Barry Smith

The central hypothesis of the collaboration between Language and Computing (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is that the methodology and conceptual rigor of a philosophically inspired formal ontology greatly benefits application ontologies. To this end r®, L&C’s ontology, which is designed to integrate and reason across various external databases simultaneously, has been submitted to the conceptual demands of IFOMIS’s Basic Formal Ontology (BFO). With this project we aim to move beyond the level of controlled vocabularies to yield an ontology with the ability to support reasoning applications. Our general procedure has been the implementation of a meta-ontological definition space in which the definitions of all the concepts and relations in LinKBase® are standardized in a framework of first-order logic. In this paper we describe how this standardization has already led to an improvement in the LinKBase® structure that allows for a greater degree of internal coherence than ever before possible. We then show the use of this philosophical standardization for the purpose of mapping external databases to one another, using LinKBase® as translation hub, with a greater degree of success than possible hitherto. We demonstrate how this offers a genuine advance over other application ontologies that have not submitted themselves to the demands of philosophical scrutiny. LinKBase® is one of the world’s largest applications-oriented medical domain ontologies, and BFO is one of the world’s first philosophically driven reference ontologies. The collaboration of the two thus initiates a new phase in the quest to solve the so-called “Tower of Babel”.

Every domain-specific ontology must use as a framework some upper-level ontology which describes the most general, domain-independent categories of reality. In the present paper we sketch a new type of upper-level ontology, which is intended to be the basis of a knowledge modelling language GOL (for: 'General Ontological Language'). It turns out that the upper- level ontology underlying standard modelling languages such as KIF, F-Logic and CycL is restricted to the ontology of sets. Set theory has considerable mathematical power and great flexibility as a framework for modelling different sorts of structures. At the same time it has the disadvantage that sets are abstract entities (entities existing outside the realm of time, space and causality), and thus a set-theoretical framework should be supplemented by some other machinery if it is to support applications in the ripe, messy world of concrete objects. In the present paper we partition the entities of the real world into sets and urelements, and then we introduce several new ontological relations between these urelements. In contrast to standard modelling and representation formalisms, the concepts of GOL provide a machinery for representing and analysing such ontologically basic relations.

Every domain-specific ontology must use as a framework some upper-level ontology which describes the most general domain-independent categories of reality. In the present paper we sketch a new type of upper-level ontology, and we outline an associated knowledge modelling language called GOL – for: General Ontological Language. It turns out that the upper-level ontology underlying well-known standard modelling languages such as KIF, F-Logic and CycL is restricted to the ontology of sets. In a set theory which allows Urelements, however, there will be ontological relations between these Urelements which the set-theoretic machinery cannot capture. In contrast to standard modelling and representation formalisms, GOL provides a machinery for representing and analysing such ontologically basic relations. GOL is thus a genuine extension of KIF and of similar languages. In GOL entities are divided into sets and Urelements, the latter being divided in their turn into individuals and universals. Foremost among the individuals are things or substances, tropes or moments, and situoids: entities containing facts as components.

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’ is often used by philosophers as a synonym for ‘metaphysics’ (literally: ‘what comes after the Physics’), a term which was used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. The term ‘ontology’ (or ontologia) was itself coined in 1613, independently, by two philosophers, Rudolf Göckel (Goclenius), in his Lexicon philosophicum and Jacob Lorhard (Lorhardus), in his Theatrum philosophicum. The first occurrence in English recorded by the OED appears in Bailey’s dictionary of 1721, which defines ontology as ‘an Account of being in the Abstract’.

Recent work on the quality assurance of the Gene Ontology (GO, Gene Ontology Consortium 2004) from the perspective of both linguistic and ontological organization has made it clear that GO lacks the kind of formalism needed to support logic-based reasoning. At the same time it is no less clear that GO has proven itself to be an excellent terminological resource that can serve to combine together a variety of biomedical database and information systems. Given the strengths of GO, it is worth investigating whether, by overcoming some of its weaknesses from the point of view of formal-ontological principles, we might not be able to enhance a version of GO which can come even closer to serving the needs of the various communities of biomedical researchers and practitioners. It is accepted that clinical and bioinformatics need to find common ground if the results of data-intensive biomedical research are to be harvested to the full. It is also widely accepted that no single method will be sufficient to create the needed common framework. We believe that the principles-based approach to life-science data integration and knowledge representation must be one of the methods applied. Indeed in dealing with the ontological representation of carcinomas, and specifically of colon carcinomas, we have established that, had GO (and related biomedical ontologies) followed some of the basic formal-ontological principles we have identified (Smith et al. 2004, Ceusters et al. 2004), then the effort required to navigate successfully between clinical and bioinformatics systems would have been reduced. We point here to the sources of ontologically-related errors in GO, and also provide arguments as to why and how such errors need to be resolved.

