Barry Smith

We begin at the beginning, with an outline of Aristotle’s views on ontology and with a discussion of the influence of these views on Linnaeus. We move from there to consider the data standardization initiatives launched in the 19th century, and then turn to investigate how the idea of computational ontologies developed in the AI and knowledge representation communities in the closing decades of the 20th century. We show how aspects of this idea, particularly those relating to the use of the term 'concept' in ontology development, influenced SNOMED CT and other medical terminologies. Against this background we then show how the Foundational Model of Anatomy, the Gene Ontology, Basic Formal Ontology and other OBO Foundry ontologies came into existence and discuss their role in the development of contemporary biomedical informatics.

Abstract In light of the complexity of unfolding disasters, the diversity of rapidly evolving events, the enormous amount of generated information, and the huge pool of casualties, emergency responders (ERs) may be overwhelmed and in consequence poor decisions may be made. In fact, the possibility of transporting the wounded victims to one of several hospitals and the dynamic changes in healthcare resource availability make the decision process more complex. To tackle this problem, we propose a multicriteria decision support service, based on the Analytic Hierarchy Process (AHP) method, that aims to avoid overcrowding and outpacing the capacity of a hospital to effectively provide the best care to victims by finding out the most appropriate hospital that meets the victims’ needs. The proposed approach searches for the most appropriate healthcare institution that can effectively deal with the victims’ needs by considering the availability of the needed resources in the hospital, the victim’s wait time to receive the healthcare, and the transfer time that represents the hospital proximity to the disaster site. The evaluation and validation results showed that the assignment of hospitals was done successfully considering the needs of each victim and without overwhelming any single hospital.

In recent years there has been a number of promising technical and institutional developments regarding use of ontologies in industry. At the same time, however, most industrial ontology development work remains within the realm of academic research and is without significant uptake in commercial applications. In biomedicine, by contrast, ontologies have made significant inroads as valuable tools for achieving interoperability between data systems whose contents derive from widely heterogeneous sources. In this position paper, we present a set of principles learned from the successful Open Biomedical Ontologies (OBO) Foundry initiative to guide the design and development of the Industrial Ontologies Foundry (IOF), which is a counterpart to the OBO Foundry initiative for the manufacturing industry. We also illustrate the potential utility of these principles by sketching the conceptual design of a framework for sustainable IOF development.

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR. Competing Interest StatementThe authors have declared no competing interest.

This paper is in two parts. Part 1 examines the phenomenon of making space as a process involving one or other kind of legal decision-making, for example when a state authority authorizes the creation of a new highway along a certain route or the creation of a new park in a certain location. In cases such as this a new abstract spatial entity comes into existence – the route, the area set aside for the park – followed only later by concordant changes in physical reality. In Part 2 we show that features identified in studying this phenomenon of legal spacemaking can be detected in other spheres of human activity, for example in planning (where spacemaking is projected into the future), and in reasoning about history (where spacemaking is projected back through time). We shall see that these features display themselves in especially complex ways in our everyday use of language, and we conclude by examining the implications of this complexity for attempts to create an artificial intelligence that would enjoy a mastery of language that would be equivalent to that of human beings.

Distinguishes two senses of 'judgment' on the one hand as meaning a state of 'conviction' or 'belief', and on the other hand as meaning an act of 'affirmation' or 'assertion'. Certainly conviction and assertion stand in close relation to each other, but they delineate two heterogeneous logical spheres, and thereby divide the total field of the theory of judgment into two neighbouring but separate sub-fields. Once this is done it is shown to have implications for our understanding especially of the phenomenon of negation, and of the distinction between negation as affirmation of a negative state of affairs, and negation as act of contradicting the judgment someone else has made.

The theory of Gestalt qualities arose from the attempt to explain how a melody is distinct from the collection of the tones which it comprehends. In this essay from 1890 Christian von Ehrenfels coined the term 'Gestaltqualität' to capture the idea of a pattern which is comprehensible in a single experience. This idea can be applied not only to melodies and other occurrent patterns, but also to continuant patterns such as shapes and colour arrays such as the array of a chess board. Ehrenfel's essay gave birth to the Gestalt movement in psychology.

A constant theme in Sherry Turkle’s work is the idea that computers shape our social and psychological lives. This idea is of course in a sense trivial, as can be observed when walking down any city street and noting how many of the passers-by have their heads buried in screens. In The Second Self, however, Turkle makes a stronger claim to the effect that where people confront machines that seem to think this suggests a new way for us to think – about human thought, emotion, memory, and understanding and thereby affects the way we think and see ourselves as humans. I here attempt here to throw a sceptical light on claims of this sort by examining the Chinese chatbot “Xiǎoice”, which is described by its authors as “the most popular social chatbot in the world”.

Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology development work being undertaken in support of scientific research. The ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But these ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, we shall argue, ontologies such as the GO are comparable to scientific theories, to scientific databases, or to scientific journal publications. Such a view implies a radically new conception of what is involved in the authoring, maintenance and application of ontologies in scientific contexts, and therewith also a radically new approach to the evaluation of ontologies and to the training of ontologists.

Imagine that your body has become attached, without your permission, to that of a sick violinist. The violinist is a human being. He will die if you detach him. Such detachment seems, nonetheless, to be morally permissible. Thomson argues that an unwantedly pregnant woman is in an analogous situation. Her argument is considered by many to have established the moral permissibility of abortion even under the assumption that the foetus is a human being. Another popular argument is that presented by Singer and Unger to the effect that even those who are moderately prosperous are morally obliged to help the poor if they can do so at relatively small cost to themselves. The paper (published under the pseudonym 'Nicola Bourbaki') considers the question whether these two arguments can be simultaneously valid.

Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO). As an Open Biomedical Ontology (OBO) library ontology, CIDO is an open source and interoperable with other existing OBO ontologies. In this article, the general architecture and the design patterns of the CIDO are introduced, CIDO representation of coronaviruses, phenotypes, anti-coronavirus drugs and medical devices (e.g. ventilators) are illustrated, and an application of CIDO implemented to identify repurposable drug candidates for effective and safe COVID-19 treatment is presented.

Driven by the use cases of PubChemRDF and SCAIView, we have developed a first community-based clinical trial ontology (CTO) by following the OBO Foundry principles. CTO uses the Basic Formal Ontology (BFO) as the top level ontology and reuses many terms from existing ontologies. CTO has also defined many clinical trial-specific terms. The general CTO design pattern is based on the PICO framework together with two applications. First, the PubChemRDF use case demonstrates how a drug Gleevec is linked to multiple clinical trials investigating Gleevec’s related chemical compounds. Second, the SCAIView text mining engine shows how the use of CTO terms in its search algorithm can identify publications referring to COVID-19-related clinical trials. Future opportunities and challenges are discussed.

In the present review we focus on what we take to be some remaining issues with the Behaviour Change Intervention Ontology (BCIO). We are in full agreement with the authors’ endorsement of the principles of best practice for ontology development In particular, we agree that an ontology should be “logically consistent and having a clear structures [sic], preferably a well-organised hierarchical structure,” and that “Maximising the new ontology’s interoperability with existing ontologies by reusing entities from existing ontologies where appropriate” is critically important (Wright et al., 2020, p. 17). Our remaining concerns with BCIO relate directly to these two principles. First, we identify a number of issues with some of the classifications and definitions in BCIO that seem to be in tension with the just-mentioned principle . Second, we note some reservations about the reuse of certain classes in BCIO, namely from the Gazetteer (GAZ), the Ontology of Medically Related Social Entities (OMRSE), and the Information Artifact Ontology (IAO). While the latter principle of “reuse” is important, it is also important not to let the reuse of existing classes (or their corresponding definitions) compromise the logical integrity or the realist nature of one’s ontology.

The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile spacebased adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to this data fusion framework. The first is the challenge involved in handling multiple complex terminologies, which is addressed by drawing on a set of Space Domain Ontologies. Another challenge is the complex combinatorics involved when considering all possible feature combinations. This can be mitigated by using integer linear programming optimization that is outlined by the Complex Conceptual Spaces Single Observation mathematical model framework. A third challenge is the complicated physics that is involved in a spacecraft collision that must be addressed to obtain a better understanding of threat assessment. Overcoming these various challenges allows for a quantitative ranking for the potential of a kinetic kill collision across multiple spacecraft pairs. In addition to overcoming these challenges this paper will break down threat assessment into four domains and identify a ranking of threat both for each individual domain and for the four domains combined. Simulation results are shown to verify the developed concepts.

The formal ontology here presented is what we might call a typed combinatorial Meinongian mereology. Its author seeks to formulate the laws, here called ‘canons’, regulating how entities can combine together in wholes of different sorts. The method, as in Bergmann’s earlier works, involves the construction of an ideal language of such a sort that the analysis of complex wholes can be achieved by transforming our natural-language representations of reality into what we might think of as artificial characteristic maps or diagrams which allow the relevant ontological structures to be read off immediately from the symbolic representations which results. In former works Bergmann had held that the symbolic language of Principia Mathematica could serve as the appropriate diagrammatic device for the standard first-order functional calculus and develops instead a new sort diagrammatic language

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.

Driving licenses, identity cards, passports, boarding passes, credit cards, ATM cards – all of these are examples of credentials. Credentials are documents that play a fundamental role in all modern societies. However, philosophers and social ontologists have not yet addressed the analysis of their nature and function. This paper aims to fill this gap through a review of the essential characteristics of credentials, as documents whose primary purpose is to certify the identity and institutional status of the bearer, for example as being the bearer of specific rights. However, credentials also allow their holders the concrete exercise of their rights, as when exercising a right concretely (e.g., crossing a border) requires the possession of a particular credential. The authors distinguish the different types of credentials and describe their functions and the various kinds of acts that are performable with their aid.

Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient exchange of data and information among those involved, which can impede the response process and slow decision making. We, therefore, hypothesize that promoting semantic interoperability across ERO information systems might improve information exchange among stakeholders and thereby allow a more coherent response to the disaster. We propose an ontology‐based messaging service on the basis of the Emergency Data Exchange Language (EDXL) standards. The parties involved will continue to use the terminologies to which they are accustomed, but the system will resolve inconsistencies and thereby enhance mutual understanding among EROs by ensuring semantic translation of the exchanged information. The evaluation of the semantic translation demonstrated the effectiveness and accuracy of the proposed service.

This paper provides a method for characterizing space events using the framework of conceptual spaces. We focus specifically on estimating and ranking the likelihood of collisions between space objects. The objective is to design an approach for anticipatory decision support for space operators who can take preventive actions on the basis of assessments of relative risk. To make this possible our approach draws on the fusion of both hard and soft data within a single decision support framework. Contextual data is also taken into account, for example data about space weather effects, by drawing on the Space Domain Ontologies, a large system of ontologies designed to support all aspects of space situational awareness. The framework is coupled with a mathematical programming scheme that frames a mathematically optimal approach for decision support, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundation for critical assessments of collision likelihood.

The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Ontologies – structured, controlled, vocabularies – are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the virus research domain, following the principles of the Open Biological and Biomedical Ontology (OBO) Foundry and drawing on the resources of the Infectious Disease Ontology (IDO) Core. We report the development of the Virus Infectious Disease Ontology (VIDO), a reference ontology extending IDO Core covering viral infectious diseases. We examine newly minted terms, showcase ontology term reuse, and illustrate the use of VIDO by annotating selections from recent life science research on SAR-CoV-2, in the interest of supporting machine learning projects.

Disaster response is a highly collaborative and critical process that requires the involvement of multiple emergency responders (ERs), ideally working together under a unified command, to enable a rapid and effective operational response. Following the 9/11 and 11/13 terrorist attacks and the devastation of hurricanes Katrina and Rita, it is apparent that inadequate communication and a lack of interoperability among the ERs engaged on-site can adversely affect disaster response efforts. Within this context, we present a scenario-based terrorism case study to highlight the challenges of operational disaster command and response. In this article, which is based on the French emergency response doctrine, we outline a semantics-based common operational command system that is designed to guarantee an efficient information flow among ERs. Our focus is on offering to all ERs, a real-time operational picture of the situation in order to enable multilevel coordination among firefighters, police, healthcare units, public authorities, and other stakeholders. Our approach consolidates information to promote timely sharing of data among ERs. The proposed system is based on an ontology that has been developed to represent the different types of knowledge on the part of ERs, providing a shared vocabulary that covers a variety of interoperability concerns.

In “Ontologies Relevant to behaviour change interventions: A Method for their Development” Wright, et al. outline a step by step process for building ontologies of behaviour modification – what the authors call the Refined Ontology Developmental Method (RODM) – and demonstrate its use in the development of the Behaviour Change Intervention Ontology (BCIO). RODM is based on the principles of good ontology building used by the Open Biomedical Ontology (OBO) Foundry in addition to those outlined in (Arp, Smith, and Spear 2015). BCIO uses as its top-level ontology Basic Formal Ontology (BFO). The methods outlined in Wright, et al. are a valuable contribution to the field, especially the use of formal mechanisms for literature annotation and expert stakeholder review, and the BCIO will certainly play an important role in the extension of OBO Foundry ontologies into the behavioural domain.

Functionally graded materials (FGMs) have been used in many different kinds of applications in recent years and have attracted significant research attention. However, we do not yet have a commonly accepted way of representing the various aspects of FGMs. Lack of standardised vocabulary creates obstacles to the extraction of useful information relating to pertinent aspects of different applications. A standard resource is needed for describing various elements of FGMs, including existing applications, manufacturing techniques, and material characteristics. This motivated the creation of the FGM Ontology (FGMO) in 2016. Here, we present a revised and expanded version of the FGM Ontology, which includes enrichments along four dimensions: (1) documenting recent FGMs applications; (2) reorganising the framework to incorporate an updated representation of types of manufacturing processes; (3) enriching the axioms of the ontology; and (4) importing mid-level ontologies from the Common Core Ontologies (CCO) and Product Life Cycle (PLC) Ontologies. The work is being carried out within the framework of the Industry Ontology Foundry (IOF), and the ontology is conformant to Basic Formal Ontology (BFO).

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.