Recently, there has been growing interest in the use of ontology as a fundamental tool for representing domain-specific conceptual models to improve the semantics, accuracy, and relevance of domain users’ query results. Although the amount of data has grown steadily over the past decade, much data shares similar characteristics that can be captured by a foundational ontology. In this paper, we show how queries based on a foundational ontology can be evaluated and their performance measured. We also present a Foundational (...) Patterns benchmark to help select the most efficient triple memory and its layout. We evaluate the foundational benchmark with both generated and real datasets for state-of-the-art triple stores. (shrink)

In this paper we provide a framework for studying the ways in which food endures the passage of time. Central to our inquiry is the following Duration Question: when is it that the predicate-schema “Is an X-Food,” where “X-Food” stands for a certain type of food (e.g., Champagne, yoghurt) ceases to apply to an entity? We show that the answer depends on two independent theoretical aspects: the underlying conception of food and the kinds of change that a specific food can (...) undergo. We then argue that specific answers to the duration question should take the form of conceptual rethinking among different stakeholders (e.g., producers, consumers, institutions), where philosophers would feature among the experts guiding the negotiation. (shrink)

Ontology development methodologies emphasise knowledge gathering from domain experts and documentary resources, and knowledge representation using an ontology language such as OWL or FOL. However, working ontologists are often surprised by how challenging and slow it can be to develop ontologies. Here, with a particular emphasis on the sorts of ontologies that are content-heavy and intended to be shared across a community of users (reference ontologies), we propose that a significant and heretofore under-emphasised contributor of challenges during ontology development is (...) the need to create, or bring about, consensus in the face of disagreement. For this reason reference ontology development cannot be automated, at least within the limitations of existing AI approaches. Further, for the same reason ontologists are required to have specific social-negotiating skills which are currently lacking in most technical curricula. (shrink)

Ontologies have been successfully used to assign semantics in the Semantic Web context, to support integration of data from different systems or different sources, and to enable reasoning. However, building ontologies is not a trivial task. Ontology reuse can help in this matter. The search and selection of ontologies to be reused should consider the alignment between their scope and the scope of the ontology being developed. In this paper, we discuss how goal modeling can be helpful in this context (...) and we present GO-FOR, a framework in which goals are the central elements to promote ontology reuse. GO-FOR comprises a conceptual architecture, a goal-oriented ontology development process and a supporting tool. In GO-FOR we introduce Goal-Oriented Ontology Patterns as a new type of pattern to be applied to develop ontologies in a goal-oriented approach. Results of the use of GO-FOR to build an ontology used to integrate patient examination data are also shown in this paper. (shrink)

The next generation of Geographic Information Systems is anticipated to automate some of the reasoning required for spatial analysis. An important step in the development of such systems is to gain a better understanding and corresponding modeling practice of when to apply arithmetic operations to quantities. The concept of extensivity plays an essential role in determining when quantities can be aggregated by summing them, and when this is not possible. This is of particular importance to geographic information systems, which serve (...) to quantify phenomena across space and time. However, currently, multiple contrasting definitions of extensivity exist, and none of these suffice for handling the different practical cases occurring in geographic information. As a result, analysts predominantly rely on intuition and ad hoc reasoning to determine whether two quantities are additive. In this paper, we present a novel approach to formalizing the concept of extensivity. Though our notion as such is not restricted to quantifications occurring within geographic information, it is particularly useful for this purpose. Following the idea of spatio-temporal controls by Sinton, we define extensivity as a property of measurements of quantities with respect to a controlling quantity, such that a sum of the latter implies a sum of the former. In our algebraic definition of amounts and other quantities, we do away with some of the constraints that limit the usability of older approaches. By treating extensivity as a relation between amounts and other types of quantities, our definition offers the flexibility to relate a quantity to many domains of interest. We show how this new notion of extensivity can be used to classify the kinds of amounts in various examples of geographic information. (shrink)

Advances in machine learning and the development of very large knowledge graphs have accompanied a proliferation of ontologies of many types and for many purposes. These ontologies are commonly developed independently, and as a result, it can be difficult to communicate about and between them. To address this difficulty of communication, ontologies and the communities they serve must agree on how their respective terminologies and formalizations relate to each other. The process of coming into accord and agreement is called “harmonization.” (...) The Ontology Summit 2021 examined the overall landscape of ontologies, the many kinds of ontology generation and harmonization, as well as the sustainability of ontologies. The Communiqué synthesizes and summarizes the findings of the summit as well as earlier summits on related issues. One of the major impediments to harmonization is the relatively poor quality of natural language definitions in many ontologies. The summit surveyed the state of the art in natural language definition development, based on lexicographic principles, as well as examples of ongoing projects that are explicitly dealing with harmonization and sustainability. (shrink)

We present in this paper a novel ontological theory of events 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. We discuss then the way language refers to events, observing that, in most cases, event descriptions refer to complex, cognitively relevant clusters of co-occurring qualitative changes, 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”, we show how the lexicon provides systematic principles for individuating such clusters and classifying them into kinds. Finally, we address some open challenges in the semantics of locative and manner modifiers. (shrink)

