Requirements on and Selection of Data Storage Technologies for Life Cycle Assessment

Michael Ulbig, Simon Merschak, Peter Hehenberger, Johann Bachler

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


The importance of a centralized data storage system for life cycle assessment (LCA) will be addressed in this paper. Further, the decision-making process for a suitable data storage system is discussed. LCA requires a lot of relevant data such as resource/material data, production process data and logistics data, originating from many different sources, which must be integrated. Therefore, data collection for LCA is quite difficult. In practice, relevant data for LCA is often not available or is uncertain and has therefore to be estimated or generalized. This implies less accuracy of the calculated carbon footprint. State of the Art research shows that the LCA data collection process can benefit from data engineering approaches. Key of these approaches is a suitable and efficient data storage system like a data warehouse or a data lake. Depending on the LCA use case, a data storage system can also benefit from the combination with other technologies such as big data and cloud computing. As a result, in this paper a criteria catalog is developed and presented. It can be used to evaluate and decide which data storage systems and additional technologies are recommended to store and process data for more efficient and more precise carbon footprint calculation in life cycle assessment.
Original languageEnglish
Pages (from-to)86-95
Number of pages10
JournalProduct Lifecycle Management. PLM in Transition Times: The Place of Humans and Transformative Technologies
Publication statusPublished - 1 Feb 2023
EventIFIP 19th International Conference on Product Lifecycle Management (PLM2022) - University Grenoble Alpes and Grenoble-INP, Grenoble, France
Duration: 10 Jul 202213 Jul 2022


  • Carbon footprint
  • Data engineering
  • Data storage technology
  • Life cycle assessment

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