Barry Smith

Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ in this sense is often used by philosophers as a synonym of ‘metaphysics’ (a label meaning literally: ‘what comes after the Physics’), a term used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. But in recent years, in a development hardly noticed by philosophers, the term ‘ontology’ has gained currency in the field of computer and information science, and in information-driven research in bioinformatics and related areas. We examine these new developments in applied ontology, and show what lessons they might have for both philosophers and information scientists.

In 1890 Christian von Ehrenfels published his classic paper "Über 'Gestaltqualitäten'", the first systematic investigation of the philosophy and psychology of Gestalt. Ehrenfels thereby issued an important challenge to the psychological atomism that was still predominant in his day. His paper not only exerted a powerful influence on the philosophy of the Meinong school, it also marked the beginning of the Gestalt tradition in psychology, later associated with the work of Wertheimer, Köhler and Koffka in Berlin. Includes papers by C. Von Ehrenfels, Kurt Grelling and Paul Oppenheim and contributions by K. Mulligan, P.M. Simons and Barry Smith.

The Austrian philosopher Christian von Ehrenfels published his essay "On 'Gestalt Qualities'" in 1890. The essay initiated a current of thought which enjoyed a powerful position in the philosophy and psychology of the first half of this century and has more recently enjoyed a minor resurgence of interest in the area of cognitive science, above all in criticisms of the so-called 'strong programme' in artificial intelligence. The theory of Gestalt is of course associated most specifically with psychologists of the Berlin school such as Max Wertheimer, Wolfgang Kohler and Kurt Koffka. We shall see in what follows, however, that an adequate philosophical understanding of the Gestalt idea and of Ehrenfels' achievement will require a close examination not merely of the work of the Berlin school but also of a much wider tradition in Austrian and German philosophy in general.

The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’.

Ontologies are being used increasingly to promote the reusability of scientific information by allowing heterogeneous data to be integrated under a common, normalized representation. Definitions play a central role in the use of ontologies both by humans and by computers. Textual definitions allow ontologists and data curators to understand the intended meaning of ontology terms and to use these terms in a consistent fashion across contexts. Logical definitions allow machines to check the integrity of ontologies and reason over data annotated with ontology terms to make inferences that promote knowledge discovery. Therefore, it is important not only to include in ontologies multiple types of definitions in both formal and in natural languages, but also to ensure that these definitions meet good quality standards so they are useful. While tools such as Protégé can assist in creating well-formed logical definitions, producing good definitions in a natural language is still to a large extent a matter of human ingenuity supported at best by just a small number of general principles. For lack of more precise guidelines, definition authors are often left to their own personal devices. This paper aims to fill this gap by providing the ontology community with a set of principles and conventions to assist in definition writing, editing, and validation, by drawing on existing definition writing principles and guidelines in lexicography, terminology, and logic.

The Matrix exposes us to the uncomfortable worries of philosophical skepticism in an especially compelling way. However, with a bit more reflection, we can see why we need not share the skeptic’s doubts about the existence of the world. Such doubts are appropriate only in the very special context of the philosophical seminar. When we return to normal life we see immediately that they are groundless. Furthermore, we see also the drastic mistake that Cypher commits in turning his back upon reality and re-entering the matrix. Not only does reason compel us to admit the existence of the external world, it also requires us to face this world, to build for ourselves meaningful lives within it, and to engage, as adults, in the serious business of living.

Ontology is the philosophical discipline which aims to understand how things in the world are divided into categories and how these categories are related together. This is exactly what information scientists aim for in creating structured, automated representations, called 'ontologies,' for managing information in fields such as science, government, industry, and healthcare. Currently, these systems are designed in a variety of different ways, so they cannot share data with one another. They are often idiosyncratically structured, accessible only to those who created them, and unable to serve as inputs for automated reasoning. This volume shows, in a nontechnical way and using examples from medicine and biology, how the rigorous application of theories and insights from philosophical ontology can improve the ontologies upon which information management depends.

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research.

In 1929 when Aurel Kolnai published his essay “On Disgust” in Husserl's ]ahrbuch he could truly assert that disgust was a "sorely neglected" topic. Now, however, this situation is changing as philosophers, psychologists, and historians of culture are turning their attention not only to emotions in general but more specifically to the large and disturbing set of aversive emotions, including disgust. We here provide an account of Kolnai’s contribution to the study of the phenomenon of disgust, of his general theory of emotions and of the phenomenological methodology he employed in his work.

The present essay is devoted to the application of ontology in support of research in the natural sciences. It defends the thesis that ontologies developed for such purposes should be understood as having as their subject matter, not concepts, but rather the universals and particulars which exist in reality and are captured in scientific laws. We outline the benefits of a view along these lines by showing how it yields rigorous formal definitions of the foundational relations used in many influential ontologies, illustrating our results by reference to examples drawn from the domain of the life sciences.

We provide an overview of Searle's contributions to speech act theory and the ontology of social reality, focusing on his theory of constitutive rules. In early versions of this theory, Searle proposed that all such rules have the form 'X counts as Y in context C' formula – as for example when Barack Obama (X) counts as President of the United States (Y) in the context of US political affairs. Crucially, the X and the Y terms are here identical. A problem arises for this theory for cases involving 'free-standing Y terms', as for example in the case of money in a computerized bank account. Here there is no physical X to which a status function might be attached. We conclude by arguing that Searle's response to this problem creates difficulties for his naturalistic framework.