The notion of affordance remains elusive, notwithstanding its importance for the representation of agency, cognition, and behaviors. This paper lays down a foundation for an ontology of affordances by elaborating the idea of “core affordance” which would serve as a common ground for explaining existing diverse conceptions of affordances and their interrelationships. For this purpose, it analyzes M. T. Turvey’s dispositional theory of affordances in light of a formal ontology of dispositions. Consequently, two kinds of so-called “core affordances” are proposed: (...) specific and general ones. Inspired directly by Turvey’s original account, a specific core affordance is intimately connected to a specific agent, as it is reciprocal with a counterpart effectivity of this agent within the agent-environment system. On the opposite, a general core affordance does not depend on individual agents; rather, its realization involves an action by an instance of a determinate class of agents. The utility of such core affordances is illustrated by examining how they can be leveraged to formalize other major accounts of affordances. Additionally, it is briefly outlined how core affordances can be employed to analyze three notions that are closely allied with affordances: the environment, image schemas, and intentions. (shrink)

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection (...) and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale. (shrink)

GUM is a linguistically-motivated ontology originally developed to support natural language processing systems by offering a level of representation intermediate between linguistic forms and domain knowledge. Whereas modeling decisions for individual domains may need to be responsive to domain-specific criteria, a linguistically-motivated ontology offers a characterization that generalizes across domains because its design criteria are derived independently both of domain and of application. With respect to this mediating role, the use of GUM resembles the adoption of upper ontologies as tools (...) for mediating across domains and for supporting domain modeling. This paper briefly introduces the ontology, setting out its origins, design principles and applications. The example cases for this special issue are then described, illustrating particularly some of the principal differences and similarities of GUM to non-linguistically motivated upper ontologies. (shrink)

dolce, the first top-level ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and (...) is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources. Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases. (shrink)

Upper ontologies have traditionally arisen from the approach in which concepts that are common across a set of domains can be axiomatized at a general level. The rationale is that reuse across domains is to be supported through specialization of the general concepts from an upper ontology. Similarly, semantic integration between ontologies is to be achieved through the general concepts they specialize. The TUpper Ontology follows an alternative approach to the conventional upper ontology paradigm. Rather than think of an upper (...) ontology as a monolithic axiomatization centred on a taxonomy, the sideways approach considers an upper ontology to be a modular ontology composed of generic ontologies that cover concepts including those related to time, process, and space. TUpper is therefore composed of a set of generic ontologies, and each generic ontology axiomatizes a particular set of generic concepts. The TUpper Ontology is designed as a top-level ontology that contains modules from the ontologies within existing international standards. (shrink)

The General Formal Ontology is a top-level ontology that is being developed at the University of Leipzig since 1999. Besides introducing some of the basic principles of the ontology, we expound axiomatic fragments of its formalization and present ontological models of several use cases. GFO is a top-level ontology that integrates objects and processes into a unified framework, in a way that differs significantly from other ontologies. Another unique selling feature of GFO is its meta-ontological architecture, which includes set theory (...) into ontology and which accounts for its specific role in common representation approaches. The second level of that architecture starts from the distinction of categories and individuals, which forms the backbone of the world’s structure. Furthermore, GFO comprises several kinds of categories, among them universals and concepts, and it considers several ontological regions and levels. In the context of this special issue paper, we study five pre-determined use cases from the perspective of GFO. The results of these analyses yield insights into how the ontology treats several important notions. Very abridged, this covers material objects and their composition; roles and social entities; properties with their relations to objects and processes, and their changing; changes of processes, including a functional perspective; and, eventually, the nature and changing of concepts as well as terminology. A final part summarizes application projects that use GFO in various contexts. (shrink)

yamato sharply distinguishes itself from other existing upper ontologies in the following respects. Most importantly, yamato is designed with both engineering and philosophical minds. yamato is based on a sophisticated theory of roles, given that the world is full of roles. yamato has a tenable theory of functions which helps to deal with artifacts effectively. Information is a ‘content-bearing’ entity and it differs significantly from the entities that philosophers have traditionally discussed. Taking into account the modern society in which a (...) flood of information occurs, yamato has a sophisticated theory of informational objects. Quality and quantity are carefully organized for the sake of greater interoperability of real-world data. The philosophical contribution of yamato includes a theory of objects, processes, and events. Those features are illustrated with several case studies. These features lead to the intensive application of yamato in some domains such as biomedicine and learning engineering. (shrink)

Basic Formal Ontology (BFO) is a top-level ontology consisting of thirty-six classes, designed to support information integration, retrieval, and analysis across all domains of scientific investigation, presently employed in over 350 ontology projects around the world. BFO is a genuine top-level ontology, containing no terms particular to material domains, such as physics, medicine, or psychology. In this paper, we demonstrate how a series of cases illustrating common types of change may be represented by universals, defined classes, and relations employing the (...) BFO framework. We provide discussion of these cases to provide a template for other ontologists using BFO, as well as to facilitate comparison with the strategies proposed by ontologists using different top-level ontologies. (shrink)

The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of (...) UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.). (shrink)