We propose the beginnings of a general theory of environments, of the parts or regions of space in which organisms live and move. We draw on two sources: on the one hand on recent work on the ontology of space; and on the other hand on work by ecological scientists on concepts such as territory, habitat, and niche. An environment is in first approximation a volume of space; it is a specific habitat, location, or site that is suitable or adequate for given purposes (of foraging, resting, hunting, breeding, nesting, grooming) in the life of an organism or group of organisms. This spatial notion of environment can be drawn closer to biological and ecological science by taking account of the pertinent physical attributes realized within given spatial regions.

The Gene Ontology is an important tool for the representation and processing of information about gene products and functions. It provides controlled vocabularies for the designations of cellular components, molecular functions, and biological processes used in the annotation of genes and gene products. These constitute three separate ontologies, of cellular components), molecular functions and biological processes, respectively. The question we address here is: how are the terms in these three separate ontologies related to each other? We use statistical methods and formal ontological principles as a first step towards finding answers to this question.

Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (b) they do this in terms of the types and type-level relationships described in these ontologies. While much attention has been devoted to (1), work on (2), which is the topic of this paper, is comparatively rare. Using Referent Tracking as basis, we describe a technical data wrangling strategy which consists in creating for each dataset a template that, when applied to each particular record in the dataset, leads to the generation of a collection of Referent Tracking Tuples (RTT) built out of unique identifiers for the entities described by means of the data items in the record. The proposed strategy is based on (i) the distinction between data and what data are about, and (ii) the explicit descriptions of portions of reality which RTTs provide and which range not only over the particulars described by data items in a dataset, but also over these data items themselves. This last feature allows us to describe particulars that are only implicitly referred to by the dataset; to provide information about correspondences between data items in a dataset; and to assert which data items are unjustifiably or redundantly present in or absent from the dataset. The approach has been tested on a dataset collected from patients seeking treatment for orofacial pain at two German universities and made available for the NIDCR-funded OPMQoL project.

An accurate classification of bacteria is essential for the proper identification of patient infections and subsequent treatment decisions. Multi-Locus Sequence Typing (MLST) is a genetic technique for bacterial classification. MLST classifications are used to cluster bacteria into clonal complexes. Importantly, clonal complexes can serve as a biological species concept for bacteria, facilitating an otherwise difficult taxonomic classification. In this paper, we argue for the inclusion of terms relating to clonal complexes in biomedical ontologies.

Can there be a theory-free experience? And what would be the object of such an experience. Drawing on ideas set out by Husserl in the “Crisis” and in the second book of his “Ideas”, the paper presents answers to these questions in such a way as to provide a systematic survey of the content and ontology of common sense. In the second part of the paper Husserl’s ideas on the relationship between the common-sense world (what he called the ‘life-world’) and the world of physical theory are subjected to a critical evaluation. The relation of Husserl’s ideas to current work in folk psychology and naive physics and to the direct realism of J. J. Gibson are also treated.

Intelligent defence support systems are confronted with the need to manage ever-increasing floods of data in a way that raises significant challenges because the data are described and presented using different terminologies and formats. How, on this basis, is it possible to reach a common understanding of the information content of these data among people and software agents? How is it possible to ensure that domain knowledge is reused in consistent fashion in a way that makes this information available for integration and analysis? How can we support the identification, selection, composition, and orchestration of services based on such diverse data providing homogeneous support by a service-oriented architecture? This collection is devoted to the use of ontologies to answer questions such as these.

The desideratum of semantic interoperability has been intensively discussed in medical informatics circles in recent years. Originally, experts assumed that this issue could be sufficiently addressed by insisting simply on the application of shared clinical terminologies or clinical information models. However, the use of the term ‘ontology’ has been steadily increasing more recently. We discuss criteria for distinguishing clinical ontologies from clinical terminologies and information models. Then, we briefly present the role clinical ontologies play in two multicentric research projects. Finally, we discuss the interactions between these different kinds of knowledge representation artifacts and the stakeholders involved in developing interoperational real-world clinical applications. We provide ontology engineering examples from two EU-funded projects.

