Ebook: Formal Ontology in Information Systems
Formal Ontology in Information Systems (FOIS) is the flagship conference of the International Association for Ontology and its Applications, a non-profit organization promoting interdisciplinary research and international collaboration at the intersection of philosophical ontology, linguistics, logic, cognitive science, and computer science.
This book presents the 11 papers accepted for the 12th edition of FOIS. The conference was held from 13-17 September 2021 in Bozen-Bolzano, Italy, as a hybrid event with some participants attending on-site in Bolzano and others attending virtually online. The papers are divided into 3 sections and cover a wide range of topics: (1) Foundations, addressing fundamental issues; (2) Applications and Methods, presenting novel uses, systems, tools, and approaches; and (3) Domain Ontology, describing well-formed ontologies in particular subject areas.
This volume contains papers accepted for the 12th edition of the Formal Ontology in Information Systems conference (FOIS 2021). The conference occurred in hybrid format involving on-site attendance in Bolzano, Italy, as well as virtual attendance online. This hybrid structure was a first for FOIS and proved to be quite successful, with sessions typically involving a mix of on-site and virtual contributions. Another first for FOIS was the integration of content from two conferences, FOIS 2020 and FOIS 2021, due to the COVID-prompted cancellation of the FOIS 2020 live program. As a result, papers accepted for FOIS 2020 were presented at FOIS 2021, with necessary adjustments to both presentation length and format.
As with FOIS 2020, FOIS 2021 occurred in the broader context of a Bolzano Summer of Knowledge event (BoSK 2021). BoSK 2021 included multiple conferences, workshops, and tutorials, all dedicated to knowledge representation. FOIS 2021 itself reflected this breadth, as it consisted of several workshops and tutorials, an Early Career Symposium, as well as dedicated Demonstration and Ontology Showcase seminars, all in addition to the FOIS 2020 and 2021 paper presentations.
Due to experience gained from FOIS 2020, the organizers made several changes to this edition of FOIS, primarily to stimulate a greater variety of contributions. Historically, FOIS has always accepted a broad range of papers. To highlight this diversity, through explicit solicitation, we introduced three different research tracks: a Foundations track for formal and theoretical issues, an Applications and Methods track for novel ontology uses, systems, approaches, and tools, and a Domain Ontology track for original or significant ontologies in a specific domain of interest. As these tracks are quite distinct, authors and reviewers were provided detailed evaluation criteria to clarify expectations. In addition, the Program Committee was nearly doubled to better reflect the diversity of the community. As a minor change, the rebuttal phase of reviewing was retained from FOIS 2020, but somewhat shortened.
Overview of Accepted Papers
As hoped, the expansion of the program committee and the introduction of different research tracks led to increased submissions of papers on applications and methods as well as on domain ontologies. In contrast, compared to FOIS 2020, fewer papers were submitted on foundational topics. There was a continuing trend in all three tracks to social and agent themes.
For FOIS 2021 we accepted 11 of 42 research paper submissions, which is an acceptance rate of 26%. The submissions ranged across a wide variety of topics, as typical for FOIS, distributed across the three research tracks:
Foundations: 5 accepted
Applications and Methods: 3 accepted
Domain Ontology: 3 accepted
The foundations track is dominated by papers concerned with representational issues: three papers focus on formalisms for multiple perspectives, concept descriptions, and certain natural language scenarios, and a fourth paper is concerned with the nature of representation itself. In Standpoint Logic: Multi-Perspective Knowledge Representation, Gómez Álvarez and Rudolph develop a logic framework for representing multiple perspectives in cases of semantic heterogeneity, with biological examples. The problem of expressing concepts, possibly within evolving or multi-perspective scenarios, is considered by Selway, Stumptner and Mayer in their paper entitled Towards Formalisation of Concept Descriptions and Constraints. As a third contribution to this track, Bennett explores logic-based representations for a particular natural language construct in Semantic Analysis of Winograd Schema No. 1, concluding representational structures such as ontologies play an important role in advancing machine resolution of the construct. From a more birds-eye view, and in the fourth accepted paper on representational issues, the ontological structure of representation itself is investigated by Mizoguchi and Borgo in An Ontology of Representation. The fifth and final paper in this track is by Fumiaki Toyoshima, Adrien Barton, Ludger Jansen and Jean-François Ethier, and is entitled Towards a Unified Dispositional Framework for Realizable Entities. It explores the ontological nature of things such as dispositions and roles, analyzed with an eye for potential application within the BFO foundational ontology.
