ESS Control System Data Lab - Executive Summary
(2021) In Technical report- Abstract
- 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... (More) - 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1dda6ef9-73e8-4fd9-921d-0bbe652ac43b
- author
- Runeson, Per LU ; Andersson, Per LU ; Hall, Anna ; Larsson, Jan Eric LU ; Rathsman, Karin LU and Söderberg, Emma LU
- organization
- publishing date
- 2021-02-19
- type
- Book/Report
- publication status
- published
- subject
- in
- Technical report
- issue
- 105
- pages
- 2 pages
- publisher
- Lunds Universitet/Lunds Tekniska Högskola
- ISSN
- 1404-1200
- project
- ESS Data Lab
- language
- English
- LU publication?
- yes
- id
- 1dda6ef9-73e8-4fd9-921d-0bbe652ac43b
- date added to LUP
- 2021-02-22 15:04:37
- date last changed
- 2022-05-04 15:43:15
@techreport{1dda6ef9-73e8-4fd9-921d-0bbe652ac43b, abstract = {{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:<br/>1. How to govern a data ecosystem, and which tools are needed to support it?<br/>2. How can alarm data be interpreted across industrial contexts, i.e., which meta data<br/>and reference models are needed?<br/>3. How can data sharing be practically and legally handled at ESS?<br/>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.}}, author = {{Runeson, Per and Andersson, Per and Hall, Anna and Larsson, Jan Eric and Rathsman, Karin and Söderberg, Emma}}, institution = {{Lunds Universitet/Lunds Tekniska Högskola}}, issn = {{1404-1200}}, language = {{eng}}, month = {{02}}, number = {{105}}, series = {{Technical report}}, title = {{ESS Control System Data Lab - Executive Summary}}, url = {{https://lup.lub.lu.se/search/files/94381963/ESS_CSDL_Executive_Summary_v2.pdf}}, year = {{2021}}, }