Workshops 2018

Workshop: Turning Data into Sound and Music

Hannah Davis

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Data sonification lets us think and reason about data in an entirely new way! It can reveal variables and dimensions that would otherwise stay below the surface. On top of that, data sonification can also be used to create music and other creative projects!
This workshop will introduce users to the field of data sonification, or turning data into sound. We’ll look at different real-world examples, and see data from politics, sports, literature, and others turned into sound and music. We’ll look at the various types of data sonification, and how to decide which types are best suited for which types of data. We’ll see how to implement data sonification with several different tools. We’ll also look at music generation as a subset of data sonification. By the end of the workshop, participants will understand the field of data sonification and be able to implement it using a tool of their choice.
SKILL LEVEL: Intro/Intermediate
• Introduction to sonification; examples and use cases.
• Deciding what the best type of sonification is for types of data, and talking about appropriate mappings. Talk about any datasets that attendees brought to the workshop.
• Go over tools for data sonification, and implement several examples in Python and p5.js.
• Work with participants to implement data sonification projects of their own.
• personal laptop
• headphones
Attendees should feel free to bring their own dataset to sonify. Otherwise, sample datasets will be provided to download.

Workshop: Observe, Collect, Draw!

Giorgia Lupi & Stefanie Posavec

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Giorgia and Stefanie (creators of the project and book Dear Data) are in the same city for once, and together they are teaching a very special data-drawing workshop! 

Data is the raw material from which a range of outputs such as data visualization, information graphics, and data-driven artworks are created. This material is often associated with heavy programming skills, complex software and huge numbers but in fact, lots of data visualization designers use old-fashioned sketching and drawing techniques on paper as their primary design tool. How would your approach and sensibility within a data project change if you started by working with charcoal and paper instead of code and screens? Starting a data project by sketching by hand introduces novel ways of thinking, and leads to designs that are uniquely customized for the specific type of data problems we are working with. Through this workshop, you will discover how to use data as a creative material to inform any kind of design, and discover a new way of seeing and engaging with our world, where everything and anything can be a creative starting point for play and expression. 

During the day we'll explore ways of using traditional methods and materials as a starting point for creating data-driven visual systems by taking techniques from the world of art and design and applying them to data. 

We will learn how to produce and create a dataset through observing the world around us: starting from a main question we will build our own data points filled with attributes from what we notice.

Finally, we'll think about the creation of a visualisation system through using a handmade design process, exploring variability in mark-making and material as a way to communicate information, and how to take visual inspiration from what you see to guide your data drawing: learning to see and to reproduce the aesthetic traits that attract our eyes to our surroundings and translate it into visual symbols.

By the end of this workshop, you'll both better understand the data visualization design process and also have access to a different starting process for working with data and shaping its aesthetic (even if you move onto your computer / into code at a later point!)

The entire workshop will be off-screen, using nothing more than basic drawing materials.
SKILL LEVEL: Intermediate

• Why draw data? Why not use software and code?

Applying a creative approach to data visualization

• Learning to see data all around you, and to become a collector in your daily life
Learning how to produce / create a dataset, with attributes and categories
• Basic data analysis as part of the design process
Introduction to rule-based drawing as approach to creating a data visualization

• How to determine the architecture of your data-drawing
Anatomy of a data visualization

• Visual inspiration as a guiding principle

Data-drawing ‘Bootcamp’ (Intensive drawing session merging traditional drawing exercises with data to build creative confidence and push experimentation).
• Feel free to bring along any favorite drawing utensils!

Workshop: Building Creative Interactions with Machine Learning

Rebecca Fiebrink

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Are you interested in creating real-time interactions with sensors, cameras, depth sensors, gaming controllers, or microphones? Machine learning can be a great tool for giving such inputs control over animation, sounds, robots, game engines, or other systems you’ve built. Machine learning makes it possible to build complex interactions that are difficult or impossible to create using only programming; machine learning also makes it possible for non-programmers to build and customize systems, and for programmers to build things more quickly.
In this workshop, you’ll get a hands-on introduction to using machine learning for designing new interactive art, music, games, and other real-time systems. We’ll teach you the basics of a few standard machine learning techniques and help you get started hacking with machine learning on your own projects.
For students who want to prototype things quickly without code, we’ll be using the Wekinator., a free and cross-platform software tool that connects to a wide variety of existing hardware and software (e.g., Arduino, Unity 3D, Max/MSP, PD, Ableton, openFrameworks, Processing, Kinect, Bitalino, …). We’ll also be showing how the same techniques can be used within code (including openFrameworks/C++ and JavaScript) using free libraries such as the RAPID-MIX API.
We’ll talk about how to use machine learning to work more effectively with sensors, audio, and video data, and to build expressive & embodied interactions. You don’t need any prior machine learning knowledge (though you’ll still learn a lot even if you’ve previously studied machine learning in a more conventional context!). We’ll combine lectures and discussion with plenty of hands-on hacking. We’ll be using free and open source software to hook up game controllers, sensors, webcams, and microphones to interact with sound, animation, game engines, actuators, and other creative gear.
SKILL LEVEL: Intro / Intermediate / Advanced
The workshop will be most useful for people who can do a bit of coding in some environment (e.g., Processing, openFrameworks, JavaScript). But people who don’t do any programming will still be able to fully participate, as we have plenty of off-the-shelf examples which can be run without coding.
• All attendees should bring a laptop (any operating system).
• Optionally, attendees can also bring input devices such as those listed at (e.g., Leap Motion, Arduino + sensors, joysticks, mobile phone with touchOSC, ...).
• Attendees may also want to bring software/hardware they might want to control with machine learning (e.g., Arduino with motors; Max/MSP, Unity, Processing, openFrameworks, ...)
• Install Wekinator from
• Make sure it runs! If not, install the most recent version of Java for your operating system.
• If you're a Processing programmer, install the Processing code "Quick Start Pack" from Follow the instructions at this Youtube How to run Wekinator examples in Processing Video to install the Processing libraries for OSC and video if you don't already have these.
• Or if you're not a Processing programmer, install the "Quick Start Pack" for your operating system at Run the executable in Inputs/Simple_Mouse_DraggedObject_2Inputs/ and make sure you see a green box on a black screen. If you don't, please download the "last resort" examples from