Hintergrund: Biomedizinische Ontologien existieren unter anderem zur Integration von klinischen und experimentellen Daten. Um dies zu erreichen ist es erforderlich, dass die fraglichen Ontologien von einer großen Zahl von Benutzern zur Annotation von Daten verwendet werden. Wie können Ontologien das erforderliche Maß an Benutzerfreundlichkeit, Zuverlässigkeit, Kosteneffektivität und Domänenabdeckung erreichen, um weitreichende Akzeptanz herbeizuführen? Material und Methoden: Wir konzentrieren uns auf zwei unterschiedliche Strategien, die zurzeit hierbei verfolgt werden. Eine davon wird von SNOMED CT im Bereich der Medizin vertreten, die andere im Bereich der Biologie und Biomedizin von der OBO Foundry. Es soll aufgezeigt werden, wie die Verpflichtung zu speziellen Kriterien der Ontologieentwicklung die Nützlichkeit und Effektivität der Ontologien positiv beeinflusst, indem die Pflege der terminologischen Systeme und ihre Interoperabilität vereinfacht werden. Ergebnisse: SNOMED CT und die OBO Foundry unterscheiden sich grundlegend in ihren Ansätzen und Zielen. Unabhängig davon kann jedoch ein allgemeiner Trend zur strengeren Formalisierung und Fokussierung auf Interoperabilität zwischen unterschiedlichen Domänen und ihren Repräsentationen beobachtet werden.

In the management of biomedical data, vocabularies such as ontologies and terminologies (O/Ts) are used for (i) domain knowledge representation and (ii) interoperability. The knowledge representation role supports the automated reasoning on, and analysis of, data annotated with O/Ts. At an interoperability level, the use of a communal vocabulary standard for a particular domain is essential for large data repositories and information management systems to communicate consistently with one other. Consequently, the interoperability benefit of selecting a particular O/T as a standard for data exchange purposes is often seen by the end-user as a function of the number of applications using that vocabulary (and, by extension, the size of the user base). Furthermore, the adoption of an O/T as an interoperability standard requires confidence in its stability and guaranteed continuity as a resource.

In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the ontology within the ACGT project thus far.

Biomedical terminologies are focused on what is general, Electronic Health Records (EHRs) on what is particular, and it is commonly assumed that the step from the one to the other is unproblematic. We argue that this is not so, and that, if the EHR of the future is to fulfill its promise, then the foundations of both EHR architectures and biomedical terminologies need to be reconceived. We accordingly describe a new framework for the treatment of both generals and particulars in biomedical information systems that is designed: 1) to provide new opportunities for the sharing and management of data within and between healthcare institutions, 2) to facilitate interoperability among different terminology and record systems, and thereby 3) to allow new kinds of reasoning with biomedical data.

The theory of speech acts put forward by Adolf Reinach in his "The A Priori Foundations of the Civil Law" of 1913 rests on a systematic account of the ontological structures associated with various different sorts of language use. One of the most original features of Reinach's account lies in hIs demonstration of how the ontological structure of, say, an action of promising or of commanding, may be modified in different ways, yielding different sorts of non-standard instances of the corresponding speech act varieties. The present paper is an attempt to apply this idea of standard and modified instances of ontological structures to the realm of judgement and cognition, and thereby to develop a Reinachian theory of how intentionality is mediated through language in acts of thinking and speaking.

The theory of speech acts put forward by Adolf Reinach in his "The A Priori Foundations of the Civil Law" of 1913 rests on a systematic account of the ontological structures associated with various different sorts of language use. One of the most original features of Reinach's account lies in hIs demonstration of how the ontological structure of, say, an action of promising or of commanding, may be modified in different ways, yielding different sorts of non-standard instances of the corresponding speech act varieties. The present paper is an attempt to apply this idea of standard and modified instances of ontological structures to the realm of judgement and cognition, and thereby to develop a Reinachian theory of how intentionality is mediated through language in acts of thinking and speaking.

The objective of this research programme is to contribute to the establishment of the emerging science of Formal Ontology in Information Systems via a collaborative project involving researchers from a range of disciplines including philosophy, logic, computer science, linguistics, and the medical sciences. The re­searchers will work together on the construction of a unified formal ontology, which means: a general framework for the construction of ontological theories in specific domains. The framework will be constructed using the axiomatic-deductive method of modern formal ontology. It will be tested via a series of applications relating to on-going work in Leipzig on medical taxonomies and data dictionaries in the context of clinical trials. This will lead to the production of a domain-specific ontology which is designed to serve as a basis for applications in the medical field.

I shall begin with the assumption that there are, among our mental acts. some which stand in direct contact with ohjects in the material world. The aim of this paper will he to clarify and to draw out certain implications of this somewhat trivial assumption, and ultimately to say something about the ontological structure of those of our acts which effect the function of bringing us into contact with material acts which serve. as we might say, as the most external points of consciousness which touch the objects consciousness is trying to grasp. Amongst material objects I shall include not only material things such as tables.

