It is generally agreed that as a fundamental feature of the world, time merits treatment within an upper ontology, that is, an ontology that is designed to capture those categories which are sufficiently generic to transcend the specific subject matters of any particular domain ontologies. In this paper I examine how time is handled within three well-known upper ontologies (BFO, DOLCE, and GFO), and follow this with a discussion of three key issues emerging from the survey, namely dimensionality (the treatment of instants and intervals), frame-dependence (as required by the Theory of Relativity), and indexicality (the status of past, present and future). The overall conclusion is that while existing upper ontologies tend to adopt some kind of compromise between a supposedly objective, scientific account of physical time, and a more subjective, cognitive account of time as we experience it, the fundamental philosophical and scientific questions concerning the nature of time have scarcely been addressed by any of them.

In this paper we present an ontological perspective on ongoing work in histological and histopathological imaging involving the quantitative and algorithmic analysis of digitised images of cells and tissues. We present the derivation of consistent histological models from initially captured images of prepared tissue samples as a progression through a number of ontological levels, each populated by its distinctive classes of entities related in systematic ways to entities at other levels. We see this work as contributing to ongoing efforts to provide a consistent and widely accepted suite of ontological resources such as those currently constituting the OBO Foundry, and where possible we draw links between our work and existing ontologies within that suite.

In many applications, the environmental context for and drivers of movement patterns are just as important as the patterns themselves. This article adapts standard data mining techniques, combined with a foundational ontology of causation, with the objective of helping domain experts identify candidate causal relationships between movement patterns and their environmental context. In addition to data about movement and its dynamic environmental context, our approach requires as input definitions of the states and events of interest. The technique outputs causal and causal-like relationships of potential interest, along with associated measures of support and confidence. As a validation of our approach, the analysis is applied to real data about fish movement in the Murray River in Australia. The results demonstrate that the technique is capable of identifying statistically significant patterns of movement indicative of causal and causal-like relationships.

Discrete mereotopology (DM) is a first-order spatial logic that fuses together mereology (the theory of parthood relations) and topology to model discrete space. We show how a set of quasitopological functions defined within DM can be mapped to specific operators defined in mathematical morphology (MM) and easily implemented in scientific image processing programs. These functions provide the means to model topological properties of individual regions and spatial relations between them such as contact, overlap, and the relation of part to whole. DM not only extends the expressive power of image processing applications where mathematical morphology is used, but by functioning as a logic it also supplies the formal basis with which to prove the correctness of implemented algorithms as well as providing the computational basis to mechanically reason about segmented digital images using automated reasoning programs. In particular, we show how DM can supply a model-based and algorithmic context to the otherwise blind pixel-based image processing routines still dominating conventional imaging approaches. A number of worked examples drawn from the histological domain are given, including segmentation of cells in culture, identifying basal cell layers from stratified epithelia sections, and cell sorting in blood smears.

The subject of causality is large, and fraught with difficulties. In this paper, we concentrate on two aspects which are of importance when we seek to handle causality from an ontological point of view, The first concerns the range of particulars between which causal and causal-like relations may hold. In addition to events—the domain most typically chosen as the objects of causation—we consider the role played by processes and states, taking a particular view of the nature of these entities. The second aspect concerns the range of different causal and causal-like relations to be considered. In addition to causation itself we consider such things as initiation and termination, perpetuation, enablement and prevention. We do not present a fully-fledged ontological theory of causation, but lay down some basic ingredients that should be taken into account in the construction of such a theory.

We are surrounded by collective phenomena, with examples existing on many levels of granularity. Despite our frequent experiences of such phenomena they seem to have been largely ignored within the field of ontology. In this paper, existing ontologies are examined to determine the extent to which they can adequately represent collective phenomena, and are found wanting in a number of important respects. Our goal is to find good ways of representing collective phenomena in a way which does justice to the often subtle relationship that exists between the view of a collective as a whole and its constitution as a plurality of individual participants. An important prerequisite for this is to determine the range of variation that exists within the broad class of collectives. A number of example collective phenomena have been studied to extract appropriate classification criteria. The results from this study are used to produce a new typology of collectives which is intended to establish a basis for the adequate treatment of collectives within an ontology. The paper concludes with a set of further research questions that have been raised during the development of the classification.

We develop a theory of processes which takes into account the observation that processes differ markedly from events in their relation to change. Whereas events are fixed items of history which cannot be described as undergoing change, processes are more like ordinary objects in that they can be directly present at one time and can undergo change as time proceeds. This leads to a fundamental ontological distinction between EXP, the dynamic experiential world of objects and processes as they exist at one time, and HIST, the static historical overview populated by events that are generated by the ongoing processes in EXP. Formally, this means that terms describing processes can serve as arguments to time-varying predicates, whereas terms describing events cannot. We illustrate this by presenting part of a suitable formalism and using it to give an account of the progressive aspect.

