Driven by the idea to use alarm data to explore machine learning across Industry 4.0 applications, the goal of this pilot study was to explore how to collect, store, manage and share data from the ESS Control System. Generally, we seek to make any control system data available for research and innovation but started with alarms as a feasible domain in which to explore machine learning. The goals were threefold, each explored in a work package:
1. How to govern a data ecosystem, and which tools are needed to support it?
2. How can alarm data be interpreted across industrial contexts, i.e., which meta data
and reference models are needed?
3. How can data sharing be practically and legally handled at ESS?
In summary, we identify a set of potential alleys for continued work to foster industrial innovation and collaboration in a control system data ecosystem with ESS as a catalyst.
Original languageEnglish
PublisherLunds Universitet/Lunds Tekniska Högskola
Number of pages2
Publication statusPublished - 2021 Feb 19

Publication series

NameTechnical report
PublisherLund University, department of computer science
ISSN (Print)1404-1200

Subject classification (UKÄ)

  • Information Systems


Dive into the research topics of 'ESS Control System Data Lab - Executive Summary'. Together they form a unique fingerprint.

Cite this