Guendalina Righetti, Maria M. Hedblom, Oliver Kutz, Stefano De Giorgis
Website: https://caos.inf.unibz.it/

CAOS: Cognition And OntologieS is a workshop series devoted to the relationship between cognition and ontologies with the purpose to model, simulate and represent cognitive phenomena for artificial intelligence.

With the increased interest in ideas derived from embodied cognition and cognitive computing within Artificial Intelligence and Machine Learning, the connection between symbolic methods and the cognitive sciences has gained renewed importance and urgency.

The success story of machine learning and neural networks to perform certain cognitive and classification tasks does not, indeed, reduce the usefulness of symbolic approaches. To the contrary, the development of a new wave of hybrid artificial intelligence will enable a better understanding and simulation of cognitive phenomena, and classic methods from knowledge representations and ontologies can greatly benefit the solutions to the challenging problems of explainable and ethical AI.

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 state-of-the-art work.

Cognition And OntologieS (CAOS) has been held five times. First held in Annecy 2016 at FOIS/JOWO, it was next organised as a workshops at the AISB convention in 2017, held at the University of Bath, UK. The third and fourth editions of CAOS were once again held at JOWO, in Cape Town in 2018, and in Graz in 2019. CAOS V was announced for 2020 and then moved to 2021 (due to the Covid-19 pandemic) and was held as a FOIS workshop as part of the 2020/21 Bolzano Summer of Knowledge.

Boyan Brodaric, Michael Gruninger, Torsten Hahmann

Website: TBA

Luiz Olavo Bonino da Silva Santos, Giancarlo Guizzardi, Clement Jonquet, Cassia Trojahn

Website: https://onto4fair.github.io

Making the resources produced by researchers fully reusable and understood requires specific efforts. The Findable, Accessible, Interoperable and Reusable (FAIR) principles were elaborated to address these issues, describing a set of requirements for resource reusability and interoperability. These principles have been gaining increasing attention in a range of different areas and applications.

One the one hand, a key aspect is the ability of properly and semantically describing resources, in particular with the help of ontologies. On the other hand, ontologies themselves have to be compliant with the FAIR principles.

The workshop has the following goals:

to bring together leaders from academia, industry and user institutions to discuss the adoption of FAIR principles in research and real-world requirements

• to serve to inform about existing research efforts that may meet their requirements.
• to investigate how the FAIR principles are supported by the use of ontologies that ideally are themselves FAIR.
• to discuss the challenges and perspectives in adopting FAIR principles.

Damion Dooley, Matthew Lange, Hande Küçük McGinty, Anoosha Sehar

Website: https://foodon.org/ifow-2023-workshop/

Motivated by FAIR data sharing mandates, academic, agricultural and public health agencies are adopting ontology in their research and data management and reporting infrastructure, often by way of emerging data sharing standards such as the Genomic Standards Consortium MIxS collection. It is one thing to have basic standardized term coverage of various food related domains – from organism anatomy and taxonomy, to food products, food safety properties, agricultural treatments, and food processing methods. The next generation of data harmonization occurs at a higher level of modeling – the standardized data structures for modelling plant and animal trait genomics, agricultural practices, food processing, nutritional analysis, contaminant exposure and diet, health and disease related research. What vocabulary, tool ecosystem and data models are needed to accomplish this modelling? 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
Website: https://csse.utoronto.ca/oss2023

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, society, and services. We invite researchers from the Knowledge Representation, Semantic Web, and Machine Learning communities to submit theoretical contributions, novel algorithms, artifacts, and tools related to the interaction of society and service provisioning. We welcome reports from sociologists and service practitioners across various society-focused domains (e.g. social workers, therapists, physicians, probation officers, urban planners, etc.) on their experiences using semantic-enabled technologies, best practices, and insights.

Davide Audrito, Luigi Di Caro, Francesca Grasso, Roberto Nai, Emilio Sulis

Website: https://km4law.di.unito.it/

Artificial Intelligence (AI), Knowledge Modeling (KM), Information Extraction (IE) and Process Mining (PM) methods are increasingly important for many sub-domains of legal informatics, including ontologies, argumentation, natural language processing, legal event log analysis, eventually paired with a multilingual approach. The Knowledge Management and Process Mining for Law (KM4LAW) workshop intends to be a forum to focus on legal informatics from different perspectives.

The advanced developments in AI over recent years have meant that seemingly insurmountable problems in AI & Law are beginning to be addressed. Accordingly, it is necessary to identify the limits of automated systems and how such systems can handle the remaining unsolved intentional and unintentional ambiguities and conflicts that require legal interpretation. Therefore, research works on the limits and unexplored opportunities offered by AI for the representation of knowledge in the legal domain constitute worthwhile contributions for this workshop.

Typical goals may include: classification of legal sources, legal design and legal ontologies, similarity among legal decisions and clustering, prediction and support during judicial decision making, legal interpretation support, identification of evolution of legal concepts and definitions over time, information extraction and classification, process mining for legal compliance, detection of linguistic phenomena and patterns in legal sources, multilingual alignments of concepts on domestic and international legal sources, identification of legal references and network analysis.

Loris Bozzato, Torsten Hahmann, Cogan Shimizu, Antoine Zimmermann

Website: https://mk2023.fbk.eu/

The dramatic increase in the amount of open and linked data and the increasing semantification of such data make clear that knowledge is not monolithic, static or uniform, and that there is a need of methods and tools for dealing with heterogeneous and distributed knowledge as a constellation of modules.
The Modular Knowledge workshop offers an interdisciplinary venue for discussing and developing solutions for modularity of knowledge.
The workshop combines the efforts of previous experiences (like WoMO, ARCOE-Logic and WOMoCoE workshops) into an interdisciplinary venue for discussing and developing solutions for modularity of knowledge.
Modular Knowledge 2023 aims to cover and establish connections between various approaches (ranging from rich semantic representations, like Knowledge Graphs and formal ontology, to simpler schemas, like RDF and database schemas) for representing knowledge, its context, its evolution, and for making it accessible to automatic reasoning and knowledge management tasks. We welcome approaches that make use of logic-based, subsymbolic, or numerical representations.

Fumiaki Toyoshima, Riccardo Baratella, Oliver Kutz, Stefano Borgo

Website: https://foust.inf.unibz.it/foust7/

Foundational ontologies are attempts to systematize 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 organized, 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 specialized 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.