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Chemistry Knowledge Graph - marine, air quality and nanoparticles

Chemistry Knowledge Graph - marine, air quality and nanoparticles

This showcase entails CMCL’s chemistry knowledge graph (KG) and provides a consistent framework to store, access and interpret vastly growing chemical data, marine emissions data, location data and air quality data, in an intelligent manner using the DOME 4.0 ecosystem. CMCL will establish semantic interoperability between a variety of data sources (ship location/positioning databases, marine nanoparticle emissions software, air quality - dispersion modelling software, data-based surrogate model generation software). To achieve this interoperability across multiple domains CMCL will employ and extend its existing ontologies (Ontokin); its detailed (mesoscopic and continuum) emissions prediction software, kinetics; its data-based model development toolkit, MoDS. Through the course of the 4-year project, CMCL will develop web-based software agents to work on the data from multiple sources.


For example, an automated service to identify best quantum chemistry data from existing marketplaces or databases will be developed to feed the thermodynamic quantities for gas phase species that are used in emissions prediction models. The dispersion models will in turn utilise this information to provide localised air quality measures, in particular the particulates in terms of mass and number concentration. The following metrics will be tracked: 1) The integrated MoDS-kinetics software and CMCL’s chemistry KG can offer a new product for predicting regional air quality. 2) Using the temporal KG, improved decision making for the development of new marine powertrains will be assessed. 3) Data transactions from multiple sources via DOME 4.0 will be leveraged to reduce development costs of marine manufacturing technologies. 4) Applicability of the developed infrastructure to nanoparticles manufacturing (carbon black, silicon, zinc oxide, etc.).


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