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Getting WISER
One of the main obstacles that sustainability experts are confronted with when computing recommendations that will allow stakeholders reducing their Greenhouse Gases (GHG) emissions is the availability, easy access, and quality of the data they require to perform accurate assessments of the stakeholder’s activities that emit GHGs. To improve this situation, academics are working on a system that could act as a one-stop-shop for contextualised, rich GHG data. In this project, you will be contributing towards the creation of such a system, working with real-life data in a real-life problem.
Keywords: sustainability, GHG, netzero, semantic technologies, knowledge graph, data analysis
One of the main obstacles that sustainability experts are confronted with when computing recommendations that will allow stakeholders reducing their Greenhouse Gases (GHG) emissions is the availability, easy access, and quality of the data they require to perform accurate assessments of the stakeholder’s activities that emit GHGs. To improve this situation and be able to make a long-lasting impact, researchers from several academic institutions in Switzerland are working on a system that will provide a one-stop-shop for contextualized machine-readable and machine-understandable data in the GHG domain. A central part of this system is a Knowledge Graph (KG) that will act as an interoperability layer among heterogenous data sources. In this project, you will be contributing towards the creation of such a KG, working with real-life data in a real-life problem. Specifically, you will be working on the following activities:
Knowledge Engineering:
Familiarization with sustainability standards and data bases (e.g., ILCD and EcoSpold)
Creation of knowledge models in RDF/OWL
Usage of RDFication tools & explore RML rules for data mapping
Contribute to the creation of a bridging ontology for connecting different database schemas
Data validation:
Creation of SHACL/ShEx shapes for data validation following the sustainability standards
Demonstrator:
Creation of a demonstrator that showcases the advantages of the interoperability layer
One of the main obstacles that sustainability experts are confronted with when computing recommendations that will allow stakeholders reducing their Greenhouse Gases (GHG) emissions is the availability, easy access, and quality of the data they require to perform accurate assessments of the stakeholder’s activities that emit GHGs. To improve this situation and be able to make a long-lasting impact, researchers from several academic institutions in Switzerland are working on a system that will provide a one-stop-shop for contextualized machine-readable and machine-understandable data in the GHG domain. A central part of this system is a Knowledge Graph (KG) that will act as an interoperability layer among heterogenous data sources. In this project, you will be contributing towards the creation of such a KG, working with real-life data in a real-life problem. Specifically, you will be working on the following activities:
Knowledge Engineering:
Familiarization with sustainability standards and data bases (e.g., ILCD and EcoSpold)
Creation of knowledge models in RDF/OWL
Usage of RDFication tools & explore RML rules for data mapping
Contribute to the creation of a bridging ontology for connecting different database schemas
Data validation:
Creation of SHACL/ShEx shapes for data validation following the sustainability standards
Demonstrator:
Creation of a demonstrator that showcases the advantages of the interoperability layer
Contribute to the creation of a Knowledge Graph that is capable of acting as an interoperability layer for GHG emissions data.
Contribute to the creation of a Knowledge Graph that is capable of acting as an interoperability layer for GHG emissions data.
Dr. Kimberly Garcia at kimberly.garcia@unisg.ch
Prof. Dr. Simon Mayer at simon.mayer@unisg.ch
Dr. Kimberly Garcia at kimberly.garcia@unisg.ch Prof. Dr. Simon Mayer at simon.mayer@unisg.ch