An Open Source Dataset and Ontology for Product Footprinting

Abstract

Product footprint describes the environmental impacts of a product system. To identify such impact, Life Cycle Assessment (LCA) takes into account the entire lifespan and production chain, from material extraction to final disposal or recycling. This requires gathering data from a variety of heterogeneous sources, but current access to those is limited and often expensive. The BONSAI project, instead, aims to build a shared resource where the community can contribute to data generation, validation, and management decisions. In particular, its first goal is to produce an open dataset and an open source toolchain capable of supporting LCA calculations. This will allow the science of lifecycle assessment to perform in a more transparent and more reproducible way, and will foster data integration and sharing. Linked Open Data and semantic technologies are a natural choice for achieving this goal. In this work, we present the first results of this effort 3 : (1) the core of a comprehensive ontology for industrial ecology and associated relevant data; and (2) the first steps towards an RDF dataset and associated tools to incorporate several large LCA data sources.

Transparent Integration and Sharing of Life Cycle Sustainability Data with Provenance

“…Given the complex nature of the production chain of any product, to perform reliable LCSA, analysts need access to data from a variety of heterogeneous sources across countries, scientific and economic sectors, and institutions. To enable the integration of diverse data sources, previous efforts [6] designed an ontology and corresponding open database to allow multiple organizations and researchers to share LCSA data and to make use of such data to produce analysis and models. These efforts lay the foundations of a platform where domain experts can both freely access data to compute and produce new models, but also re-share their results within the same framework.…”

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

“…While the ontology design patterns have elements of overlap with the ontology presented here, especially with regard to "spatio-temporal scope" of processes, their concepts are tightly bound to the LCA modelling approach. More recently, the BONSAI project [8] has been developing a broader ontology which aims to catalogue a range of datasets relevant to sustainability assessment. They acknowledge the problems of working with actual data points defined with differing terminology, but also stop short of harmonising individual data points.…”

“…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.…”

Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food

“…mass, volume, and calories), and assumptions made are not always clear or well-documented, make it difficult for nonexperts to interpret, use, and apply this content to more comprehensive studies like those about healthy and sustainable food. Recently, Ghose et al, (2019) and Ghose (2020) proposed NLP methods for semantic investigation of LCA databases. However, while the sustainability data might be available for individual ingredients, it is still rare for entire recipes.…”