On the role of domain ontologies in the design of domain-specific visual modeling langages

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user’s perspective, the language’s modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community

Cognitive context and arguments from ontologies for learning

The deployment of learning resources on the web by different experts has resulted in the accessibility of multiple viewpoints about the same topics. In this work we assume that learning resources are underpinned by ontologies. Different formalizations of domains may result from different contexts, different use of terminology, incomplete knowledge or conflicting knowledge. We define the notion of cognitive learning context which describes the cognitive context of an agent who refers to multiple and possibly inconsistent ontologies to determine the truth of a proposition. In particular we describe the cognitive states of ambiguity and inconsistency resulting from incomplete and conflicting ontologies respectively. Conflicts between ontologies can be identified through the derivation of conflicting arguments about a particular point of view. Arguments can be used to detect inconsistencies between ontologies. They can also be used in a dialogue between a human learner and a software tutor in order to enable the learner to justify her views and detect inconsistencies between her beliefs and the tutor’s own. Two types of arguments are discussed, namely: arguments inferred directly from taxonomic relations between concepts, and arguments about the necessary an

Ontology-based model abstraction

In recent years, there has been a growth in the use of reference conceptual models to capture information about complex and critical domains. However, as the complexity of domain increases, so does the size and complexity of the models that represent them. Over the years, different techniques for complexity management in large conceptual models have been developed. In particular, several authors have proposed different techniques for model abstraction. In this paper, we leverage on the ontologically well-founded semantics of the modeling language OntoUML to propose a novel approach for model abstraction in conceptual models. We provide a precise definition for a set of Graph-Rewriting rules that can automatically produce much-reduced versions of OntoUML models that concentrate the models’ information content around the ontologically essential types in that domain, i.e., the so-called Kinds. The approach has been implemented using a model-based editor and tested over a repository of OntoUML models

An Ontological Solution to the Mind-Body Problem

I argue for an idealist ontology consistent with empirical observations, which seeks to explain the facts of nature more parsimoniously than physicalism and bottom-up panpsychism. This ontology also attempts to offer more explanatory power than both physicalism and bottom-up panpsychism, in that it does not fall prey to either the ‘hard problem of consciousness’ or the ‘subject combination problem’, respectively. It can be summarized as follows: spatially unbound consciousness is posited to be nature’s sole ontological primitive. We, as well as all other living organisms, are dissociated alters of this unbound consciousness. The universe we see around us is the extrinsic appearance of phenomenality surrounding—but dissociated from—our alter. The living organisms we share the world with are the extrinsic appearances of other dissociated alters. As such, the challenge to artificially create individualized consciousness becomes synonymous with the challenge to artificially induce abiogenesis

The question concerning the environment: a Heideggerian approach to environmental philosophy : a thesis presented in partial fulfillment of the requirements for the degree of Master of Arts in Philosophy at Massey University

This thesis will engage with the thinking of Martin Heidegger in order to show that our environmental problems are the necessary consequences of our way of 'knowing' the world. Heidegger questions the abstract, theoretical approach that the Western tradition has to 'knowledge', locating 'knowledge' in the human 'subject', an interior self, disengaged from and standing over against the other-than-human world, as external 'object'. Such an approach denies a voice to the other-than-human in the construction of 'knowledge'. Heidegger maintains that we are not a disembodied intellect, but rather we are finite, self-interpreting beings, embodied in a physical, social and historical context, for whom things matter. In view of this, he discards traditional notions of 'knowledge', in favour of understanding and interpretation. Accordingly, he develops what can be called a dialectical ontology, whereby we come to understand and interpret ourselves and other beings in terms of our involved interactions. This involved understanding acknowledges the participation of other-than-human beings in constructing an interpretation of the world, giving them a voice. Following Heidegger's way of thinking, I suggest that by developing an ontological-ethic, a way of dwelling-in-the-world based on a responsive engagement with other-than- human entities, we can disclose a world that makes both the other-than- human and humanity possible

OntoWebML: A Knowledge Base Management System for WSML Ontologies

This paper addresses the topic of defining a knowledge base system for representing and managing ontologies according to the WSMO conceptual model. We propose a software engineering approach to this problem, by implementing: (i) the relational model for ontologies that corresponds to the WSML representation of WSMO; (ii) the usage of a well known Web modeling language called WebML, extended by a set of new components for exploiting ontological contents in Web services and Web applications design; and (iii) a Web-based content management system for ontologies editing and reasoning, implemented using the abovementioned software engineering approach