The manufacturing industry is evolving rapidly, becoming more complex, more interconnected, and more geographically distributed. Competitive pressure and diversity of consumer demand are driving manufacturing companies to rely more and more on improved knowledge management practices. As a result, multiple software systems are being created to support the integration of data across the product life cycle. Unfortunately, these systems manifest a low degree of interoperability, and this creates problems, for instance when different enterprises or different branches of an enterprise interact. Common ontologies (consensus-based controlled vocabularies) have proved themselves in various domains as a valuable tool for solving such problems. In this paper, we present a consensus-based Additive Manufacturing Ontology (AMO) and illustrate its application in promoting re-usability in the field of dentistry product manufacturing.

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory?　 Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society.

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, pathogenesis, diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19.

Part 1 of this exchange consists in a critique by Smith of Searle’s The Construction of Social Reality focusing on Searle’s use of the formula ‘X counts as Y in context C’. Smith argues that this formula works well for social objects such as dollar bills and presidents where the corresponding X terms (pieces of paper, human beings) are easy to identify. In cases such as debts and prices and money in a bank's computers, however, the formula fails, because these are cases of what he calls ‘free-standing Y terms’, since there is here no X which can count as the corresponding Y. In his response in Part 2, Searle argues that Smith’s critique rests on three misunderstandings: 1. in wrongly presupposing that Searle is trying to analyze the nature of what he calls “social objects”, rather than of social facts; 2. in thinking that the counts as formula is intended as a definition, rather than as a mere mnemonic; and 3. in neglecting the naturalism of Searle’s account.

‘Eruv’ is a Hebrew word meaning literally ‘mixture’ or ‘mingling’. An eruv is an urban region demarcated within a larger urban region by means of a boundary made up of telephone wires or similar markers. Through the creation of the eruv, the smaller region is turned symbolically (halachically = according to Jewish law) into a private domain. So long as they remain within the boundaries of the eruv, Orthodox Jews may engage in activities that would otherwise be prohibited on the Sabbath, such as pushing prams or wheelchairs, or carrying walking sticks. There are eruvim in many towns and university campuses throughout the world. There are five eruvim in Chicago, five in Brooklyn, twenty three in Queens and Long Island, and at least three in Manhattan. The US Supreme Court is (like most other major US Federal Government buildings) located within the eruv of Washington DC. In many cases, not all of those living within or near the area of an actual or proposed eruv will themselves be Orthodox Jews, and this has sometimes led to protests against eruv creation. It is such protests which triggered the writing of this essay.

The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end of life. We call this suite the Product Life Cycle (PLC) Ontologies. The suite extends proximately from The Common Core Ontologies (CCO) used widely in defense and intelligence circles, and ultimately from the Basic Formal Ontology (BFO), which serves as top level ontology for the CCO and for some 300 further ontologies. The PLC Ontologies were developed together, but they have been factored to cover particular domains such as design, manufacturing processes, and tools. We argue that these ontologies, when used together with standard public domain alignment and browsing tools created within the context of the Semantic Web, may offer a low-cost approach to solving increasingly costly problems of data management in the manufacturing industry.

Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy.

Numerous research groups are now utilizing Basic Formal Ontology as an upper-level framework to assist in the organization and integration of biomedical information. This paper provides elucidation of the three existing BFO subcategories of realizable entity, namely function, role, and disposition. It proposes one further sub-category of tendency, and considers the merits of recognizing two sub-categories of function for domain ontologies, namely, artifactual and biological function. The motivation is to help advance the coherent ontological treatment of functions, roles, and dispositions, to help provide the potential for more detailed classification, and to shed light on BFO’s general make-up and use.

In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now used by over one hundred ontology projects around the world, and offers examples of domain ontologies that utilize BFO. The book also describes Web Ontology Language (OWL), a common framework for Semantic Web technologies. Throughout, the book provides concrete recommendations for the design and construction of domain ontologies.

In perceptual experience we are directed towards objects in a way which establishes a real relation between a mental act and its target. In reading works of fiction we enjoy experiences which manifest certain internal similarities to such relational acts, but which lack objects. The substitution theory of art attempts to provide a reason why we seek out such experiences and the artifacts which they generate. Briefly, we seek out works of art because we enjoy the physiology and the phenomenology of, for example, the experience of love or mountain climbing, and works of art serve as props for the promotion of substitutes for the corresponding genuine feelings. Art arose, or came to be separated out from other, related phenomena, through the discovery that the experience of substitute emotions can be pleasurable.

The term ‘formal ontology’ was first used by the philosopher Edmund Husserl in his Logical Investigations to signify the study of those formal structures and relations – above all relations of part and whole – which are exemplified in the subject-matters of the different material sciences. We follow Husserl in presenting the basic concepts of formal ontology as falling into three groups: the theory of part and whole, the theory of dependence, and the theory of boundary, continuity and contact. These basic concepts are presented in relation to the problem of providing an account of the formal ontology of the mesoscopic realm of everyday experience, and specifically of providing an account of the concept of individual substance.

Ernst Mach's atomistic theory of sensation faces problems in doing justice to our ability to perceive and remember complex phenomena such as melodies and shapes. Christian von Ehrenfels attempted to solve these problems with his theory of "Gestalt qualities", which he sees as entities depending one-sidedly on the corresponding simple objects of sensation. We explore the theory of dependence relations advanced by Ehrenfels and show how it relates to the views on the objects of perception advanced by Husserl and by the Gestalt psychologists.

A meaningful life, we shall argue, is a life upon which a certain sort of valuable pattern has been imposed by the person in question - a pattern which involves in serious ways the person having an effect upon the world. Meaningfulness is thus a special kind of value which a human life can bear. Two interrelated difficulties face ths proposal. One concerns responsiblity: how are we to account for the fact that a life that satisfies the above criteria can have more meaning than a life with the same positive outcomes but which lacks responsiblity on the part of the agent? The other turns on these outcomes themselves: how can the meaningfulness engendered by actions you perform now be affected by what those actions go on to produce in the future, perhaps even after your death? We provide a response to both of these difficulties