Barry Smith

While Darwin is commonly supposed to have demonstrated the inapplicability of the Aristotelian ontology of species to biological science, recent developments, especially in the wake of the Human Genome Project, have given rise to a new golden age of classification in which ontological ideas -- as for example in the Gene Ontology, the Cell Ontology, the Protein Ontology, and so forth -- are once again playing an important role. In regard to species, on the other hand, matters are more complex. We provide a brief overview of recent proposals concerning the ontology of species, dealing with species as sets, classes and as collections, the views of Ernst Meyr, and mereological views.

The Universal Core (UCore) is a central element of the National Information Sharing Strategy that is supported by multiple U.S. Federal Government Departments, by the intelligence community, and by a number of other national and international institutions. The goal of the UCore initiative is to foster information sharing by means of an XML schema providing consensus representations for four groups of universally understood terms under the headings who, what, when, and where. We here describe a project to create an ontology-based supporting layer for UCore, entitled ‘Universal Core Semantic Layer’ (UCore SL), and describe how UCore SL can be applied to further UCore’s information sharing goals.

When the U.S. conducts warfare, elements of a force are drawn from different services and work together as a single team to accomplish an assigned mission. To achieve such unified action, it is necessary that the doctrines governing the actions of members of specific services be both consistent with and subservient to joint Doctrine. Because warfighting today increasingly involves not only live forces but also automated systems, unified action requires that information technology that is used in joint warfare must be aligned with joint doctrine. It requires also that the separate information systems used by the different elements of a joint force must be interoperable, in the sense that data and information that is generated by each element must be usable (understandable, processable) by all the other elements that need them. Currently, such interoperability is impeded by multiple inconsistencies among the different data and software standards used by warfighters. We describe here the on-going project of creating a Joint Doctrine Ontology (JDO), which uses joint doctrine to provide shared computer-accessible content valid for any field of military endeavor, organization, and information system. JDO addresses the two previously mentioned requirements of unified action by providing a widely applicable benchmark for use by developers of information systems that will both guarantee alignment with joint doctrine and support interoperability.

This paper presents an axiomatic formalization of a theory of top-level relations between three categories of entities: individuals, universals, and collections. We deal with a variety of relations between entities in these categories, including the sub-universal relation among universals and the parthood relation among individuals, as well as cross-categorial relations such as instantiation and membership. We show that an adequate understanding of the formal properties of such relations – in particular their behavior with respect to time – is critical for geographic information processing. The axiomatic theory is developed using Isabelle, a computational system for implementing logical formalisms. All proofs are computer verified and the computational representation of the theory is available online.

The analytical philosophy of the last hundred years has been heavily influenced by a doctrine to the effect that the key to the correct understanding of reality is captured syntactically in the ‘Fa’ (or, in more sophisticated versions, in the ‘Rab’) of standard first order predicate logic. Here ‘F’ stands for what is general in reality and ‘a’ for what is individual. Hence “f(a)ntology”. Because predicate logic has exactly two syntactically different kinds of referring expressions—‘F’, ‘G’, ‘R’, etc., and ‘a’, ‘b’, ‘c’, etc.—so reality must consist of exactly two correspondingly different kinds of entity: the general (properties, concepts) and the particular (things, objects). We describe the historical influence of this view, and also show how standard first-order predicate logic can be used for the logical formalization of a more adequate “six category ontology”, which recognizes, at the level of both particulars and universals, not only things or objects but also events and qualities.

We describe a strategy for integration of data that is based on the idea of semantic enhancement. The strategy promises a number of benefits: it can be applied incrementally; it creates minimal barriers to the incorporation of new data into the semantically enhanced system; it preserves the existing data (including any existing data-semantics) in their original form (thus all provenance information is retained, and no heavy preprocessing is required); and it embraces the full spectrum of data sources, types, models, and modalities (including text, images, audio, and signals). The result of applying this strategy to a given body of data is an evolving Dataspace that allows the application of a variety of integration and analytic processes to diverse data contents. We conceive semantic enhancement (SE) as a lightweight and flexible process that leverages the richness of the structured contents of the Dataspace without adding storage and processing burdens to what, in the intelligence domain, will be an already storage- and processing-heavy starting point. SE works not by changing the data to which it is applied, but rather by adding an extra semantic layer to this data. We sketch how the semantic enhancement approach can be applied consistently and in cumulative fashion to new data and data-models that enter the Dataspace.

The perceptual psychologist J. J. Gibson embraces a radically externalistic view of mind and action. We have, for Gibson, not a Cartesian mind or soul, with its interior theater of contents and the consequent problem of explaining how this mind or soul and its psychological environment can succeed in grasping physical objects external to itself. Rather, we have a perceiving, acting organism, whose perceptions and actions are always already tuned to the parts and moments, the things and surfaces, of its external environment. We describe how on this basis Gibson sought to develop a realist science of environments which will be ‘consistent with physics, mechanics, optics, acoustics, and chemistry’.

