Creative Data Exchange is a knowledge exchange project based on the development of a community of practice working on creative projects driven by data investigations. It is designed for those with a research-first approach to data and/or creative practice. Community members come from many different backgrounds; they could be creative practitioners, research professionals, technologists and everything in between. What they have in common is an investigative mind, an interest in working with data, software and creative processes. They could be experienced in an area of creative practice and only curious about data, or very experienced in data research and only curious about creative practice. The purpose of the community is to help bring creativity and digital research expertise together, whatever the level of experience members have on either side of the spectrum.
Why it matters
New technology has been disrupting creative practice long before the invention of the first paintbrush. Yet it has been some time since a single wave of innovation held the potential to fundamentally transform how we investigate the world and how we create — across disciplines and at every stage of the creative process.
And as with many moments of profound change, the Data & AI hype emerged around serious ethical and safety concerns, as well as mysticism, fuelling curiosity but also provoking unease, scepticism, and hesitation to engage.
Creative Data Exchange is the antidote to this. It provides a space for open, grounded conversations about working creatively with data — where you can share questions and ambitions and find routes to answers in good company.
We are passionate about art and technology but we have seen the recent advances increasing the digital divide. Those who had experience and felt confident to onboard the AI boat have done so. But there hasn’t been much opportunity for artists who are unfamiliar with this technology to get clarity beyond the hype. This is a systemic problem because this debate has many implications for creative practice, not least related to copyrights, visibility and funding of their own work, digital or not. This is bad for technology development, which gets narrower, involving a smaller set of artistic questions and practice. And it is bad for artists too, who may miss out on opportunities and debates that are crucial for their development and that of the creative industries more generally. So we want to understand from this community what it takes to break those barriers and create opportunities for the community itself to drive this change.
Partners
Creative Data Exchange is presented by the Contemporary Narratives Lab in partnership with Goldsmiths Futures of Creativity Institute (FOCI) and Fuel. It is supported by the Institute for Research Software via an IRS Fellowship 2026.
Who we are
This project is led by André Piza, as an Institute for Research Software Fellow 2026.
André Piza is a community developer at heart, with a background as a creative practitioner, producer and research programme manager. For over 7 years, he has managed and coordinated research delivery of the Alan Turing Institute’s flagship Digital Humanities programmes, like Living with Machines and the Research Software Engineering Capability Roadmap. Previously, he has managed major international creative and research projects at People’s Palace Projects, an arts research centre based at Queen Mary University of London where he also worked as Knowledge Exchange Manager for the Creative Industries. His work there included collaborating with arts organisations, policy institutions, and independent artists and activists.
He has written about cultural exchange practice in The Art of Cultural Exchange (2019) and is a co-founder of the Turing’s AI&Arts interest group. He currently manages the CoSTAR Foresight Lab, a research and innovation hub exploring the impact of emerging technologies on the creative industries, based at Goldsmiths, University of London.
Our leading Research Software Engineers
Kaspar Beelen is a digital historian who explores the impact of datafication and machine learning on humanities research. After obtaining his interdisciplinary PhD in history and linguistics (2014) at the University of Antwerp, he worked as a postdoctoral fellow at the University of Toronto, as a researcher on the Digging into Linked Parliamentary Data (Dilipad) project. In 2016, Kaspar moved to the University of Amsterdam, where he first worked as a postdoc and later became an assistant professor in Digital Humanities (Media Studies). Between 2019 and 2023, he worked at the Alan Turing Institute as a research associate for the Living with Machines project, where he focused on understanding biases in large historical collections. Currently, he works as Technical Lead Digital Humanities at the School of Advanced Study, University of London, exploring the use of multimodal and vision models for cultural heritage.
Rosie Wood is a Research Software Engineer working at the Alan Turing Institute. From 2023 to 2025 she worked as part of the Living with Machines and Data/Culture projects where she was core developer for MapReader — a computer vision pipeline for analysing large collections of historical maps. Since then, she’s been part of the Research Computing team at the Turing, where she works with High Performance Computing (HPC) systems — including providing training and support for Turing researchers wanting to use HPC, benchmarking HPC applications and running model training and inference on GPU. She is also part of the t0 team, which focuses on applications of local LLMs and agentic AI.
Lydia France is an AI engineer at Marker and a Schmidt AI in Science Research Fellow at the University of Oxford. After obtaining her PhD in bird flight (2019) at Oxford, she worked as a Research Software Engineer at the Alan Turing Institute between 2021 and 2026. Lydia worked on cross-disciplinary projects including Digital Humanities and AI for climate forecasting. Earlier this year she moved to Marker, a startup making software for writers that puts human creativity and writing first (and not writing for you!). She is currently working on training small language models that are energy efficient and privacy first. Her university research uses data-driven methods to understand coordinated movement in animals, particularly wings in bird flight. She also regularly performs and teaches Improv Comedy as part of the Oxford Imps and has been previously involved with Young Fiction Writing communities.