Resources
A Human-centric Ontology Evaluation Process (HERO)
HERO is a Human-centric ontology Evaluation pROcess that guides ontology engineers through the relevant steps to be taken in human-in-the-loop ontology evaluation campaigns and can thus reduce the likelihood of crowd-sourced errors or biases and improve the reliability of the results at the design phase of the campaign. The activities, part of HERO can be divided into three main stages: preparation, execution, and follow-up analysis of the crowd-sourced campaign.
Semantics-based Explanation of Cyber-physical Systems (SENSE)
SENSE was developed to improve the transparency, explainability, and trustworthiness of complex cyber-physical systems (CPSs) for engineers, operators, and end-users. It provides an open-source technology stack together with the SENSE ontology, enabling the systematic generation of meaningful, context-aware explanations for CPS behaviour. SENSE is designed to guide practitioners in understanding, deploying, and assessing explainable CPS solutions.
Semantic-Web Machine Learning System (SWeMLS)
Semantic Web Machine Learning Systems (SWeMLS) are the result of a combination between Semantic Web Technologies and an inductive model. More precisely, they describe a system which makes use of Semantic Web knowledge structure as well as machine learning sub-system in order to solve a specific task. The SWeMLS ontology provides a mean for classifying SWeMLS based on a set of its characteristics. We reuse a number of concepts and namespaces from other ontologies as describes in the following sub-section.