Roles remain nebulous entities, notwithstanding their extensive interdisciplinary research. This paper argues through a meta-ontological conceptual tool of grounding that there are three key facets of roles: a role position, a role specification, and a role potential. A foundational perspective on roles can be specified by “role choices” as to which facet of roles is primary. Role choices are illustrated with theories of roles that are built in compliance with four well-known upper ontologies: GFO, DOLCE, BFO, and UFO. The relationship (...) between such three facets of roles and the GFO-based three kinds of roles (relational, processual, and social) is closely examined. These three facets are also comparatively studied from linguistic (e.g. ‘have a role’ versus ‘play a role’) and methodological (realism versus conceptualism regarding ontology design) perspectives. Furthermore, the family resemblance view of roles as “epistemic trackers” is proposed: the general notion of role is merely (partially) unified by its three facets and helps to keep track of some entity with respect to its role-related aspects. Finally, defining characteristics of roles in conceptual modeling are considered in terms of the three-facet theory. This work provides the grist for future practical development of an ontological module for generic role representation. (shrink)

The collection and classification of data into meaningful categories is a key step in the process of knowledge making. In the life sciences, the design of data discovery and integration tools has relied on the premise that a formal classificatory system for expressing a body of data should be grounded in consensus definitions for classifications. On this approach, exemplified by the realist program of the Open Biomedical Ontologies Foundry, progress is maximized by grounding the representation and aggregation of data on (...) settled knowledge. We argue that historical practices in systematic biology provide an important and overlooked alternative approach to classifying and disseminating data, based on a principle of coordinative rather than definitional consensus. Systematists have developed a robust system for referring to taxonomic entities that can deliver high quality data discovery and integration without invoking consensus about reality or “settled” science. (shrink)

Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be (...) constructed in such a way that their terms are seen as referring to what we call universals or types in reality. As we show, Merrill’s critique is of little relevance to the success of our realist project, since it not only reveals no actual errors in our work but also criticizes views on universals that we do not in fact hold. However, it nonetheless provides us with a valuable opportunity to clarify the realist methodology, and to show how some of its principles are being applied, especially within the framework of the OBO (Open Biomedical Ontologies) Foundry initiative. (shrink)

In “Ontological realism: Methodology or misdirection?” I offered a detailed critique of the position referred to as “realism” taken by Barry Smith and Werner Ceusters. This position is claimed to serve as the basis for a “realist methodology” that they seek to impose on the development of scientific ontologies, particularly within the biomedical sciences. Here, in part responding to a reply to those criticisms by Smith and Ceusters, I return the focus to an examination of fundamental incoherencies in this realist (...) approach and propose an alternative that is amenable to much of what Smith and Ceusters hope to accomplish. And I sketch what I believe is needed to advance ontology theory and practice in the sciences. (shrink)

Philosophers frequently struggle with the relation of metaphysics to the everyday world, with its practical value, and with its relation to empirical science. This paper distinguishes several different models of the relation between philosophical ontology and applied (scientific) ontology that have been advanced in the history of philosopy. Adoption of a strong participation model for the philosophical ontologist in science is urged, and requirements and consequences of the participation model are explored. This approach provides both a principled view and justification (...) of the role of the philosophical ontologist in contemporary empirical science as well as guidelines for integrating philosophers and philosophical contributions into the practice of science. (shrink)

Bio-ontologies are digital frameworks for handling biological and biomedical data. They consist of theoretical entities and relations with explicitly defined logical structures and precise definitions, whose purpose is to provide a shared language for representing information to be distributed and integrated across diverse scientific contexts. It is tempting to view bio-ontologies as clear and formal expressions of a scientific community’s ontological commitments about their domain of inquiry, and to view their integration as tantamount to the metaphysical unification of science that (...) some philosophers have envisaged. However, I argue that the local, practical, social and technological factors that influence their design prevent us from straightforwardly reading metaphysical conclusions from them. I discuss these complications and suggest how they can be overcome, revealing more general lessons for the development of a well-founded scientific metaphysics. (shrink)