The remarks which follow are intended to address a certain apparent asymmetry as between German and Anglo-Saxon philosophy. Put most simply, it is clear to every philosopher moving backwards and forwards between the two languages that the translation of an Anglo-Saxophone philosophical text into German is in general a much easier task than is the translation of a German philosophical text into English. The hypothesis suggests itself immediately that this is so because English philosophical writings are in the main clear and intelligible, and therefore easy to translate. The texts of German philosophy, on the other hand, both classical and contemporary, seem in many cases to be marked by stylistic obscurities or idiosyncracies of a sort which make them not translatable in the strict sense at all.

We present an ontology of pain and of other pain-related phenomena, building on the definition of pain provided by the International Association for the Study of Pain (IASP). Our strategy is to identify an evolutionarily basic canonical pain phenomenon, involving unpleasant sensory and emotional experience based causally in localized tissue damage that is concordant with that experience. We then show how different variant cases of this canonical pain phenomenon can be distinguished, including pain that is elevated relative to peripheral trauma, pain that is caused neuropathically (thus with no necessary peripheral stimulus), and pain reports arising through deception either of self or of others. We describe how our approach can answer some of the objections raised against the IASP definition, and sketch how it can be used to support more sophisticated discrimination of different types of pain resulting in improved data analysis that can help in advancing pain research.

The Emotion Ontology is an ontology covering all aspects of emotional and affective mental functioning. It is being developed following the principles of the OBO Foundry and Ontological Realism. This means that in compiling the ontology, we emphasize the importance of the nature of the entities in reality that the ontology is describing. One of the ways in which realism-based ontologies are being successfully used within biomedical science is in the annotation of scientific research results in publicly available databases. Such annotation enables several objectives, including searching, browsing and cross-database data integration. A key benefit conferred by realismbased ontology is that suitably annotated research results are able to be aggregated and compared in a fashion that is based on the underlying reality that the science is studying. This has the potential of increasing the power of statistical analysis and meta-analysis in data-driven science. This aspect has been fruitfully exploited in the investigation of the functions of genes in molecular biology. Cognitive neuroscience uses functional neuroimaging to investigate the brain correlates of areas of mental functioning such as memory, planning and emotion. The use of functional neuroimaging to study affective phenomena such as the emotions is called ‘affective neuroscience’. BrainMap is the largest curated database of coordinates and metadata for studies in cognitive neuroscience, including affective neuroscience (Laird et al., 2005). BrainMap data is already classified and indexed using a terminology for classification, called the ‘Cognitive Paradigm Ontology’ (CogPO), that has been developed to facilitate searching and browsing. However, CogPO has been developed specifically for the BrainMap database, and the data are thus far not annotated to a realism-based ontology which would allow the discovery of interrelationships between research results across different databases on the basis of what the research is about. In this contribution, we describe ongoing work that aims to annotate affective neuroscience data, starting with the BrainMap database, using the Emotion Ontology. We describe our objectives and technical approach to the annotation, and mention some of the challenges.

In ancient times was known two kinds of physics. On one side there was the astronomy , which is characterized by the use of exact mathematical principles, on the other hand, there was the physics in the true sense of the word, a science, which coincides often with what we now call `metaphysics' . While astronomy has to do with the region of celestials and the imperishable, the physics is about the range of the sublunary, terrestrial things that come and go, and from their movements. The physicist is familiar with the nature of things, of which he speaks, and so he also understands the causes of their movements. It was not until Copernicus dared to equate the Earth to other planets that all physical events explain the same system to be dynamic postulates. This is still regarded as a commonplace of both philosophy and science of the natural world. I want to show in what follows that we now return from rather unexpected reasons the old dualistic view and we should no longer be guided by the sole prerogative of nachgalileischen physics.

How do we find what is clinically significant in the swarms of data being generated by today’s diagnostic technologies? As electronic records become ever more prevalent – and digital imaging and genomic, proteomic, salivaomics, metabalomics, pharmacogenomics, phenomics and transcriptomics techniques become commonplace – fdifferent clinical and biological disciplines are facing up to the need to put their data houses in order to avoid the consequences of an uncontrolled explosion of different ways of describing information. We describe a new strategy to advance the consistency of data in the dental research community. The strategy is based on the idea that existing systems for data collection in dental research will continue to be used, but proposes a methodology in which past, present and future data will be described using a consensus-based controlled structured vocabulary called the Ontology for Dental Research (ODR).