Summary form only given. In philosophy it is common to introduce a high-level ontological distinction between continuants and occurrents. Continuants are entities which endure through time: for this reason, they are also called endurants. A continuant can undergo change and yet preserve its identity through those changes. Its parts are spatial parts, and it exists, as a whole, at each moment of its lifetime - notwithstanding the possibility that at different moments that whole might consist of different parts. Occurrents, on the other hand, are extended in time: they `perdure' (hence, they are called perdurants). Unlike continuants, occurrents have temporal parts, e.g., the first half of the concert and the second half of the concert. Because an occurrent as a whole spans the time period from its beginning to its end, it cannot be said to change (although it may be a change), and it does not exist, as a whole, at any one moment during its temporal extent. In this paper, the author proposes a radical view of processes as continuants rather than occurrents. Processes, like objects but unlike events, can be the subject of change: the water flow increases, the heartbeat speeds up, music becomes louder. A corollary of this is that our snapshot of the world at one time must contain processes as well as objects; snapshots are thus not static but have an intrinsic dynamism which may be thought of as providing the 'power source' for the generation of events. He uses Lyons' (1977) distinction between experiential and historical modes of description to underpin the essential contrast between, on the one hand, the world of dynamic snapshots containing objects and processes, and on the other hand, the fixed history of events as faits accomplis, as it were the fossil record of once-active processes. He shall show that this idea is entirely in accordance with standard mathematical ways of modelling the changing world, provides an appropriate explanatory framework for handling the phenomenon of aspect in natural language, and can even throw light on ancient puzzles such as Zeno's arrow paradox. Finally, he shall also indicate how the conception of processes as continuants can provide a sound basis for the logical modelling of dynamical systems

We present a method for formalising the behaviour of simple deterministic devices and protocols in a way that makes explicit the causal dependencies amongst the component elements, thereby allowing true causal (as opposed to purely temporal) reasoning. Our intention is to handle such systems effectively in the simplest possible way, without invoking additional problematic considerations (concerning, for example, non-monotonicity) that may be necessary for modelling a more general range of scenarios.

. The majority of existing formalisms for reasoning about action and change require explicit references to low-level entities such as time points or situations whether or not these are a relevant feature of the problem in hand. Transition calculus is an alternative, high-level approach, in which actions are directly modelled in terms of the state changes that they bring about. It is argued that this provides a more natural way of representing and solving many action and change problems and it is shown how the formalism can be applied to the AI planning domain. Although primarily intended as a purely high-level formalism, transition calculus may also be given a temporal semantics and can thus also be used to solve problems reformulated in terms of explicit temporal references. Any useful action and change formalism must be capable of handling the frame problem. Transition calculus accomplishes this via a novel nonmonotonic reasoning mechanism based on minimization of unexplained state change. This is readily implementable and has been shown to solve a wide variety of canonical problems.

Allen and Hayes proposed five axioms for the logic of temporal intervalθ Ladkin claimed that the fifth axiom was a consequence of the first three. The purpose of this short note is to show that this is not in fact the case, thus vindicating Allen and Hayes. We conclude with a discussion of what light this demonstration throws on the role played by the fifth axiom.

In formalizing temporal reasoning, should a proposition be allowed to change its truth value infinitely often over a finite period of time? It has been widely felt that for many types of proposition this phenomenon, which following Hamblin we call ‘intermingling’, should be outlawed. In this paper we systematically examine the varieties of intermingling, distinguishing intermingling over an interval from intermingling at an instant. We survey the axioms that have been proposed in the literature to rule out intermingling, and determine precisely which varieties of intermingling are ruled out by which axioms. We distinguish ‘weak’ non-intermingling principles, which only rule out one or two forms of intermingling, from ‘strong’ non-intermingling principles which rule out all or most forms of intermingling. We show that none of the first-order solutions in the literature suffices to rule out all forms of intermingling, though a second-order solution can do so.

No doubt every reader of this journal is aware that computer science is becoming infiltrated by a strange breed of people called logicians, who try to convince computer people that their arcane symbolism and obscure terminology are just what is needed to solve the software crisis, the hardware crisis, and any other difficulties that the computer world finds itself facing. Unfortunately the symbolism and the jargon can be very off-putting to anyone who has not already become immersed informal logic; I have often met people who work with computers and are aware of how important logic is claimed to be by its devotees, and who feel that they really ought one day to make an effort to penetrate its mysteries, but who have not known how to set about doing so. This article and its sequel (‘Logic as a Formal Method’) are intended as a fairly gentle initiation into what logic is about and what it has to offer computer scientists. They are inevitably very sketchy and incomplete – more like the brochures that can be picked up at a travel agent's than a proper guide-book – but it is to be hoped that some, at least, of my readers will come away with a clearer picture of what lies in store for them if they decide to follow up the more detailed references. The present article outlines the two systems which form the standard core of formal logic, the propositional calculus and the predicate calculus. For a more detailed treatment, see my good Logic for Information Technology (Wiley, 1990). The second article looks at applications of these systems to computer science, and then expands the horizons by looking at some of the non-standard logical systems that have developed from the standard core and which have found application in a computational context.

The aim of this article is to present, in outline, a representative selection of the ways in which formal logic has been of service to computer science. Logic offers so many possibilities of application, and there are so many diverse groups of researchers developing logic-based applications, that it will be impossible in the space available to do justice to the whole field. Indeed it will be impossible even to mention everything that is going on, let alone say anything about it. Therefore I confine myself to a few areas which I believe, taken together, give a fair impression of the promise that formal logic holds as a tool for computer scientists. I assume in this article that the reader has a working knowledge of the classical propositional and predicate calculi: a lightning sketch of these systems can be found in my article ‘Classical Logic: a Crash Course for Beginners’ which appears earlier in this issue; for more details, the reader is urged to consult a textbook such as my Logic for Information Technology (Wiley, 1990).