Explicit Ontologies Research Articles

Introduction

Many divination systems are epistemologically justified according to an explicit ontology: results are attributed to the work of an agent (gods, spirits) or to a cosmic principle (as in the Chinese conceptqi). Analytically, we can thus distinguish between divination based on ‘agentive ontology’, which raises the possibility of deception by gods or spirits, and ‘calculatory ontology’, which understands verdicts as calculations based on fixed principles. The relationship between explicit ontology and epistemic affordance, including the circumstances under which divination is subject to ontological explanation, suggests large-scale comparative questions concerning the wider socio-political and economic correlates of agentive and calculatory systems. These are exemplified in this special issue by the divergences between divination systems in the Greco-Roman world, in Han China, and among the Nuosu.

Reflective Ontology and Intuitive Credibility in Chinese Six Lines Prediction

Any form of divination can be intuitively compelling without the need for ontological elaboration, but practices like Chinese six lines prediction involve complex ontological accounts, raising the question of what effect this has on divination’s authority and persuasiveness. The explicit ontology of six lines prediction appears to make it especially persuasive, because it provides a coherent model of epistemology and causation that is readily comparable to scientific observation and description based on constant principles. Meanwhile, six lines prediction’s mathematical character adds to its intuitive authority. By relying on a predetermined system of correlates, it creates the impression that the diviner is not the source of the divinatory result or its interpretation. This likely allows six lines prediction to flourish in an environment in which it is officially classified as ‘superstition’.

The Ontology of Landscapes

The paper aims at an analysis of the concept of landscape, offering an ontological approach. Our claim is that such a perspective is hardly ever assumed in philosophical aesthetics, even if theories of landscape appreciation are in fact based on tacit ontological assumptions. We argue that having an explicit ontology of landscapes is important, for aesthetic theories of their appreciation are often attacked in terms of the problems caused by their tacit ontologies. Therefore, we sketch an “Experience Ontology” that serves as an alternative to the ontologies implied in the two best known aesthetic approaches to landscapes. We contend that a landscape should not be conceived of as an object or view but as a way of experiencing one’s surroundings, and we argue that our theory is not only free from the shortcomings of the two dominant theories but that it also corresponds better to everyday intuitions.

Knowledge-based semantic discretisation using data mining techniques

Certain data mining techniques can be applied only on discretised data. Various studies show significant improvement in certain data mining techniques, when applied on discretised data rather than continuous data. Discretisation methods based on statistical techniques are inadequate in capturing and exploiting the knowledge inherent in data and context of study. To overcome this limitation, we propose a novel knowledge-based semantic discretisation method using data mining techniques, in which discretisation is done based on semantic data. Semantic data is domain knowledge inherent in the data and context of the study. Unlike semantic data mining, no explicit ontology associated with the data for semantic discretisation. Therefore, it's a challenging task to identify, capture, interpret and exploit the semantic data for semantic discretisation. This study presents the novel concept of semantic discretisation. The effectiveness of the proposed methodology is shown by applying it on Pima Indian diabetes dataset.

Ontology and human rights

This paper examines the question of whether human rights are related to ontology. It examines perspectives on this question from human rights theories in the Western and African traditions of philosophy and defends the thesis that a good account of human rights requires an explicit ontology of the human, and that taking this seriously engenders divergent conclusions about what rights are. It then proceeds to claim that the African Charter on Human and Peoples’ Rights adds substantive features to the International Bill of Human Rights, and that the Charter expresses Kwame Gyekye’s ontology of the human being.

