New Guidelines for Data Modeling and Data Integration for Material Flow Analysis

Material flow analysis (MFA) is booming. A large number of datasets are being compiled and produced as part of MFA research, but many of them are not available or cumbersome to extract — either because of their format (e.g., pdf), or because they lack systems context.
For this reason, researchers often have to spend too much time searching for, formatting and interpreting data sets, which means that valuable time is lost in evaluation, quality control, uncertainty analysis and documentation of their own data products.
Progress in research (e.g., comparative studies), link to other fields (e.g. climate scenario modelling), and dissemination (such as policy-relevant work) requires data integration built on easy access, combination, re-use, and update of existing datasets.

As part of its mission, the Section Board of the Topical Section for Research on Socio-Economic Metabolism (SEM) of the International Society for Industrial Ecology (ISIE, has compiled the first Guidelines for Data Modeling and Data Integration for Material Flow Analysis and Socio-Metabolic Research (Version 1.0 of June 2021). This document was compiled by Stefan Pauliuk together with the 2020/21 ISIE-SEM board members: Hiroki Tanikawa, Tomer Fishman, Stefan Giljum, Helen Hamilton, Gang Liu, Kazuyo Matsubae, and Peter Paul Pichler. It was refined during several rounds of peer review within the ISIE-SEM section and beyond. The following colleagues provided detailed feedback and additional suggestions: Gian Andrea Blengini, Florian Dierickx, Tomer Fishman, Arturo de la Fuente, Rick Lupton, Fabrice Mathieux, Stephan Moll, Philip Nuss, Simon Schulte, and Christina Torres de Matos. The responsibility for the final version, and any shortcomings and inconsistencies it may have, lies with the ISIE-SEM board.

The document is self-explaining and not too long! It should be a standard reference for all who are in the process of publishing, documenting, or archiving MFA research, either within a software such as STAN ( or in a custom modelling environment.

You find it here: SEM_MFA_Guidelines_V1.0_June_2021 (pdf)

We hope that these guidelines will provide reliable orientation in many different research and consulting settings. The guideline document is evolving and will be updated every couple of years to keep pace with the development of the field. We also hope that it will trigger discussions and spur engagement around some of the open items, like the development of common material classifications or of a system taxonomy for MFA datasets. If you have issues to raise, please use the contact details provided in the document.

All the best for your ongoing and future MFA research!

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