Guideline Proposal for Data Modelling in MFA - Request for feedback from section members
Dear members of the section for socioeconomic metabolism section and fellow MFA practitioners,
A large number of datasets are being compiled and produced as part of material flow analysis (MFA) research, but many of them are not available or cumbersome to extract (pdf, lacking systems context). For this reason, researchers often have to spend too much time searching for and formatting data sets, which means that valuable time is lost in evaluation, quality control, uncertainty analysis and documentation of their own data products.
As a research community, we should strive to become better at integrating (i.e., combining, reusing, improving, sharing, archiving) our data.
The SEM section board believes that we can find a healthy balance between data formatting standards that are too restrictive and too loose. Standards, which allow for both: flexible research design and the development of a cumulative knowledge base.
To advance interoperability of MFA data and prepare or field for the increased use of automated data processing, the current MFA section board drafted a document entitled "Guidelines for Data Modelling and Integration for Industrial Ecology/Material Flow Analysis/Socioeconomic Metabolism". This document shall serve as community-wide guideline in the future. It is hereby put out for review by the community members.
The draft is available under
We solicit feedback and input from the SEM community members on the content and structure of this document as well as on the specific questions listed and highlighted in the draft. Please use the suggestion mode when adding new text.
The plan is to discuss all feedback in the SEM section board and announce a refined version of the guideline document to the community later this year.
Please submit your feedback by the end of July (July 31).
As part of the process, we also started compiling relevant information about classifications for materials, processes, products, and regions into an open repository: https://github.com/IndEcol/SEM_classifications