Conceptual modeling is a complex and demanding task. It is a task centered around the challenge of representing a portion of the world in a way that is objective, understandable, shareable, and reusable by a community of practitioners, who rely on models to design and implement software or to clarify the concepts within a given domain. The difficulty of conceptual modeling stems from the inherent limitations of human representation abilities, which cannot fully capture the infinite richness and diversity of the world, nor the endless possibilities for description enabled by language. Significant effort has been invested in addressing these challenges, particularly in the creation of effective and reusable conceptual models, which have presented numerous difficulties. This paper explores conceptual modeling from a philosophical standpoint, proposing that conceptual models should not be viewed merely as the static representational output of an a priori activity, subject to modification only during a preliminary design phase. Instead, they should be seen as dynamic artifacts that require continuous design, adaptation, and evolution from their inception to their application, which may account for multiple purposes. The paper seeks to highlight the importance of understanding conceptual modeling primarily as an act of communication, rather than just a process of information transmission. It also aims to clarify the distinction between these two aspects and to examine the potential implications of adopting a communicative approach to modeling . These implications extend not only to the tools and methodologies used in modeling but also to the ethical considerations that arise from such an approach.

Multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language’s constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. They may support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis if built following generally accepted quality requirements for scientific data management. More specifically, not unlike scientific (meta)data, models should be shared according to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. The catalog, publicly available at https://w3id.org/ontouml-models, currently includes over one hundred and forty models, developed in a variety of contexts and domains.