the case of narrative-driven, ‘immersive’ scientific visualizations/animations, is when aesthetics appears to be the leading design parameter (sometimes at the expense of scientific accuracy and clarity). I don’t believe one has to sacrifice one for the other. Oversimplification can also be a problem… I am very interested in my research in how we can use design to manage the depiction of scientific complexity.
Programming languages like R and software like Tableau are becoming common methods for preparing visualisations. What programming languages and/or software would you recommend?
Depends on the result you are trying to achieve. For clean, vector-based visualizations, tools like Processing have been very popular. For the kind and variety of images, interactives, simulations and animations we created for a project like the ‘Life on Earth’ iBook, tools range from HTML5 to some of the workhorses of the entertainment industry like Autodesk Maya, The Foundry’s modo, Pixologic’s Zbrush and the Adobe Creative Suite (Photoshop, Illustrator, After Effects, etc).
Will people attending the Data Visualisation Masterclass be learning any programming languages or software? What level are you pitching the class?
Yes – but since some of the software we use is both extremely powerful and also comes with a steep learning curve, the aim is to provide enough of an introduction so that participants know whether or not they want to invest additional time to learn. Nobody masters 3D animation software in one afternoon or day… but it is possible to gain a very good feel for the capabilities of the software and whether or not it is the right tool for depicting your science.
What do you think are the biggest issues facing companies in the field of analytics, visualisations and data analysis?
From a business perspective, a big question is whether or not the company wants to be a service-based company or one that develops products (be they content-driven products or software tools/resources). As a service-based business, finding clients and projects that can sustain the budgets necessary to do great work can be challenging… but it is wonderful that there is a fascinating and endless list of visualization challenges one is faced with. For the product-based business, developing high-quality content can be a real challenge in an era where many people somehow feel that content is free and ubiquitous.
What are some of the pitfalls humans face in terms of their visual perception?
As we know there are all kinds of interesting idiosyncrasies to the human visual system… but I tend not to think of them as pitfalls or weaknesses but rather opportunities to be used in design. In other words, by understanding these we can better manipulate or manage the viewers’ attention and guide them through visual stories or other data-rich displays.
Can you give us an example of where data visualisations have really helped in telling an important story or presenting important results?
Sure – there are many. One of Digizyme’s strengths is in molecular animation and we have created dynamic visualizations that piece together structural and dynamic data from many disparate data sources. In that sense, a visualization can become a knowledge synthesis exercise that helps scientists or students grasp the ‘big picture’ of a complex process. For example, we created a visualization of the Death-Inducing Signalling Complex (DISC) that gives viewers a sense of the step-by-step dynamic assembly process of this 20+ protein complex. We felt that both an animation and a static diagram was most effective to communicate this process: http://www.digizyme.com/genentech.html
This type of knowledge synthesis does not always have to be a dynamic visualization – we designed the popular ‘Human Pathways in Cancer’ poster that summarizes several key signal transduction pathways in cancer while highlighting the extensive amount of crosstalk that occurs between such pathways: http://www.digizyme.com/cst_cancerposter.html
We also created cellular landscapes that showcase the great structural diversity of molecular components but also organize these in a way that viewers can navigate interactively:http://media.cellsignal.com/www/html/science/landscapes/mitochondria/mit…
Gael McGill will appear at the Data Visualisation Masterclass at the University of Sydney for Vivid Festival on June 8. For more information and tickets please visit: http://www.vividsydney.com/event/ideas/data-visualisation-masterclass or datavismasterclass.org
Originally published on 19 May 2015 at the following website: http://www.theaureview.com/interviews/digizyme-cofounder-gael-mcgill-describes-how-visualisations-can-help-with-complex-processes
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