We propose a view of vagueness as a semantic property of names and predicates. All entities are crisp, on this semantic view, but there are, for each vague name, multiple portions of reality that are equally good candidates for being its referent, and, for each vague predicate, multiple classes of objects that are equally good candidates for being its extension. We provide a new formulation of these ideas in terms of a theory of granular partitions. We show that this theory provides a general framework within which we can understand the relation between vague terms and concepts and the corresponding crisp portions of reality. We also sketch how it might be possible to formulate within this framework a theory of vagueness which dispenses with the notion of truth-value gaps and other artifacts of more familiar approaches. Central to our approach is the idea that judgments about reality involve in every case (1) a separation of reality into foreground and background of attention and (2) the feature of granularity. On this basis we attempt to show that even vague judgments made in naturally occurring contexts are not marked by truth-value indeterminacy. We distinguish, in addition to crisp granular partitions, also vague partitions, and reference partitions, and we explain the role of the latter in the context of judgments that involve vagueness. We conclude by showing how reference partitions provide an effective means by which judging subjects are able to temper the vagueness of their judgments by means of approximations.

Abstract: What follows is a contribution to the field of user modeling for adaptive teaching and learning programs especially in the medical field. The paper outlines existing approaches to the problem of extracting user information in a form that can be exploited by adaptive software. We focus initially on the so-called stereotyping method, which allocates users into classes adaptively, reflecting characteristics such as physical data, social background, and computer experience. The user classifications of the stereotyping method are however ad hoc and unprincipled, and they can be exploited by the adaptive system only after a large number of trials by various kinds of users. We argue that the remedy is to create a database of user ontologies from which readymade taxonomies can be derived in such a way as to enable associated software to support a variety of different types of users.

The truthmaker theory rests on the thesis that the link between a true judgment and that in the world to which it corresponds is not a one-to-one but rather a one-to-many relation. An analogous thesis in relation to the link between a singular term and that in the world to which it refers is already widely accepted. This is the thesis to the effect that singular reference is marked by vagueness of a sort that is best understood in supervaluationist terms. In what follows we show that the supervaluationist approach to singular reference, when wedded to the truthmaker idea, yields a framework of surprising power, which offers a uniform set of solutions to a range of problems regarding identity, reference and knowledge, problems which have hitherto been dealt with on an ad hoc basis.

Research has indicated that microRNAs (miRNAs), a special class of non-coding RNAs (ncRNAs), can perform important roles in different biological and pathological processes. miRNAs’ functions are realized by regulating their respective target genes (targets). It is thus critical to identify and analyze miRNA-target interactions for a better understanding and delineation of miRNAs’ functions. However, conventional knowledge discovery and acquisition methods have many limitations. Fortunately, semantic technologies that are based on domain ontologies can render great assistance in this regard. In our previous investigations, we developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), to provide the community with common data elements and data exchange standards in the miRNA research. This paper describes (1) our continuing efforts in the OMIT ontology development and (2) the application of the OMIT to enable a semantic approach for knowledge capture of miRNA-target interactions.

Identification of non-coding RNAs (ncRNAs) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncRNA data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a precisely defined ncRNA controlled vocabulary, which can fill a specific and highly needed niche in unification of ncRNA biology.

Plants from a handful of species provide the primary source of food for all people, yet this source is vulnerable to multiple stressors, such as disease, drought, and nutrient deficiency. With rapid population growth and climate uncertainty, the need to produce crops that can tolerate or resist plant stressors is more crucial than ever. Traditional plant breeding methods may not be sufficient to overcome this challenge, and methods such as highOthroughput sequencing and automated scoring of phenotypes can provide significant new insights. Ontologies are essential tools for accessing and analysing the large quantities of data that come with these newer methods. As part of a larger project to develop ontologies that describe plant phenotypes and stresses, we are developing a plant disease extension of the Infectious Disease Ontology (IDOPlant). The IDOPlant is envisioned as a reference ontology designed to cover any plant infectious disease. In addition to novel terms for infectious diseases, IDOPlant includes terms imported from other ontologies that describe plants, pathogens, and vectors, the geographic location and ecology of diseases and hosts, and molecular functions and interactions of hosts and pathogens. To encompass this range of data, we are suggesting inOhouse ontology development complemented with reuse of terms from orthogonal ontologies developed as part of the Open Biomedical Ontologies (OBO) Foundry. The study of plant diseases provides an example of how an ontological framework can be used to model complex biological phenomena such as plant disease, and how plant infectious diseases differ from, and are similar to, infectious diseases in other organism.