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

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.

Use of Semantic Technologies to Inform Progress Toward Zero-Carbon Economy

“…However, datasets vary in the completeness and format of this metadata. A general data model for resource data has been proposed [16] which is largely sufficient to meet these requirements. The main barrier to allow its use with Semantic Technologies is the formalisation into a proper ontology which exploits the characteristics of this data model.…”

“…To allow quantified data points on resource use to be expressed in RDF, we build on the data model proposed by Pauliuk et al [16]. This describes three components of a data point: value, metadata, and "system location".…”

“…In addition, the lack of well-defined data models for this type of data is limiting to data reuse and holding back academic research [19,9]. While progress has been made in developing shared data models [17,18,11,8] and data catalogues [16,14], which improve access to and reuse of relevant datasets, they do not yet confront the fundamental challenge of resolving conflicts where individual datasets are defined in inconsistent ways.…”

Winners of the 2019 Graedel Prizes: The Journal of Industrial Ecology Best Paper Prizes

“…Seven of the 10 nominated papers were in the senior first author category—and after the first round of judging, five of these were particularly close. These five, in alphabetical order, were: a "big picture" examination of infrastructure from a complex adaptive systems perspective in relation to changes to the Anthropocene (Chester, Markolf, & Allenby, 2019); a detailed, bottom‐up analysis of consumption‐induced impacts of Swiss households, employing machine learning techniques (Froemelt, Buffat, & Hellweg, 2019); an assessment of circularity in the European Union (EU) economy using economy‐wide material flow accounting integrated with waste flows, recycling, and downcycled materials (Mayer et al., 2019); a practical paper on generalized data structures for industrial ecology, including taxonomy and implementation (Pauliuk, Heeren, Hasan, & Müller, 2019); and an assessment of the potential environmental impacts of future global metal extraction, to 2050, using lifecycle‐based methodology (Van der Voet, Van Oers, Verboon, & Kuipers, 2019). Two excellent papers on the positive impacts of environmental disclosures (Hora & Subramanian, 2019) and a typology for defining boundaries for recycling by manufacturing firms (Magnusson, Andersson, & Ottosson, 2019) completed the seven nominations.…”

ODYM—An open software framework for studying dynamic material systems: Principles, implementation, and data structures

“…The data model described here was generalized by Pauliuk, Heeren, Hasan, and Müller () to cover a broad spectrum of datatypes regularly occurring in quantitative industrial ecology research.…”