MOMo - Modular Ontology Modeling - is an ontology (and by extension: knowledge graph) design methodology that incorporates as important principles a wide range of methods that have evolved out of a quarter century of Semantic Web research. This includes strong axiomatization with formal logic, design patterns, modularity, capturing of human conceptualizations, visual collaborative modeling in a diverse team, vocabulary and documentation guidelines, etc. In addition, from its inception MOMo was designed to be a Knowledge Graph and Ontology Engineering approach that is amenable for partial automation. In this presentation, we will talk about the principles that lead to MOMo and are incorporated in it, as well as recent progress regarding the use of LLMs for assisting in Knowledge Graph and Ontology Engineering.
Pascal Hitzler is University Distinguished Professor and endowed Lloyd T. Smith Creativity in Engineering Chair at the Department of Computer Science at Kansas State University, one of the Directors of the Institute for Digital Agriculture and Advanced Analytics (ID3A), and Director of the Center for Artificial Intelligence and Data Science (CAIDS) Until July 2019 he was endowed NCR Distinguished Professor, Brage Golding Distinguished Professor of Research, and Director of Data Science at the Department of Computer Science and Engineering at Wright State University in Dayton, Ohio, U.S.A. He is director of the Data Semantics (DaSe) Lab. From 2004 to 2009, he was Akademischer Rat at the Institute for Applied Informatics and Formal Description Methods (AIFB) at the University of Karlsruhe in Germany, and from 2001 to 2004 he was postdoctoral researcher at the Artificial Intelligence institute at TU Dresden in Germany. In 2001 he obtained a PhD in Mathematics from the National University of Ireland, University College Cork, and in 1998 a Diplom (Master equivalent) in Mathematics from the University of Tübingen in Germany. His research record lists over 400 publications in such diverse areas as neuro-symbolic artificial intelligence, semantic web, knowledge graphs, knowledge representation and reasoning, denotational semantics, and set-theoretic topology. His research is highly cited. He was founding Editor-in-chief of the Semantic Web journal, the leading journal in the field, and is founding Editor-in-chief of the new Neurosymbolic Artificial Intelligence journal, and of the IOS Press book series Studies on the Semantic Web. He is co-author of the W3C Recommendation OWL 2 Primer, and of the book Foundations of Semantic Web Technologies by CRC Press, 2010, which was named as one out of seven Outstanding Academic Titles 2010 in Information and Computer Science by the American Library Association's Choice Magazine, and has translations into German and Chinese. He is on the editorial board of several journals and book series and a founding steering committee member of the Neural-Symbolic Learning and Reasoning Association and the Association for Ontology Design and Patterns, and he frequently acts as conference chair in various functions. For more information about him, see http://www.pascal-hitzler.de.
Oscar Corcho is a Full Professor at the Universidad Politécnica de Madrid (UPM), where he co-leads the Ontology Engineering Group in the Department of Artificial Intelligence. His research focuses on the Semantic Web, Linked Data, and Ontological Engineering, bridging foundational work with applied projects in e-Science and Open Science. He has coordinated multiple EU and national research projects, supervised numerous PhD theses, and co-founded the open-data company LocaliData. A recipient of major awards—including the Juan López de Peñalver Prize—he is co-author of influential books such as *Ontological Engineering* and has published extensively in leading venues. Corcho is also active in scientific outreach and citizen-science initiatives like STARS4ALL.