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A general data model for socioeconomic metabolism and its implementation in an industrial ecology data commons prototype

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  • Stefan Pauliuk
  • Niko Heeren
  • Mohammad Mahadi Hasan
  • Daniel B. Müller

Abstract

Until this day, data in industrial ecology (IE) have been commonly seen as existing within the domain of particular methods or models, such as input–output, life cycle assessment, urban metabolism, or material flow analysis data. This artificial division of data into methods contradicts the common phenomena described by those data: the objects and processes in the industrial system, or socioeconomic metabolism (SEM). A consequence of this scattered organization of related data across methods is that IE researchers and consultants spend too much time searching for and reformatting data from diverse and incoherent sources, time that could be invested into quality control and analysis of model results instead. This article outlines a solution to two major barriers to data exchange within IE: (a) the lack of a generic structure for IE data and (b) the lack of a bespoke platform to exchange IE datasets. We present a general data model for SEM that can be used to structure all data that can be located in the industrial system, including process descriptions, product descriptions, stocks, flows, and coefficients of all kind. We describe a relational database built on the general data model and a user interface to it, both of which are open source and can be implemented by individual researchers, groups, institutions, or the entire community. In the latter case, one could speak of an IE data commons (IEDC), and we unveil an IEDC prototype containing a diverse set of datasets from the literature.

Suggested Citation

  • Stefan Pauliuk & Niko Heeren & Mohammad Mahadi Hasan & Daniel B. Müller, 2019. "A general data model for socioeconomic metabolism and its implementation in an industrial ecology data commons prototype," Journal of Industrial Ecology, Yale University, vol. 23(5), pages 1016-1027, October.
  • Handle: RePEc:bla:inecol:v:23:y:2019:i:5:p:1016-1027
    DOI: 10.1111/jiec.12890
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    Cited by:

    1. Omar Isaac Asensio & Camila Z. Apablaza & M. Cade Lawson & Sarah Elizabeth Walsh, 2022. "A field experiment on workplace norms and electric vehicle charging etiquette," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 183-196, February.
    2. Junming Zhu, 2020. "Suggested use? On evidence‐based decision‐making in industrial ecology and beyond," Journal of Industrial Ecology, Yale University, vol. 24(5), pages 943-950, October.
    3. Sileryte, Rusne & Sabbe, Arnout & Bouzas, Vasileios & Meister, Kozmo & Wandl, Alexander & van Timmeren, Arjan, 2022. "European Waste Statistics data for a Circular Economy Monitor: opportunities and limitations from the Amsterdam Metropolitan Region," OSF Preprints da6f2, Center for Open Science.
    4. Agneta Ghose & Matteo Lissandrini & Emil Riis Hansen & Bo Pedersen Weidema, 2022. "A core ontology for modeling life cycle sustainability assessment on the Semantic Web," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 731-747, June.
    5. Seiya Maki & Satoshi Ohnishi & Minoru Fujii & Naohiro Goto & Lu Sun, 2022. "Using waste to supply steam for industry transition: Selection of target industries through economic evaluation and statistical analysis," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1475-1486, August.
    6. Fernando Aguilar Lopez & Romain G. Billy & Daniel B. Müller, 2022. "A product–component framework for modeling stock dynamics and its application for electric vehicles and lithium‐ion batteries," Journal of Industrial Ecology, Yale University, vol. 26(5), pages 1605-1615, October.
    7. Chris Kennedy & Reid Lifset, 2020. "Winners of the 2019 Graedel Prizes: The Journal of Industrial Ecology Best Paper Prizes," Journal of Industrial Ecology, Yale University, vol. 24(5), pages 940-942, October.
    8. Stefan Pauliuk & Niko Heeren, 2020. "ODYM—An open software framework for studying dynamic material systems: Principles, implementation, and data structures," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 446-458, June.
    9. P. James Joyce & Anna Björklund, 2022. "Futura: A new tool for transparent and shareable scenario analysis in prospective life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 134-144, February.
    10. Hanspeter Wieland & Manfred Lenzen & Arne Geschke & Jacob Fry & Dominik Wiedenhofer & Nina Eisenmenger & Johannes Schenk & Stefan Giljum, 2022. "The PIOLab: Building global physical input–output tables in a virtual laboratory," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 683-703, June.
    11. Jan Streeck & Stefan Pauliuk & Hanspeter Wieland & Dominik Wiedenhofer, 2023. "A review of methods to trace material flows into final products in dynamic material flow analysis: From industry shipments in physical units to monetary input–output tables, Part 1," Journal of Industrial Ecology, Yale University, vol. 27(2), pages 436-456, April.

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