Applications and Methods
Despite a wide variety of papers submitted to this track, the accepted papers fall into two distinct categories: (1) methodological, focused on methods related to ontology-supported concept combination and logical inconsistency, as well as (2) system-oriented, focused on a platform for collaborative ontology design. The contribution by Righetti, Porello, Troquard, Kutz, Hedblom and Galliani, entitled Asymmetric Hybrids: Dialogues for Computational Concept Combination presents an ontology-supported and dialogue-based approach to concept combination, in which contributing concepts exert unequal influence on the resulting combination. In Debugging classical ontologies using defeasible reasoning tools, Coetzer and Britz explore an approach to finding and resolving logical inconsistencies in ontologies using defeasible reasoning to strategically weaken faulty axioms. The system-oriented paper in this track describes a platform for collaborative ontology design, exemplified by development and refinement of the FIBO ontology for the financial domain in An infrastructure for collaborative ontology development – Lessons learned from developing the Financial Industry Business Ontology (FIBO) by Allemang, Garbacz, Grądzki, Kendall and Trypuz.
The three accepted papers in the domain ontology track tackle quite different subject matter, albeit all linked somehow to actual or simulated human activity, e.g. healthy living, personal data privacy, and robot action. NAct: The Nutrition and Active Ontology for healthy living by Tsatsou, Lalama, Wilson-Barnes, Hart, Cornelissen, Buys, Pagkalos, Dias, Dimitropoulos and Daras, presents an ontology of factors to support healthy living implemented in a decision system. The paper by El Ghosh and Abdulrab entitled Capturing the Basics of the GDPR in a Well-Founded Legal Domain Modular Ontology develops and evaluates an ontology to support implementation of European data protection regulations, founded on the UFO ontology. The final paper in this track explores ontological support for robotic action in Foundations of the Socio-physical Model of Activities (SOMA) for Autonomous Robotic Agents by Beßler, Porzel, Pomarlan, Vyas, Höffner, Beetz, Malaka and Bateman.
FOIS 2021 conferred three awards: best paper, distinguished paper, and best student paper. The best paper award was sponsored by IOS Press, and the best student paper award was sponsored by the Artificial Intelligence Journal. The awards were mutually exclusive, as a winner in one category could not win in another, with the best paper award taking precedence. The selection was made difficult, as ever, by a number of high quality candidates.
After much deliberation by the selection committee, the FOIS best paper award was given to Guendalina Righetti, Daniele Porello, Nicolas Troquard, Oliver Kutz, Maria Hedblom and Pietro Galliani for their contribution entitled Asymmetric Hybrids: Dialogues for Computational Concept Combination. Submitted to the Applications and Methods track, this paper provides novel insight into the integration of applied ontology and the cognitive science field of conceptual combination.
The distinguished paper award was awarded to Fumiaki Toyoshima, Adrien Barton, Ludger Jansen and Jean-François Ethier for their paper entitled Towards a Unified Dispositional Framework for Realizable Entities, which was submitted to the Foundations track. It analyzes realizable entities, such as dispositions and roles, and proposes an enhanced classification.
The best student paper award went to Simone Coetzer and Arina Britz for their entry in the Applications and Methods track entitled Debugging classical ontologies using defeasible reasoning tools, which helps identify and rectify logical inconsistencies in ontologies.
Authors of all submitted papers, accepted or not, are sincerely thanked for their submissions. These not only enable the conference program to be built, but also serve to keep the conference series robust and current, while bolstering the applied ontology community.
