Workshop: 11th International Workshop on Formal Ontologies meet Industry (FOMI)
FOMI is an international forum and the flagship of the Industry and Standards Technical Committee (ISTC) of IAOA. Researchers and practitioners are invited to participate in the FOMI workshop to analyse and discuss issues across methods, theories, tools and applications based on formal ontologies, knowledge modeling and the semantic dimension of information. The aim is to collect, discuss and share lessons learned by implementing theoretical views and lessons learned by theoretical/ontological analyses of existing application systems.
Workshop: 4th Workshop on Foundational Ontology (FOUST IV)
Foundational ontologies are attempts to systematise categories of thought or reality which are common to all or almost all subject-matters. Commonly considered examples of such categories include ‘object’, ‘quality’, ‘function’, ‘role’, ‘process’, ‘event’, ‘time’, and ‘place’. Among existing foundational ontologies, there is both a substantial measure of agreement and some dramatic disagreements. There is currently no uniform consensus concerning how a foundational ontology should be organised, how far its ‘reach’ should be (e.g., is the distinction between physical and non-physical entities sufficiently fundamental to be included here?), and even what role it should play in relation to more specialised domain ontologies. The purpose of the FOUST workshop is to provide a forum for researchers to present work on specific foundational ontologies as well as foundational ontologies in general and their relations to each other and to the wider ontological enterprise.
Workshop: The International Workshop on Ontologies and Conceptual Modelling (OntoCom)
The International Workshop on Ontologies and Conceptual Modelling (OntoCom) concerns the practical and formal application of ontologies to conceptual modelling. While models pervade the information systems lifecycle from requirements to implementation, there appears to be a lack of theoretical foundation in the way that models are developed. As a result it is quite common for practitioners, even working together, to produce different representations of the same real world domain or system. Conversely, a preferred approach would be one in which IS practitioners have the necessary conceptual tools to enable them to accurately represent the things that exist in the real world. Foundational or upper ontologies have the potential to resolve the difficult problems that derive from a lack of a consistent and sound ontological theory. The benefits that can derive from the application of a foundational ontology include improved mapping to the real world domain, increased level of communication and understanding among stakeholders, model reuse, semantic integration and interoperability and increased overall efficiency and effectiveness of information systems development and evolution. OntoCom is intended to be highly interactive and bring together academics and practitioners interested in foundational ontologies and their meta-ontological choices.
Workshop: Deep Learning meets Ontologies and Natural Language Processing
Deep Learning (DL) meets Natural Language Processing (NLP) to solve human language problems for further applications, such as information extraction, machine translation, search and summarization. Previous works has attested the positive impact of domain knowledge on data analysis and vice versa. In this context, ontology is a structured knowledge representation that facilitates data access (data sharing and reuse) and assists the DL process as well. DL meets recently ontologies and tries to model data representations with many layers of non-linear transformations. The combination of DL, ontologies and NLP might be beneficial for different tasks such as ontology learning, semantic graph embeddings, summarization, semantic role labeling. This workshop aims at demonstrating recent and future advances in semantic rich deep learning by using Semantic Web and NLP techniques which can reduce the semantic gap between the data, applications, machine learning process, in order to obtain a semantic-aware approaches.
Workshop: Data meets Applied Ontologies in Explainable Artificial Intelligence (DAO-XAI)
The interest in Explainable AI has led to a plethora of new approaches for explanations of black-box models, for both autonomous and human-in-the-loop systems, aiming to achieve explainability without sacrificing system performances. Only a few of these approaches, however, focus on how to integrate and use domain knowledge to let decisions made by these systems be more explainable and understandable by human users. The objective of the DAO-XAI workshop is to provide stakeholders from the academia, industry, and public organisations opportunities to present their latest developments in explainable and trustworthy decision making, and in approaches that integrate symbolic and non-symbolic reasoning. The workshop will be a great opportunity to synthesise new insights, and disseminate knowledge across field boundaries to promote interaction between these stakeholders.
Workshop: Ontology of Social, Legal and Economic Entities (SoLEE 2020)
Understanding the ontological nature of social, legal and economic concepts and institutions is crucial for providing principled modelling in many important domains such as enterprise modelling, business processes, and social ontology. A significant number of fundamental concepts that are ubiquitous in economics, social, and legal sciences – such as value, risk, capability, good, service, exchange, transaction, competition, social norm, group, institution – have only recently been approached from a specifically ontological perspective. It is therefore important to offer a venue to gather the recent contributions to this topic. The workshop encourages submissions on both theoretical and methodological issues in the use of ontologies for modelling social, legal and economic concepts and institutions, as well as submissions on concrete use of ontologies in application for these domains.
Workshop: Ontologies for Autonomous Robotics (ROBONTICS 2020)
ROBONTICS 2020 is the first edition of a workshop aimed at providing a platform to disseminate research into robot autonomy enabled by knowledge-driven approaches, and in particular formal ontologies. Its purpose is to foster communication between the fields of robotics, ontology, and knowledge representation and reasoning, to match open problems to promising approaches, and to review progress in knowledge-driven robotics.
Tutorial : An Introduction to the BORO Foundation and its Industrial Applications through its Modelling Approaches
Lecturers: Chris Partridge, Sergio de Cesare, Pawel Garbacz, Andrew Mitchell
This interactive tutorial introduces the Business Object Reference Ontology (BORO) and its associated methodology (bCLEARer) to re-engineering legacy data and systems through working hands-on with BORO Modelling approaches. BORO is an extensionalist foundational ontology that has been widely applied in industry. Examples include the oil and gas, finance and defence sectors. The modelling approaches that will be used are Space-Time Maps and the associated STM Domain Models, Ontological Euler Diagrams and BORO UML (BUML). The organisers will present the modelling approaches in a way that reveals the ontological foundations of these approaches.
Tutorial: Knowledge acquisition for ontology development
Lecturer: Mara Abel
Ontology development is a result of collecting shared consensual knowledge applied to solve a large range of tasks in a community of practice. Ontologies differ from knowledge models in the sense that the semantic is not based on the software application itself, but in the common acquaintance of the terminology among a community under the philosophical view about world understanding. This tutorial explains the distinction between knowledge models and ontologies as a motivation for applying distinctive approaches for knowledge acquisition and modeling for both types of models. It introduces practical steps and techniques for knowledge elicitation with the focus of producing well-founded domain ontologies for industrial projects. We discuss how to select the professionals and legacy material that will be the source of knowledge. We present techniques for literature analysis, open and structure interviews for knowledge elicitation, data analysis for ontology modeling, and preliminary specification of the concepts. The content considers and discusses previously developed cases on oil and gas industry. We aim the explanation would be useful for general use in conceptual modeling tasks.
Tutorial: Verbal and non-verbal predication across the grammatical-conceptual divide
Lecturers: Bridget Copley, Isabelle Roy
Studying natural language data without a knowledge of grammar is like cooking without labels on the spices—it’s quite possible, but it’s helpful to know which spice is in which bottle. That is, it’s helpful to know that a predicate in language gives us information about the kind of entity its argument is. In this tutorial we provide an introduction to the use of verbal and non-verbal predication to study ontology at the grammatical-conceptual divide. In the morning we present some basic tools (natural language syntax, architecture, and compositional semantics), and in the afternoon we zoom in on selected topics. No linguistics background required.