Guidelines for data modeling and data integration for material flow analysis and socio-metabolic research

摘要: • General data model for MFA (Pauliuk et al. 2019), based on multi-dimensional data cube model (https://en. wikipedia. org/wiki/OLAP_cube) and data commons prototype(http://www. database. industrialecology. unifreiburg. de/) with a larger number of formatted MFA datasets and reports of difficulties that can occur when formatting data ( http://www. database. industrialecology. unifreiburg. de/resources/DataModel_SEM_IEDC_FAQ. pdf)• A large number of openly available datasets, including the Yale Stocks and Flows database (Myers et al. 2019), the recently published building material composition database (Heeren and Fishman 2019), the Metabolism of Cities database (https://metabolismofcities. org/resources/data/datasetoverview), or the UNEP IRP MFA database (https://www. resourcepanel. org/globalmaterial-flows-database) can already be used by the community. They were mapped to a general data model and are (partly) available in the new format (Fig. 1), which gives an example of how data exchange in the community can look like.• BONSAI–The Big Open Network for Sustainability Assessment Information: A network of researchers dedicated to creating an open source database and toolchain for supply chain analysis, more specifically integrating inputoutput/supply-and-use data with product-specific process flow data. For more information, visit https://bonsai. uno/.