Events, Processes, and their Descriptions

In this tutorial I will introduce a novel ontological theory of events published in a recent paper on Applied Ontology, whose central tenet is the Aristotelian distinction between the object that changes and the actual subject of change, which is what we call an individual quality. While in the Kimian tradition events are individuated by a triple <o, P, t>, where o is an object, P a property, and t an interval of time, for us the simplest events are qualitative changes, individuated by a triple <o, q, t>, where q is an individual quality inhering in o or in one of its parts. Detaching the individuation of events from the property they exemplify results in a fine-grained theory that keeps metaphysics and semantics clearly separate, and lies between the multiplicative and the unitarian approaches. 

After presenting this ontological account of simple events as qualitative changes, I will focus on the event descriptions occurring in natural language, which usually  refer to complex, cognitively relevant clusters of co-occurring simple events, which exhibit a synchronic structure depending on the way they are described. Contra Bennett, who famously argued that the semantics of event names ultimately depends on “local context and unprincipled intuitions”, I will show how the lexicon provides systematic principles for individuating such clusters and classifying them into kinds. In particular, this allows to clarify the semantics of verbal modifiers.

Finally, I will briefly discuss the difference between events and processes, which according to a very recent paper are conceived as variable embodiments of events, showing ho how these cognitive and linguistic mechanisms governing the way we describe events also work in the case of processes.


  • Nicola Guarino

    Nicola Guarino is a retired research associate at the Institute of Cognitive Sciences and Technologies of the Italian National Research Council (ISTC-CNR), and former director of the ISTC-CNR Laboratory for Applied Ontology (LOA) based in Trento. He has been playing a leading role in the ontology field, developing a strongly interdisciplinary approach that combines together Computer Science, Philosophy, and Linguistics. Among the most well known results of his lab, the OntoClean methodology and the DOLCE foundational ontology. He has been founder and co-editor-in-chief  of the Applied Ontology journal, founder and former president of the International Association for Ontology and its Applications (IAOA), and editorial board member of Int. Journal of Semantic Web and Information Systems and Journal of Data Semantics. He is also a fellow of ER and the European Association for Artificial Intelligence (EurAI). He got the Peter Chen Award in 2023. On the theoretical side,  his current research interests are focusing on the ontological foundations of knowledge representation and conceptual modeling, and specifically the ontology of events and relationships. On the application side he is focusing on enterprise modeling, services, and manufacturing. His publications got 31,000+ citations, with H-index=55 according to Google Scholar.

DOLCE in OWL: A tutorial with case studies in industrial engineering

Foundational ontologies play a prominent role in ontology-based conceptual and data modeling by offering conceptually and logically well-founded top-level architectures that can be extended to meet specific application needs. Due to their complexity, it is common for both novices and experts in the field to seek theoretical knowledge about them and practical competencies regarding their use. The core objective of the tutorial is to balance these dimensions, introducing participants to various aspects of the theoretical background and practical use of foundational ontologies. In particular, the tutorial will focus on the foundational ontology DOLCE - Descriptive Ontology for Linguistic and Cognitive Engineering and its recent release in the Web Ontology Language (OWL). Attendees will gain introductory knowledge about DOLCE, as well as hands-on experience with its OWL release consisting of two modules: DOLCEbasic and DOLCEnaryRel. The first module includes the taxonomy of classes along with OWL axioms to characterize the extension of the classes. The second module, built upon the basic module, incorporates the reification of n-ary relationships to maintain the ability to represent temporalized relations. This modular architecture aims to facilitate the OWL extension of DOLCE for specific research and application purposes. Throughout the tutorial, we will introduce modeling examples from the field of industrial engineering, ontology patterns to represent them, as well as tools for manipulating datasets formalized according to DOLCE OWL using the SPARQL query/update language.


  • Emilio Sanfilippo

    Dr. Emilio M. Sanfilippo is a researcher at the ISTC Institute of the National Research Council of Italy (CNR). His research focuses on conceptual and methodological aspects related to the use of ontologies in industrial engineering, as well as humanities research areas like literary studies and musicology. Since 2019, Emilio has been involved in teaching activities at the University of Tours (France). Additionally he is actively involved in the IAOA. He participated in various European and national research projects. As part of the European project OntoCommons - Ontology-driven data documentation for Industry Commons (Horizon 2020), he conducted a 2-hour tutorial on modeling aspects using the DOLCE ontology.

  • Walter Terkaj

    Dr. Walter Terkaj is a Senior Researcher at STIIMA Institute of the Italian CNR. His main research interests are related to the study and modeling of production systems aimed at supporting the design, performance evaluation, management, and control activities, also using Semantic Web technologies. He is also involved in teaching activities at Politecnico di Milano, being formerly Adjunct Professor. Walter participated in several European and national research projects, and is currently scientific responsible for the Erasmus+ project XREN. He published more than 70 articles in international journals, books, and conference proceedings.


GitHub Applied Ontology Lab:

Web Application OntoGuiWeb:


Web Protégé:


Generating ontology conceptualization and pattern libraries with Chowlk

Ontology conceptualization is a key activity as it drives the final implementation. Usually, developers generate graphical representations to carry out this activity as it is more convenient to provide an overall idea of the model, and it is a powerful tool to communicate with domain experts. While the conceptualization might be independent of the implementation language, it is advisable to use a notation as close as possible to the ontology implementation language to avoid ambiguity and reduce effort during the implementation. To this end, the Chowlk framework provides a UML-based notation (published at VOILA23) and a converter (published at ESWC22) in order to conceptualize and implement OWL ontologies graphically. This tutorial’s learning outcomes are: 1) to know the Chowlk framework resources available; 2) to know how to use the Chowlk notation to represent OWL ontologies and the converter to generate the ontology OWL code; and 3) to learn how to use draw.io to generate their own patterns libraries. The tutorial will be organized in 2 sessions, the first one dedicated to explain the resources available and how to use them (learning outcomes 1 and 2) and the second dedicated to the creation of ontology pattern libraries (learning outcome 3).