Conferences such as FOIS also rely heavily on the diligent work of the organizing committee, who are especially thanked for their exceptional efforts during the trying circumstances of the COVID pandemic. This includes the general chair (Roberta Ferrario), the chairs of the various events, and the publicity chairs. It also includes members of the program committee, who collectively reviewed all paper submissions in concert with a small number of external reviewers. We would also like to thank Megan Katsumi, the proceedings chair, whose aid was instrumental in the creation of this volume. A full listing of the organizing committee is included after this preface.
A special mention is owed to the local organizers: Oliver Kutz and Nicolas Troquard. The COVID-19 pandemic led to constantly shifting policies by the Free University of Bolzano, as well as by local and national governments. This resulted in restricted and evolving travel conditions and local requirements, making long-term planning nearly impossible. Furthermore, the change to a hybrid live-virtual event led to complex infrastructure situations requiring considerable on-the-fly adjustments. While these factors were a potential recipe for disaster, in the end, and much to the credit of the local organizers, the conference proceeded smoothly and was enjoyed by both on-site and remote participants.
FOIS 2021, like its recent predecessors, was organized under the auspices of the IAOA (International Association for Ontology and its Applications). IAOA not only provides a governance framework for FOIS, but is a source of invaluable guidance during all stages of the conference. We thank IOS Press for its continued support in the publication of the FOIS proceedings and its sponsorship of the best paper award. We also thank the Artificial Intelligence Journal for sponsorship of the best student paper award. The following sponsors are also gratefully acknowledged: the Free University of Bozen-Bolzano as well as its KRDB Research Centre for Knowledge and Data, and the Italian National Lab for Artificial Intelligence and Intelligent Systems.
Arguably, organising a conference that involves people from many countries meeting in the Italian Alps in the middle of the COVID-19 pandemic was exceedingly ambitious. The idea was certainly born out of the unjustified hope the pandemic would be over by the autumn of 2021. Our main reason for organising FOIS in 2021, on the heels of FOIS 2020, was the conviction that FOIS live events play a crucial role in the Applied Ontology community. Unfortunately, circumstances dictated the majority of our community was only able to participate remotely. Nonetheless, many of the 35 participants who did meet in Bolzano expressed the same sentiment: after 18 months without travel, and after 18 months in which scientific discourse was mostly exiled to virtual spaces, FOIS 2021 was not just a scientific event, it was also welcomed as a place to meet, debate, and reconnect with colleagues and friends.
One final observation: of the eleven research papers accepted at FOIS 2021, six were written by first authors who are either PhD students or early-career researchers. These include the best paper and the distinguished paper of FOIS 2021. That we have so many talented budding researchers in our community gives hope and optimism for the future of FOIS and Applied Ontology.
Ontologies and knowledge bases encode, to a certain extent, the standpoints or perspectives of their creators. As differences and conflicts between standpoints should be expected in multi-agent scenarios, this will pose challenges for shared creation and usage of knowledge sources.
Our work pursues the idea that, in some cases, a framework that can handle diverse and possibly conflicting standpoints is more useful and versatile than forcing their unification, and avoids common compromises required for their merge. Moreover, in analogy to the notion of family resemblance concepts, we propose that a collection of standpoints can provide a simpler yet more faithful and nuanced representation of some domains.
To this end, we present standpoint logic, a multi-modal framework that is suitable for expressing information with semantically heterogeneous vocabularies, where a standpoint is a partial and acceptable interpretation of the domain. Standpoints can be organised hierarchically and combined, and complex correspondences can be established between them. We provide a formal syntax and semantics, outline the complexity for the propositional case, and explore the representational capacities of the framework in relation to standard techniques in ontology integration, with some examples in the Bio-Ontology domain.
