Abstract:
In the year 2015, 196 countries signed the Paris Agreement, which aims at keeping the rise in mean global temperature below 2◦C above pre-industrial levels. Governments have since launched awareness campaigns and tightened regulations, motivating companies and governmental organizations to reduce their direct greenhouse gas (GHG) emissions and the indirect emissions of their value chains. To monitor and report on GHG emissions, companies follow standardized methodologies which today remain costly, time-consuming, and require extensive human expertise. In this paper, we present a Knowledge Graph (KG) that forms the semantic backbone of an interdisciplinary research project that aims to significantly reduce the time and effort that environmental accounting experts spend gathering relevant data and validating it. To facilitate data gathering, instead of proposing the creation of a new standard, we created ontologies and management tools for three of the most common GHG data formats—ILCD, EcoSpold01, and EcoSpold02—and we propose a bridge ontology to seamlessly query data expressed in either of these formats. To take advantage of already widely-used ontologies, increase interoperability, and integrate expert knowledge, we follow the Simplified Agile Methodology for Ontology Development to create the WISER ontologies, which are part of the proposed KG and have been created to permit automatic responses to requests by environmental scientists and to capture their domain knowledge. To demonstrate the effectivity of our KG-based approach, we present a tool for data gathering that has been validated by environmental accounting experts. The proposed KG aims at decreasing the effort required for GHG emissions reporting while increasing its transparency and reproducibility. It furthermore democratizes access to GHG emissions data for environmental accounting experts, companies, auditing authorities, and regulatory bodies.