Knowledge based Semantic Discretization using Data Mining Techniques

Certain data mining techniques can be applied only on discretised data. Various studies show significant improvement in certain data mining techniques, when applied on discretised data rather than continuous data. Discretisation methods based on statistical techniques are inadequate in capturing and exploiting the knowledge inherent in data and context of study. To overcome this limitation, we propose a novel knowledge-based semantic discretisation method using data mining techniques, in which discretisation is done based on semantic data. Semantic data is domain knowledge inherent in the data and context of the study. Unlike semantic data mining, no explicit ontology associated with the data for semantic discretisation. Therefore, it's a challenging task to identify, capture, interpret and exploit the semantic data for semantic discretisation. This study presents the novel concept of semantic discretisation. The effectiveness of the proposed methodology is shown by applying it on Pima Indian diabetes dataset.

Applying novel technologies and methods to inform the ontology of self-regulation

Self-regulation is a broad construct representing the general ability to recruit cognitive, motivational and emotional resources to achieve long-term goals. This construct has been implicated in a host of health-risk behaviors, and is a promising target for fostering beneficial behavior change. Despite its clear importance, the behavioral, psychological and neural components of self-regulation remain poorly understood, which contributes to theoretical inconsistencies and hinders maximally effective intervention development. We outline a research program that seeks to define a neuropsychological ontology of self-regulation, articulating the cognitive components that compose self-regulation, their relationships, and their associated measurements. The ontology will be informed by two large-scale approaches to assessing individual differences: first purely behaviorally using data collected via Amazon's Mechanical Turk, then coupled with neuroimaging data collected from a separate population. To validate the ontology and demonstrate its utility, we will then use it to contextualize health risk behaviors in two exemplar behavioral groups: overweight/obese adults who binge eat and smokers. After identifying ontological targets that precipitate maladaptive behavior, we will craft interventions that engage these targets. If successful, this work will provide a structured, holistic account of self-regulation in the form of an explicit ontology, which will better clarify the pattern of deficits related to maladaptive health behavior, and provide direction for more effective behavior change interventions.

The e3value Ontology for Value Networks: Current State and Future Directions

ABSTRACTMeeting changing customer demands and business opportunities in a connected world makes it necessary for organizations to constantly innovate by means of value-creating collaborations. The goal of value modeling is to support the exploration of new business models from an economic point of view. The e3value approach to value modeling is based on an explicit ontology and supported by a graphical tool. This paper provides a structured overview and evaluation of e3value, and discusses two important issues. The first issue concerns the difference between a value co-creation perspective and an exchange value perspective. It shows that with some extensions, e3value can support both. The second issue is model quality. It argues that an ontology is not complete without model quality features and, as far as e3value is concerned, proposes to use the notion of “value cycle” as a soundness feature and as a replacement of the scenario concept.

Merleau-Ponty the Metaphysician: The Living Body as a Plurality of Forces

ABSTRACT We should not read Merleau-Ponty's Phenomenology of Perception as an implicit or oblique ontology (as some have) but, rather, as a work of fundamental and explicit ontology continuous with The Structure of Behavior. Merleau-Ponty's masterwork presents an entirely new metaphysics built around the notion of Form: the body–world system comprises a plurality of forces striving for an equilibrium that is continually overcome. This new interpretation changes how we understand the living body and consciousness in Merleau-Ponty's work, as we see afresh how his new metaphysics displaces the older metaphysics built on the dualisms of subject/object and mind/body.

Merleau-Ponty the Metaphysician: The Living Body as a Plurality of Forces

ABSTRACT We should not read Merleau-Ponty's Phenomenology of Perception as an implicit or oblique ontology (as some have) but, rather, as a work of fundamental and explicit ontology continuous with The Structure of Behavior. Merleau-Ponty's masterwork presents an entirely new metaphysics built around the notion of Form: the body–world system comprises a plurality of forces striving for an equilibrium that is continually overcome. This new interpretation changes how we understand the living body and consciousness in Merleau-Ponty's work, as we see afresh how his new metaphysics displaces the older metaphysics built on the dualisms of subject/object and mind/body.