The integrated management of industrial systems in future environments like Industry 4.0 requires the effective management of information throughout the engineering life cycle. As systems pass through phases of design, construction, operation, maintenance, renewal or replacement, they will be administered via different information ecosystems, requiring changing perspectives on their descriptive information. A central role in the interplay of software and hardware artefacts, functions, documentation and managing software is played by the descriptions of concepts (i.e. formalised definitions of concepts within the domain of quantification). In this paper we propose a unified formalisation of descriptions that permits consistent analysis of the relationships between the designs, types, products, and concrete artefacts that can be found in the industrial engineering life-cycle. The approach is consistent with our earlier framework that describes artefacts, requirements and functional roles in the context of the DOLCE foundational ontology.
The Winograd Schema Challenge is a general test for Artificial Intelligence, based on problems of pronoun reference resolution. I investigate the semantics and interpretation of Winograd Schemas, concentrating on the original and most famous example. This study suggests that a rich ontology, detailed commonsense knowledge as well as special purpose inference mechanisms are all required to resolve just this one example. The analysis supports the view that a key factor in the interpretation and disambiguation of natural language is the preference for coherence. This preference guides the resolution of co-reference in relation to both explicitly mentioned entities and also implicit entities that are required to form an interpretation of what is being described. I suggest that assumed identity of implicit entities arises from the expectation of coherence and provides a key mechanism that underpins natural language understanding. I also argue that conceptual ontologies can play a decisive role not only in directly determining pronoun references but also in identifying implicit entities and implied relationships that bind together components of a sentence.
In philosophy information is mainly discussed along with the notion of aboutness. In more practical communities, information is mainly addressed together with notions like data and knowledge. This paper proposes a different approach. We look at information (and related concepts) as roles played by representations. This view implies that the notion of representation is central for any ontological analysis of information and related concepts. The paper provides arguments for this new stand and discusses an ontological model of representation based on the systematic distinction between form and content. The broadness and flexibility of the proposed model is shown by discussing a list of variegated representation entities from music to procedure, from novel to painting. The paper also investigates the role of letters (characters) in natural language expressions, which turns out to be quite complex.
Realizable entities are properties that can be realized in processes of specific correlated types in which the bearer participates. It will be valuable to create a systematic classification of realizable entities because they are useful for various modeling purposes in ontologies. In this paper we outline a unifying framework for realizable entities (including dispositions and roles) in the upper ontology Basic Formal Ontology (BFO) that is theoretically underpinned by J. McKitrick’s pragmatic approach to dispositions. In particular, we develop a formal ontological account of “extrinsic dispositions” and illustrate its potential applications with clarification of functions and roles in BFO.
When people combine concepts these are often characterised as “hybrid”, “impossible”, or “humorous”. However, when simply considering them in terms of extensional logic, the novel concepts understood as a conjunctive concept will often lack meaning having an empty extension (consider “a tooth that is a chair”, “a pet flower”, etc.). Still, people use different strategies to produce new non-empty concepts: additive or integrative combination of features, alignment of features, instantiation, etc. All these strategies involve the ability to deal with conflicting attributes and the creation of new (combinations of) properties. We here consider in particular the case where a Head concept has superior ‘asymmetric’ control over steering the resulting concept combination (or hybridisation) with a Modifier concept. Specifically, we propose a dialogical approach to concept combination and discuss an implementation based on axiom weakening, which models the cognitive and logical mechanics of this asymmetric form of hybridisation.
A successful application of ontologies relies on representing as much accurate and relevant domain knowledge as possible, while maintaining logical consistency. As the successful implementation of a real-world ontology is likely to contain many concepts and intricate relationships between the concepts, it is necessary to follow a methodology for debugging and refining the ontology. Many ontology debugging approaches have been developed to help the knowledge engineer pinpoint the cause of logical inconsistencies and rectify them in a strategic way. We show that existing debugging approaches can lead to unintuitive results, which may lead the knowledge engineer to opt for deleting potentially crucial and nuanced knowledge. We provide a methodological and design foundation for weakening faulty axioms in a strategic way using defeasible reasoning tools. Our methodology draws from Rodler’s interactive ontology debugging approach and extends this approach by creating a methodology to systematically find conflict resolution recommendations. Importantly, our goal is not to convert a classical ontology to a defeasible ontology. Rather, we use the definition of exceptionality of a concept, which is central to the semantics of defeasible description logics, and the associated algorithm to determine the extent of a concept’s exceptionality (their ranking); then, starting with the statements containing the most general concepts (the least exceptional concepts) weakened versions of the original statements are constructed; this is done until all inconsistencies have been resolved.