In this article, we advocate the use of “epistemic” ontologies, i.e., systems of categories representing our knowledge of the world, rather than the world directly. We first expose a metaphysical framework based on a dual mental and physical realism, which underpins the development of these epistemic ontologies. To this end, we refer to the theories of intentionality and representation established within the school of Franz Brentano at the turn of the 20th century and choose to rehabilitate the notion of a (...) ‘representation object’, as theorized by Kasimir Twardowski. We therefore propose that the categories of epistemic ontologies correspond to ‘general representation objects’. Secondly, we apply these proposals to the treatment of technical artefacts, material qualities of objects and events (notably as a continuation of our previous work on events). This leads us to sketch out a foundational epistemic ontology. (shrink)

A survey of the similarities and differences between BFO and DOLCE, and of the mutual interactions between Nicola Guarino and Barry Smith.

Ontological realism is a philosophical stance that provides a definitional framework for ontologies and is referred to by various applied ontologists. From a computer science perspective, ontologies are often associated with formal languages for the representation of ontologies like the Web Ontology Language (OWL). It has, however, not been made explicit how the realist framework is related to the representation formalism. We analyse how the representational units of OWL can be used for modelling realist ontologies. While OWL is sufficiently close (...) to the realist framework of ontologies to describe them, there are categories in OWL that are alien to realist ontologies or duplicate categories in realist ontologies. This clarification allows separating talk about ontologies in general from talk about their specific representation. (shrink)

Many recent accounts of the ontology of groups, institutions, and practices have touched upon the normative or deontic dimensions of social reality (e.g., social obligations, claims, permissions, prohibitions, authority, and immunity), as distinct from any specifically moral values or obligations. For the most part, however, the ontology of such socio-deontic phenomena has not received the attention it deserves. In what sense might a social obligation or a claim exist? What is the ontological status of such an obligation (e.g., is it (...) an entity in its own right)? And how do people come to have social obligations or permissions in the first place? In this dissertation, I argue that such social-deontic phenomena can be accounted for ontologically in terms of the existence of shared prescriptive representational content that is backed by collectively held dispositions to monitor for compliance, and to punish (sanction, blame, chide, look unfavorably upon) those who fail to comply. (shrink)

Big data is opening new angles on old questions about scientific progress. Is scientific knowledge cumulative? If yes, how does it make progress? In the life sciences, what we call the Consensus Principle has dominated the design of data discovery and integration tools: the design of a formal classificatory system for expressing a body of data should be grounded in consensus. Based on current approaches in biomedicine and systematic biology, we formulate and compare three types of the Consensus Principle: realist, (...) contextual-best, and coordinative. Contrasted with the realist program of the Open Biomedical Ontologies Foundry, we argue that historical practices in systematic biology provide an important and overlooked alternative based on coordinative consensus. Systematists have developed a robust system for referring to taxonomic entities that can deliver high quality data discovery and integration without invoking consensus about reality or “settled” science. (shrink)

The construction of complex ontologies can be facilitated by adapting existing vocabularies. There is little clarity and in fact little consensus as to what modifications of vocabularies are necessary in order to re-engineer them into ontologies. In this paper we present a method that provides clear steps to follow when re-engineering a thesaurus. The method makes use of top-level ontologies and was derived from the structural differences between thesauri and ontologies as well as from best practices in modeling, some of (...) which have been advocated in the biomedical domain. We illustrate each step of our method with examples from a re-engineering case study about agricultural fertilizers based on the AGROVOC thesaurus. Our method makes clear that re-engineering thesauri requires far more than just a syntactic conversion into a formal language or other easily automatable steps. The method can not only be used for re-engineering thesauri, but does also summarize steps for building ontologies in general, and can hence be adapted for the re-engineering of other types of vocabularies or terminologies. (shrink)