  • María Poveda-Villalón

    Dr. María Poveda-Villalón is an associate professor at the Artificial Intelligence Department  of the Universidad Politécnica de Madrid and is also part of the Ontology Engineering Group research lab. Her research activities focus on Ontological Engineering, Ontology Evaluation, Knowledge Representation and the Semantic Web. She has contributed to the ontology engineering field developing methodologies and tools like OOPS! (Ontology Pitfall Scanner!) which has been broadly adopted by the community, the LOT methodology for building ontologies and the Chowk framework for ontology conceptualization and implementation. She has worked in the context of Spanish research projects as well as in European. She has contributed to the organization of the "Linked Data in Architecture and Construction Workshop" since 2015 edition, the "13th OWL: Experiences and Directions Workshop and 5th OWL reasoner evaluation workshop" in 2016, the Workshop on Ontology Patterns (WOP) in 2019 and 2022, the "Linked Energy Data Vocamp" in 2015 and she has organized the 2nd Summer School  of Linked Data in Architecture and Construction. Her teaching activities involve teaching semantic web and ontological engineering in different courses at official degrees, masters courses, MOOCs and online masters as well to deliver courses to the administration and private companies. She has carried out similar tutorials as “Catching up with ontological engineering. To git-commit and beyond” at EKAW2018 and “Integrating ontological development with software engineering trends” FDL2019. 

    ORCID: https://orcid.org/0000-0003-3587-0367 

  • Raúl García-Castro

    Raúl García-Castro is an Associate Professor in the Artificial Intelligence Department at Universidad Politécnica de Madrid (UPM). Having spent three years working as a software engineer, since he graduated in Computer Science in 2003 he has been working at UPM in the Ontology Engineering Group in more than twenty European and Spanish research projects, being Principal Investigator in six of them. His research focuses on ontological engineering, ontology-based application integration, and semantic interoperability. He has authored more than 150 publications and regularly participates in standardization and in the conferences and workshops that are most relevant in his field. He has a strong interest and expertise in ontological engineering, where he has contributed in topics such as ontological engineering methodologies (with the Linked Open Terms methodology), ontology testing (with the Themis suite), or ontology visualization (with the Chowlk notation). Furthermore, he has developed ontologies in many projects and in standardization bodies (W3C, ETSI). His teaching activities involve teaching semantic web and ontological engineering in different courses at official degrees, masters courses, MOOCs and online masters as well to deliver courses to the administration and private companies.

    ORCID: https://orcid.org/0000-0002-0421-452X

  • Sergio Carulli-Pérez

    Sergio Mario Carulli-Pérez studied at the Universidad Politécnica de Madrid (UPM), where he graduated in Mathematics and Computer Science. Furthermore, not satisfied with his studies, he also obtained a master's degree in Data Science at the UPM. After finishing the master's degree, he started working as a researcher at the Ontology Engineering Group (OEG), which is a laboratory affiliated to the UPM where he has been working since 2022. His responsibilities include developing ontologies to support artificial intelligence integration and working as a full stack developer providing different services for the OEG. In the field of ontology development, he has developed an extension to the Smart Appliances REFerence (SAREF) ontology called SAREF4GRID, which is an extension for the electric grid domain. Moreover, in the full stack developer field, he has developed Chowlk, an application that allows to create the OWL implementation of an ontology from its conceptualisation. 

Knowledge Engineering for Hybrid Intelligence

Hybrid Intelligence (HI) is a rapidly growing field aiming at creating collaborative systems where humans and intelligent machines synergetically cooperate in mixed teams towards shared goals. A clear characterization of the tasks and knowledge exchanged by the agents in HI applications is still missing, hampering both standardization and reuse when designing new HI systems. Knowledge Engineering (KE) methods have been used to solve such issue through the formalization of tasks and roles in knowledge-intensive processes, formerly often for Expert Systems. In this tutorial we will introduce how KE methods can be applied to HI scenarios, and specifically how common, reusable elements such as knowledge roles, tasks and subtasks can be identified in contexts where symbolic, subsymbolic and human-in-the-loop components are involved. In this tutorial we will first introduce the well-known CommonKADS methodology, and recent extensions to make it usable to hybrid scenarios. In a hands-on part, we will then use this methodology to analyze HI projects and identify common tasks.

More details about the tutorial can be found here.


  • Ilaria Tiddi

    ilaria Ilaria Tiddi is an Assistant Professor in Hybrid Intelligence at the Knowledge in AI (KAI) group of the Vrije Universiteit Amsterdam (NL). Her research focuses on creating systems that generate complex narratives through a combination of semantic technologies, open data and machine learning, applied mostly in scientific and robotics scenarios.

  • Victor de Boer

    victor Victor de Boer is an Assistant Professor at the User-Centric Data Science group at the Computer Science department of the Vrije Universiteit Amsterdam (VU) and a senior research fellow at Netherlands Institute for Sound and Vision. In his research, he combines Knowledge Representation and Machine Learning with Human-Computer Interaction to tackle research challenges in various domains.

  • Stefan Schlobach

    stefan Stefan Schlobach is an Associate Professor at the Vrije Universiteit Amsterdam. He is leading the Knowledge in Artificial Intelligence group in the Department of Computer Science. Dr. Schlobach has published over 100 research papers in the area of Knowledge Engineering and Knowledge Representation and Reasoning.