Frame-based ontological view for semantic integration

Semantic integration is crucial for successful collaboration between heterogeneous information systems. Traditional ontology-driven approaches rely on the availability of explicit ontologies. However, in most application domains, this prerequisite cannot be met. In order to address this issue, this paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to an ontological view concept. To explicitly and formally specify the ontological views, a Frame-based Ontological view Specification Language (FOSL) is proposed. This language is based on the frame knowledge representation paradigm and uses XML as the encoding. The ontological view driven semantic integration can be achieved based on the specifications. A proof-of-concept prototype environment has been implemented to achieve semantic integration based on ontological views specified with FOSL.

Concept determination as part of the development of knowledge in caring science

The purpose of this article is to highlight concept determination as part of the development of knowledge in caring science, by describing Eriksson's model of concept determination. Concepts belong to and are developed in science, and it is through concepts that reality is shaped. Concepts and language are closely related, and Gadamer's guiding thought is that language constitutes the middle where I and the world, join together. It is by its very activity of thinking that the meaning is to be heard, and Gadamer emphasizes that the being that can be understood is language and points to a universal ontological structure against the fundamental nature of what is allowing to be understood. The first outlines of the model of concept determination are described as a research design for the development of the care process model. In developing the model of concept determination, the intent has been to fill a void in the international caring science literature, where no model is sufficiently comprehensive to meet the requirement for a model from a humanistic hermeneutic perspective with roots in an explicit ontology and ethos. Eriksson's model of concept determination includes both an ontological and a contextual determination. Concept determination is the main concept in Eriksson's model and includes concept formation and concept analysis. The starting point of concept determination is a hermeneutic epistemology developed in a scientific tradition of caring. The model of concept determination opens itself to versatility in determining concepts and provides a nuanced picture of the concept in question, while the whole-part-whole thinking simultaneously leads to a deeper understanding of the multifaceted caring reality and the current object of knowledge. By constantly returning to the what-questions, the course of events will continue and conceptual determination moves around the substance towards a deeper understanding of the core.

The need for methodological development within qualitative clinical caring research

The need for methodological development within qualitative clinical caring research

Adding Deleuze to the mix

In this article I will suggest ways in which adding the French philosopher Gilles Deleuze to the mix can complement and extend the 4EA approach to cognitive science. In the first part of the paper, I will show how the Deleuzean tripartite ontological difference (virtual/intensive/actual) can provide an explicit ontology for dynamical systems theory. The second part will take these ontological notions and apply them to three areas of concern to the 4EA approaches: (a) the Deleuzean concept of the virtual will clarify the ontological status of perceptual capacity as sensorimotor skill; (b) the Deleuzean concept of “intensive individuation” will clarify the ontological status of the genesis of perceptually guided behavior; (c) the Deleuzean critique of confusing the actual and the virtual will enable us to intervene in the realism/idealism debate. These aspects will not be addressed sequentially but will be interwoven into an unfolding argument.

Instance-based domain ontological view creation towards semantic integration

In many domains today there are very limited explicit ontologies established for implementing information systems. Traditional ontology-driven semantic integration approaches cannot be directly applied in integrating these information systems. Usually, the information systems have schemas, a type of formal information model, for their information repositories which to some extent imply the semantics of the information. Each schema actually reflects a specific view of the domain conceptualization. This paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to the ontological view concept. It proposes to use ontological views to address the challenge of semantic integration. The proposed approach adopts the schemas to create local ontological views, uses data instances of the information systems to discover semantic relationships between the concepts within the ontological views, and builds a domain ontological view based on the discovered equivalence mappings. It applies the hierarchical clustering technique on the data instances and, in the further analysis, uses the clusters to reduce the cost of processing a large amount of data. The matching of concept properties is based on the probability distribution of the data instances. The experimental results have demonstrated the effectiveness of this approach.

