Monitoring and Control Data

In all Machine Learning (ML) projects, it is critical to have access to large amounts of well-organised data to feed the learning process. The exploding achievements in Artificial Intelligence (AI) over the past decade is primarily due to access to data and increasing computing power. The ESS control systems will generate at least an order of magnitude larger volumes of control system and automation related data than typical existing, large industries. This rich mix of data will range from typical industrial process control systems to state-of-the-art control and data acquisition systems.

ESS Control System Data Lab is a Vinnova-funded project coordinated by the Department of Computer Science at Lund University. The objective is to explore how to make data from the integrated control system at ESS available for research and innovation.


  • With about 1,6 million control signals in the ESS integrated control system and very high data volumes, AI and ML become viable and interesting technologies.
  • The investigation of appliance of AI and ML is performed in collaboration with other facilities, namely MAX IV and DESY.
  • In order to further develop a common understanding of the ESS challenge, a Vinnova-funded pilot study for an ESS Data Lab is being executed.
  • The study partners shall enable access to the latest technology and knowledge: GoalArt (private AI company), Lund University and Big Science Sweden.
  • By knowing the complexity and scope of the challenge at ESS it has been possible to create interest from AI and ML scientists to see ESS as a “living lab” for these studies.


  • ESS will be instrumental in more facilities working together on the same problem by working on the same data.
  • Further collaboration agreements will be established and ESS hope to contribute to an emerging control system AI and ML community.
  • Open collaborative data platforms should be selected so datasets can be shared and evaluated in different contexts.
  • The sharing of data is a necessity for collaboration on scientific challenges between facilities.
  • Data becomes the common denominator and there is a plan to use real monitoring and control data from DESY to validate the ESS systems.