Guendalina Righetti, Maria M. Hedblom, Oliver Kutz
- With the increased interest in the notion of embodied cognition and cognitive computing the connection between symbolic methods and the cognitive sciences has come to a developmental halt. However, the success in machine learning and neural networks to model cognitive phenomena does not in itself nullify the usefulness of symbolic approaches. The advancement of artificial intelligence, the understanding of cognitive phenomena can greatly benefit from classic methods in knowledge representations and ontologies. CAOS aims to bridge the gap between cognitive science and the formal methods by providing a platform for researchers in either domain to discuss and present their work.
Martin Glauer, Janna Hastings, Till Mossakowski, Fabian Neuhaus
- Energy, and sustainability more broadly, are increasingly relevant topics in the context of the climate crisis and a rapidly changing world, around which data and research needs to be aggregated. Topics that will be within scope of the proposed workshop include energy systems, sustainability, climate, ecosystems, and associated human socioeconomic impacts and preventative behaviours, including approaches to sustainable development. The workshop will focus on the development of ontologies for these domains as well as applications in which such ontologies are used.
Lucia Gomez Alvarez, Rafael Penaloza, Srdjan Vesic
- This workshop intends to create a space of confluence and a forum for discussion for researchers interested in knowledge diversity in a wide sense, including diversity in terms of diverging perspectives, different beliefs, semantic heterogeneity and others. The importance of understanding and handling the different forms of diversity that manifest between knowledge formalisations (ontologies, knowledge bases, or knowledge graphs) is widely recognised, and has led to the proposal of a variety of systems of representation, tackling overlapping aspects of this phenomenon.
Besides understanding the phenomenon and considering formal models for the representation of knowledge diversity, we are interested in the variety of reasoning problems that emerge in this context, including jointly reasoning with possibly conflicting sources, interpreting knowledge from alternative viewpoints, consolidating the diversity as uncertainty, reasoning by means of argumentation between the sources and pursuing knowledge aggregations among others.
Claudenir M. Fonseca, Jona Thai, Oliver Kutz and Stefano Borgo
- Foundational ontologies are attempts to systematise those 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’. Amongst 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 this 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.
Damion Dooley, Rhiannon Cameron, Lauren Chan, Duccio Cavalieri, Robert Warren, Hande McGinty, Matthew Lange, Fernanda Dorea, Jaspreet Ahuja
- Academic, agricultural and public health agencies are considering the benefits and complexities of adopting ontology in their research and data management and reporting infrastructure. What vocabulary, tool ecosystem and data models are needed to correlate agricultural treatments, nutritional data, eating patterns, biomarkers, pathogens, and phytochemical levels with disease and health phenotypes? This workshop seeks to define the coverage of the different ecological, agricultural, nutritional, dietary, public health, one health surveillance, food security, and trade domains that food-related ontologies are modelling, and the use of data translation tools for bringing legacy data into the ontology fold.
Bart Gajderowicz, Daniela Rozu, Janna Hastings
- Semantic Technologies provide a formal way to represent knowledge in ways that are interpretable by computers and a related technology stack to store, integrate and query information semantically. The purpose of the OSS workshop is to foster communication and strengthen interdisciplinary work at the intersection of semantic technologies and social services. We invite researchers from the Knowledge Representation, Semantic Web, Machine Learning, and Social Science communities to submit theoretical contributions, novel algorithms, artifacts, and tools related to social services. We welcome reports from Social Work practitioners on their experiences using semantic-enabled technologies, best practices, and insights.
Mihai Pomarlan, Mohammed Diab, Stefano Borgo, Alberto Olivares-Alarcos, Daniel Beßler, Robert Porzel, Aldo Gangemi
Many research projects, motivated by applications in healthcare assistance, logistics, autonomous driving etc, aim to bring robots out of the lab and into realistic human environments. Several hard problems remain, among them the large amount of real-world knowledge that an agent needs to have to be able to act competently and autonomously. Further, any item of knowledge is often relevant for many agents and behaviors, and as such should be reusable. To garner trust and enable debugging, knowledge should also be accessible to human operators, both in terms of explaining what knowledge is present in a system, as well as providing ways to easily amend it if necessary. Ontologies are a well-established technique for knowledge representation and management. They formalize conceptualizations at a symbolic, communicable level, allowing re-use of knowledge items between different modules or even agents, as well as explaining reasoning-based decisions. Ontologies have already seen use in robotics, and standardization efforts for robotics knowledge management are in progress.
Shirly Stephen, Rui Zhu, Cogan Shimizu
- There is an increasing interest in semantically integrating diverse and heterogeneous hazard data sets, along with representing hazard information in knowledge graphs. However, there are still significant deficiencies in state-of-the-art ontologies that can represent and connect hazard data across independent sources and variant schemas, for example, due to ambiguities in the interpretation of data, different and incompatible ontological commitments, the lack of web accessibility and clear identifiers for their terms, and insufficient metadata. Also, most hazard ’domain’ ontologies are inadequate for providing insight, through formal logic-supported inferencing, into the processes and relationships involved in the Natural Hazard-Disaster dynamic.