Ontology Development for Designing and Managing Dynamic Business Process Networks

Recent advances in flexible process design and deployment technologies, such as web services and flexible workflow systems, promise the development of flexible intra- and inter-organizational business process networks with potential economic benefits. However, exploiting this potential requires the development of scalable process-management technologies that provide a consistent viewpoint and common language (for describing properties of the process network) to all stakeholders involved in its management. Current approaches to managing such networks requires one to use a babel of languages (in the formal sense) at different levels of abstraction. The development of explicit process ontologies is one of the potentially viable approaches to provide an unified view. In this paper, we discuss the need for process ontologies, propose a task-based ontological framework synthesizing recent research in the fields of AI planning and software engineering, and illustrate the need to link declarative and procedural process representations. We illustrate the use of this ontological framework for managing processes in developing applications for integrating information from disparate information sources in multiple domains. Further, based on this experience, we discuss potential benefits and areas for future research.

A semantic framework and software design to enable the transparent integration, reorganization and discovery of natural systems knowledge

I present a conceptualization that attempts to unify diverse representations of natural knowledge while providing a workable computational framework, based on current semantic web theory, for developing, communicating, and running integrated simulation models. The approach is based on a long-standing principle of scientific investigation: the separation of the ontological character of the object of study from the semantics of the observation context, the latter including location in space and time and other observation-related aspects. I will show how current Knowledge Representation theories coupled with the object-oriented paradigm allow an efficient integration through the abstract model of a domain, which relates to the idea of aspect in software engineering. This conceptualization allows us to factor out two fundamental causes of complexity and awkwardness in the representation of knowledge about natural system: (a) the distinction between data and models, both seen here as generic knowledge sources; (b) the multiplicity of states in data sources, handled through the hierarchical composition of independently defined domain objects, each accounting for all states in one well-known observational dimension. This simplification leaves modelers free to work with the bare conceptual bones of the problem, encapsulating complexities connected to data format, and scale. I will then describe the design of a software system that implements the approach, referring to explicit ontologies to unambiguously characterize the semantics of the objects of study, and allowing the independent definition of a global observation context that can be redefined as required. I will briefly discuss applications to multi-scale, multi-paradigm modeling, intelligent database design, and web-based collaboration.

Combining ontologies and peer‐to‐peer technologies for inter‐organizational knowledge management

PurposeThe purpose of the paper is to review the characteristics of systems that combine P2P technology with explicit ontologies and assess the benefits of these technologies for inter‐organizational knowledge management.Design/methodology/approachWe characterize existing technologies with respect to a number of aspects that are relevant to knowledge management on a technical level. We further provide an example of an existing system and categorize it according to the aspects.FindingsWe conclude that ontology‐based P2P systems are in general beneficial for distributed knowledge management systems and that the design of such systems can be guided using the aspects we distinguish.Originality/valueThe paper presents the first attempt to rigorously identify and discuss the design space of ontology‐based P2P systems.

What Is Psychology About? Toward An Explicit Ontology

Commentators have criticized psychology's overemphasis on method and its simultaneous neglect of questions regarding the subject matter and purpose of psychology. This article summarizes four problems that have resulted from the privileging of method, and in each case illustrates how an explicit ontology provides at least partial solutions to these problems. This article also suggests three metatheoretical assumptions based on the thinking of William James that would allow for the establishment of an explicit ontology and that would allow for psychological entities per se to be studied without the threat of biological or other kinds of reductionism. Finally, concerns that may arise in the formation of an explicit ontology are briefly addressed.

Introduction to the special issue on ontologies in agent systems

It is now more than ten years since researchers in the US Knowledge Sharing Effort envisaged a future where complex systems could be built by combining knowledge and services from multiple knowledge bases and the first agent communication language, KQML, was proposed (Neches et al., 1991). This model of communication, based on speech acts, a declarative message content representation language and the use of explicit ontologies defining the domains of discourse (Genesereth & Ketchpel, 1994), has become widely recognised as having great benefits for the integration of disparate and distributed information sources to form an open, extensible and loosely coupled system. In particular, this idea has become a key tenet in the multi-agent systems research community.