Collaborative development of a shared or standardized ontology presents unique issues in workflow, version control, testing, and quality control. These challenges are similar to challenges faced in large-scale collaborative software development. We have taken this idea as the basis of a collaborative ontology development platform based on familiar software tools, including Continuous Integration platforms, version control systems, testing platforms, and review workflows.
We have implemented these using open-source versions of each of these tools, and packaged them into a full-service collaborative platform for collaborative ontology development. This platform has been used in the development of FIBO, the Financial Industry Business Ontology, an ongoing collaborative effort that has been developing and maintaining a set of ontologies for over a decade.
The platform is open-source and is being used in other projects beyond FIBO. We hope to continue this trend and improve the state of practice of collaborative ontology design in many more industries.
This paper presents the NAct (Nutrition & Activity) Ontology, designed to drive personalised nutritional and physical activity recommendations and effectively support healthy living, through a reasoning-based AI decision support system. NAct coalesces nutritional, medical, behavioural and lifestyle indicators with potential dietary and physical activity directives. The paper presents the first version of the ontology, including its co-design and engineering methodology, along with usage examples in supporting healthy nutritional and physical activity choices. Lastly, the plan for future improvements and extensions is discussed.
The primary goal of the General Data Protection Regulation (GDPR) is to regulate the rights and duties of citizens and organizations over personal data protection. Implementing the GDPR is recently gaining much importance for legal reasoning and compliance checking purposes. In this work, we aim to capture the basics of GDPR in a well-founded legal domain modular ontology named OPPD (Ontology for the Protection of Personal Data). Ontology-Driven Conceptual Modeling (ODCM), ontology layering, modularization, and reuse processes are applied. These processes aim to support the ontology engineer in overcoming the complexity of the legal knowledge and developing an ontology model faithful to reality. ODCM is used for grounding OPPD in the Unified Foundational Ontology (UFO). Ontology modularization and layering aim to simplify the ontology building process. Ontology reuse focuses on selecting and reusing Conceptual Ontology Patterns (COPs) from UFO and the legal core ontology UFO-L. OPPD intends to overcome the lack of a representation of legal procedures that most ontologies encountered. The potential use of OPPD is proposed to formalize the GDPR rules by combining ontological reasoning and Logic Programming.
In this paper, we present foundations of the Socio-physical Model of Activities (SOMA). SOMA represents both the physical as well as the social context of everyday activities. Such tasks seem to be trivial for humans, however, they pose severe problems for artificial agents. For starters, a natural language command requesting something will leave many pieces of information necessary for performing the task unspecified. Humans can solve such problems fast as we reduce the search space by recourse to prior knowledge such as a connected collection of plans that describe how certain goals can be achieved at various levels of abstraction. Rather than enumerating fine-grained physical contexts SOMA sets out to include socially constructed knowledge about the functions of actions to achieve a variety of goals or the roles objects can play in a given situation. As the human cognition system is capable of generalizing experiences into abstract knowledge pieces applicable to novel situations, we argue that both physical and social context need be modeled to tackle these challenges in a general manner. The central contribution of this work, therefore, lies in a comprehensive model connecting physical and social entities, that enables flexibility of executions by the robotic agents via symbolic reasoning with the model. This is, by and large, facilitated by the link between the physical and social context in SOMA where relationships are established between occurrences and generalizations of them, which has been demonstrated in several use cases in the domain of everyday activites that validate SOMA.