I started working on DataDrivenDance in 2011, when I was teaching ICT and acting as a member of the drafting group for the initial computing programme of study for England. I was motivated by a desire to build an interest in computing and reduce fear of the subject. I was also driven by my experiences of seeing girls having an interest and an ability in computing in Key Stage 3 (ages 11–14), but choosing not to continue the subject at GCSE. I hoped that benefits would be felt by the dancers, the audience, the educators, and artists. The project won a Google RISE award for Computer Science Education in 2013, and has also since benefited from the supported of three Grants for the Arts Awards from Arts Council England.
I first realised that the idea of a ballet about computing was powerful back in 2013, after running DanceHack as part of the Brighton Digital Festival. The project brought together dancers and programmers. One participant said there was “great insight into the boundaries of digital design and innovation, particularly useful information on how to marry, and seamlessly integrate, graphic iconography remotely generated and human choreographic movement. This has enabled moving a current project on considerably.”
I perform many roles within the development of each ballet, working as a producer through to a coder. I am not a lone wolf, working with amazing technical minds such as Alex Shaw, and the choreographer Camilla Lloyd. I have found that the role of the artist is similar to the code, in a constant cycle of creation, failure, and recreation. The iterative process allows emergent ideas, changes in choreography, all within a sphere of creativity. Failure is part of the process and nothing is perfect. Each ballet crosses many domains within the curriculum from computing, performing arts, science, design and technology, geography to RE.
All of our ballets are performed alongside a video in front of a live audience. This is the method we used to create each ballet, starting with the data first. Each ballet uses different technologies and themes.
Simulated networks
An example of theory performed through ballet and data visualisation is ‘Networks’ from the ballet [data]storm. The data visualisation represents a social network, with each node in the network representing a user who has the following characteristics:
friendliness (how often they’re likely to make friends with another user)
chattiness (how often they’re likely to send messages)
category (the subject area they’re most interested in)
The visualisations are coded in JavaScript, with random time intervals to generate the simulation based on the characteristics. All the rules stay the same throughout the simulation. At the same time, the dance (ballet) movements and wearables (LEDs) were choreographed/coded to accompany the data visualisation using network mapping techniques. Dancers took on the role of data packets travelling through a network. Certain dancers only had access to slow bandwidths that trigger modified choreography, depending on when they arrived at a certain node in the network. Choreography notation was written using node maps. An interesting output was the use of node maps as a choreographic tool.
The theory for networks, virus simulations, and associated choreography came from social network theory and social information processing. This has ties with the English curriculum on data structures, and the implications of computer use and units in the OCR GCSE specification that require students to understand data structures, data types, data transmission, network structures, and protocols.
From the stage to the classroom
You could create your own ballet in a computing classroom, but room size generally doesn’t allow for that. We think of the ballets as R&D platforms for computing in the classroom. We use Arduino and micro:bits in live performances, but the code has also been converted and simplified for a Crumble controller in a primary setting. Year 3 students have repurposed the ‘wearables’, creating disco lights using recycled bottles. They have also added interaction using a touch or ultrasonic sensor, and the Crumble. Each ballet brings a new set of learning opportunities that are converted to classroom resources.
Bringing brainwaves to ballet
Our upcoming ballet, Singularity, will use brainwave data from an Emotiv headset to highlight the hidden nature of data. Singularity is about interstellar travel, augmented reality, communication, data, and morality, encouraging reflections on the ethical use of data and cognitive privacy. The streamed data is in the Open Sound Control format, as used in other applications such as Sonic Pi and Scratch. In 2018, we gave a talk and workshop on Singularity at the Electromagnetic Field festival. The video highlights some of our plans for the project. We will be sharing some of our datasets for educators and students to explore, as the cost of the headset is significant.
DataDrivenDance technologies and themes
[arra]stre, 2014: theory and concepts from the English Department of Education computing programme of study that used a Microsoft Kinect, data visualisation, and wearables.
[data]storm, 2015: Data transmission through weather data supplied by the Met Office. Additionally used projection mapping and live data streams.
[pain]byte, 2017: Chronic pain and biomedical engineering that used biometric sensors and a VR experience.
Singularity, 2020: A story of interstellar travel to highlight technical and ethical questions of communication and human body augmentation. (This will be performed live in Cambridge, UK – see datadrivendance.com for more information).
A key aim is for teachers and students to be able to replicate the technology. We use off-the-shelf products, developing tools to facilitate this. For example, we developed our Kinect server that captures data and exports it as a JSON file. We share code so others can develop their own projects: helloworld.cc/datastorm
