9-13 October 2023

The visual communication of data and concepts has always been an integral part of sciences. Especially in the last years, with the increasing availability and potential of software and coding languages, researchers and science communicators are called to visualize their ever more complicated science when publishing, teaching, doing outreach, and posting on social media. Accessibility is also getting prioritised, with standards getting in place to make sure science is presented in a way accessible to all. However, more often than not, researchers lack the necessary tools to visually communicate their science effectively. This course provides a design toolkit for anyone that makes visuals for their research and data. From the use of text, colour, and images, to the importance of narrative, the difference between vectors and pixels, and file types, this course covers everything needed to guide the viewers through complex scientific notions and results. With these tools equipped, participants of the course will be able to make conscious design choices according to the target audience and media, and apply them in any software or coding language. They will also get hands-on practice, as well as useful resources to access images, graphics, fonts, and more.

This course will be delivered online, with live sessions that include lectures, lots of examples, practice sessions on software picked by the participants, and a bring-your-graphic-idea/draft for discussion and feedback session.

This course is for researchers, students, science communicators (and everything in-between) who want to learn how to visualize their science in a more engaging, clear, fun, and accessible way. This course provides the starting toolkit to presenting scientific concepts and results (through posters, slides, figures, social media posts, and more) according to the audience and media.

Participants don’t need any previous experience in art or graphic design, as we will cover the relevant principles of graphic design and data visualization (along with examples and useful web resources). The course will be personalised to the various levels of experience of participants with making graphics. Participants should have access to a computer with wi-fi. A camera and microphone are optional but highly recommended. This course doesn’t focus on any particular software, but participants will be putting their knowledge into practice using their preferred software (e.g. PowerPoint, Inkscape, Canva). We will also introduce additional useful software, tools and resources for all degrees of knowledge.

During this course, participants will:
•    get confident at visually communicating their scientific data and results in a captivating and accessible way,
•    learn how to use and arrange colour, text and images in order to guide the audience throughout their results narrative,
•    learn how to plan any scientific design project from start to finish, making conscious design choices according to the              audience and media,
•    get hands-on experience in a variety of popular design software, and know their way around different file formats.

Monday - 10 am - 1 pm Berlin time
What is science visualization, and why do we need it?
•    Different types and applications.
•    The importance of visualizing data and the impact it can have.
•    You don’t have to be a graphic designer to successfully visualize science!
What is an effective science data visualization?
•    How does the human brain process images and text?
•    Short-term memory, long-term memory, and attention span.
•    Not all people process information like you do – disabilities, language, culture barriers, and more.

Tuesday - 10 am - 1 pm Berlin time
Basic principles of design for science visualization: how to emphasize what matters, and guide viewers through your results.
•    The use of colour: colour theory basics, the importance of consistent colour palettes, contrast, readability, and accessibility.
•    The use of text: font types and when to use each, use of text size to hierarchise and emphasize, how much text is too much text?
•    The use of images and illustrations: when to use each, finding the good balance between images, illustrations, and text, where to get images and illustrations.
•    Element positioning: the importance of the arrangement of colours, text and graphics in guiding the viewer through your results and data.
•    Which graph for which data: different types of graphs and how to choose the right one for your data/information visualization.
•    Examples of good and bad designs, and useful resources.

Wednesday - 10 am - 1 pm Berlin time
Pixels, vectors, and file formats.
•    What are pixels and vectors, what are their pros and cons, and which one should you pick for your graphics?
•    Which file formats exist, pros and cons, and which file type(s) should you save/export your work as
What software for what project?
•    Introduction to the variety of software available: from software for beginner to advanced graphics, free and paid.
•    Software: their best features, pros and cons, complexity and learning curve, file export formats.
•    How to choose the right one(s) for your project.
•    Closer look to some of the most popular graphic design and presenting software available to researchers: PowerPoint, Inkscape, Illustrator, GIMP, Canva, and Figma.
Practice session 1: Let’s make a sci-comm gif/video in PowerPoint or Canva!
•    Short how-to tutorial and examples in both software.
•    Participants pick a short/simple result from their research or field and prepare a gif/video in PowerPoint (paid) or Canva (free).

Thursday - 10 am - 1 pm Berlin time
Adding a narrative, and knowing your audience and media.
•    How adding a narrative makes your results more memorable and engaging.
•    Design with your audience in mind: how your visualization, amount of data and focus should be different depending on the audience.
•    Adjust your design according to the media/communication channel (online vs face-to-face, synchronous or asynchronous presentation, and more)
Graphics licencing.
•    Different types of licencing.
•    How to properly use/credit other people’s graphics, and how to add a licence to your own graphics.
Practice session 2: Let’s delve into some of the software!
•    How-to tutorials on some of the most voted software by participants.

Friday - 10 am - 1 pm Berlin time
The design-process framework: how to plan any design project from start to finish.
•    Plan your project ahead: make conscious design decisions, putting everything you have learnt into practice.
•    Choose which software or combination of software to use, thinking potential integration between them.
•    Consider making designs modular, so that you can reuse them in different situations!
•    Design frameworks for the most popular things researchers have to make: posters, slides, and figures.
Practice session 3: Bring your graphic(s) for discussion and feedback.
•    Participants are asked to bring an idea or a draft of a scientific graphic or design project of their choice (e.g. a slide, poster, figure, graph relating to their research).
•    We will collectively dissect it and give feedback and potential design solutions.
•    This is a great opportunity to practice and apply everything we have covered, it doesn’t have to be finished by any means, it can be a hand-drawn sketch, or a draft made using a software you are familiar with.