2022, Laurenzi, Emanuele

Knowledge Graphs (KGs) have matured as a topical technique that organizations increasingly adopt for structuring knowledge and its subsequent analysis and reasoning as well as for integrating information extracted from different data sources. KGs also play a central role in Artificial Intelligence systems, as their structured knowledge can be used as input to improve predictions of Machine Learning. Yet, one of the main challenges in KGs is the creation and maintenance of structured and formalized knowledge (or ontologies), which requires high expertise in ontology engineering as well as is tedious and time-consuming. In this workshop, I will present AOAME: an Agile and Ontology-Aided Metamodelling Environment, with which ontologies can be automatically created and maintained while easily adapting a modeling language and creating enterprise models. To underpin the explanation of the research approach, a real-world case taken from a recently finished EU project will be implemented in AOAME.

2016-11-02, Kurjakovic, Sabrina, Lammel, Benjamin, Laurenzi, Emanuele, Woitsch, Robert, Hinkelmann, Knut