The Basic Formal Ontology (BFO) is an upper ontology that embraces both continuants and occurrents. Continuants can persist through time while undergoing changes through their participation in processes. Processes are held not to change as they are said to be changes. Yet, the BFO is silent about what sorts of changes might exist: history is the only type that is subsumed by process. Although representing and tracking instance data by means of the BFO’s time-indexed relations allows one to infer that some change must have happened in the portion of reality described by the data, change is not explicitly represented. When a change exists, there must be a change of something. However, when the color of that flower (a quality inhering in, but distinct from, that flower) instantiates red at one time, and brown at a later time, then that change, alone, is not a process under the current definitions and axioms of the BFO. This is because qualities can participate in a process p, but never by itself: p must have a material entity as participant. Furthermore, processes can only have other processes and process boundaries as parts; if the BFO would accept the change of qualities, or specifically dependent continuants in general, as occurrents, though not processes, then such change cannot be occurrent-part-of a process. In this paper we explore the basis of a theory, and the beginnings of an axiomatization thereof, as an extension to the BFO that recognizes change as a subtype of occurrent so that instances thereof happen-in processes and happen-to continuants whereby these continuants participate in the processes these changes happen-in. We anticipate re-expressing the ideas presented here as axioms expressed in terms of processes and participation in a future revision of the BFO-FOL axioms that currently prevent a tighter integration.

The Basic Formal Ontology (BFO) class continuant fiat boundary and its subclasses, including fiat surface, are not heavily axiomatized; they have elucidations, not definitions; and the meanings of these elucidations are poorly captured by the relevant BFO axioms. This paper is an effort to make progress in these respects for fiat surface. We identify a range of desiderata for a BFO-conformant view of fiat surface, argue that the GitHub does not satisfy them, argue that the view of fiat surfaces in Arp et al. (2015) does a better job, and supplement that view in ways that do a still better job. Our discussion allows us to, inter alia, present a number of axioms relevant to our topic worthy of consideration for inclusion in BFO or dependent ontologies in specific domains and for specific purposes.

SNOMED CT is a large concept-based terminology designed according to epistemic, semantic and pragmatic principles relevant to clinicians. Its goal is structured clinical reporting in electronic healthcare records (EHRs). The Basic Formal Ontology (BFO) is an ontology designed on the basis of types claimed to exist in reality based on a domain-independent ontological theory. Its goal is faithful representation of reality within that theory. The Ontology for General Medical Science (OGMS) extends the BFO by providing definitions for types relevant within the clinical domain. Combining SNOMED CT with the ontological rigor of BFO and OGMS might improve clinical reporting by, f.i., preventing data entry mistakes and inconsistencies, and make EHRs more comparable. To that end, we are developing a logical framework capable of exploiting what SNOMED CT offers terminologically and realism-based ontologies such as the BFO and the OGMS ontologically by means of bridging axioms compatible with the BFO, and expressed in the same CLIF-dialect as used in its axiomatization in first order logic. In this paper, we report on our attempts to detect in the combinations of binary relations that are used in the definition of SNOMED CT’s definitions of disorder concepts patterns which might at least partially automate the construction of such axioms. Our findings suggest that this partial automation is indeed possible, but to a smaller extent than we had hoped for. We compare our approach with a recent proposal that seeks to bring SNOMED CT and BFO closer together by reinterpreting SNOMED CT disorders as clinical occurrents. The proposal has its merit in providing a realist underpinning for that part of SNOMED CT’s concept model in terms of the BFO, but is not discriminatory enough for an automatic translation into OGMS. Key problem is the lack of face validity of SNOMED CT disorder terms as compared to the formal definitions they are given and this in absence of textual definitions.

Migrating data from electronic healthcare records (EHR) to data repositories for biomedical research provides an opportunity for the design of extracttransfer-load procedures that not only make the repository a faithful representation of what is stated in the EHR, but also of how what is stated in the EHR (may or may not) correspond to what in reality the statements are about. This includes, for example, annotating which EHR statements are inconsistent with other statements, or which statements cannot possibly be true because of what we know about reality. While one goal of ontologies is to provide background information for determining the reliability of assertions that have been introduced without using an underlying ontology, one goal of Referent Tracking is to make explicit all the implicit assumptions that need to be taken into account to interpret given data correctly. In this paper, using Basic Formal Ontology as an example, we explore the potential of Haskell to implement software that is provably correct with respect to the semantics specified in the ontology.

Changes in an upper level ontology have obvious consequences for the domain ontologies that use it at lower levels. It is therefore crucial to document the changes made between successive versions of ontologies of this kind. We describe and apply a method for tracking, explaining and measuring changes between successive versions of upper level ontologies such as the Basic Formal Ontology (BFO). The proposed change-tracking method extends earlier work on Realism-Based Ontology Versioning (RBOV) and Evolutionary Terminology Auditing (ETA). We describe here the application of this evaluation method to changes between BFO 1.0, BFO 1.1, and BFO 2.0. We discuss the issues raised by this application and describe the extensions which we added to the original evaluation schema in order to account for changes in this type of ontology. The results of our study show that BFO has undergone eight types of changes that can be systematically explained by the extended evaluation schema. Finally, we discuss problematic cases, possible pitfalls and certain limits of our study that we propose to address in future work.

The goal of the REMINE project is to build a high performance prediction, detection and monitoring platform for managing Risks against Patient Safety (RAPS). Part of the work involves developing an ontology enabling computer-assisted RAPS decision support on the basis of the disease history of a patient as documented in a hospital information system. A requirement of the ontology is to contain a representation for what is commonly referred to by the term ‘adverse event’, one challenge being that distinct authoritative sources define this term in different and context-dependent ways. The presence of some common ground in all definitions is, however, obvious. Using the analytical principles underlying Basic Formal Ontology and Referent Tracking, both developed in the tradition of philosophical realism, we propose a formal representation of this common ground which combines a reference ontology consisting exclusively of representations of universals and an application ontology which consists representations of defined classes. We argue that what in most cases is referred to by means of the term ‘adverse event’ – when used generically – is a defined class rather than a universal. In favour of the conception of adverse events as forming a defined class are the arguments that (1) there is no definition for ‘adverse event’ that carves out a collection of particulars which constitutes the extension of a universal, and (2) the majority of definitions require adverse events to be (variably) the result of some observation, assessment or (absence of) expectation, thereby giving these entities a nominal or epistemological flavour.

A common language, or terminology, for representing what clinicians have said and done is an important requirement for individual clinical systems, and it is a pre-requisite for integrating disparate applications in a distributed telematic healthcare environment. Formal representations based on description logics or closely related formalisms are increasingly used for representing medical terminologies. GALEN's experience in using one such formalism raises two major issues, as follows: how to make ontologies based on description logics easy to use and understand for both clinicians and applications developers; what features are required of the ontology and description logic if they are to achieve their aims. Based on our experience we put forward four contentions: two relating to each of these two issues, as follows: that natural language generation is essential to make a description logic based ontology accessible to users; that the description logic based ontology should be treated as an "assembly language" and accessed via "intermediate representations" oriented to users and "perspectives" adapting it to specific applications; that independence and reuse are best supported by partitioning the subsumption hierarchy of elementary concepts into orthogonal taxonomies, each of which forms a pure tree in which the branches at each level are disjoint but nonexhaustive subconcepts of the parent concept; that the expressivity of the description logic must include support for transitive relations despite the computational cost, and that this computational cost is acceptable in practice. The authors argue that these features will be necessary, though by no means sufficient, for the development of any large reusable ontology for medicine.