CEEDs: The Collective Experience of Empathic Data Systems


Project start: 01.09.2010
Duration: 3 years
Funded by: EU (FP-7)
Scientific responsibility:  Prof. Dr. Elisabeth André
Invloved Researchers:  Dr. Florian Lingenfelser
CEEDS Project

About the project



The Collective Experience of Empathic Data Systems (CEEDs) project aims to develop novel, integrated technologies to support human experience, analysis and understanding of very large datasets.




CEEDs (The Collective Experience of Empathic Data Systems) is a European project (FP7) that started in 2010.

In a wide range of specialist areas – such as archaeology, neuroscience, history and economics – experts need to make sense of and find meaning in very large and complex data sets. Finding meaningful patterns in these large data sets is challenging. Foraging for meaning in large data sets is a bottleneck that is becoming more challenging as scientific research creates and works with bigger and bigger data sets. And it’s not just scientists who are affected. In everyday life, we are confronted by increasingly complex environments requiring difficult decisions and rapid responses. CEEDS will provide new tools for ‘human-computer interaction’ that will assist our everyday decision making and information foraging.

The proposed solution has two parts. First, we will build new synthetic reality (SR) systems that allow people to consciously experience properties of large data sets, dramatically extending current work in virtual reality. Second, we will exploit the power and potential of the unconscious mind. It turns out that only a small subset of sensory input reaches conscious awareness, yet the remainder is still processed by the brain. And this subconscious processing is very good at detecting novel patterns and salient (meaningful) signals.

CEEDs will develop and use a wide range of unobtrusive multi-modal wearable technologies to measure peope’s reactions to visualisations of large data sets in specially built virtual, or synthetic, reality environments. CEEDs will measure a range of variables, including a users' heart rate, skin conductance, eye gaze, speech characteristics and brain activity. By monitoring these measures, CEEDs will identify users’ implicit (subconscious) responses to different features of visualisations of massive datasets. The implicit responses will then be used to guide users’ discovery of patterns and meaning within the datasets.