Classical Ontology Research Articles

Separability and Non-Individuality: Is It Possible to Conciliate (At Least A Form Of) Einstein’s Realism with Quantum Mechanics?

In this paper we argue that physical theories, including the most recent ones, even if only implicitly, talk of `objects' (or `things') of some sort (really, of several sorts), and question the logico-mathematical apparatus we still use to formulate them, taking into account what such theories presuppose about these entities. I shall point out that despite the discourse (or at least some discourses) goes in the direction of assuming that these quantum objects would be `new entities' of some kind, distinct from the traditional physical objects of classical physics, the logico-mathematical framework we use is still the old one, grounded on classical logic and set theory, which are committed to atavistic concepts based on individuals and distinguishable things, in complete disagreement with our present day conception of quanta. So, the use of such apparatus would impede us to be in complete agreement with the ontological commitment the theories of \textit{quanta} seem to propose. Thus, I move in the direction of joining those who try to question the `logic of quantum mechanics' from a different point of view, looking for a formal rationale for a new ontology. As a consequence of this move, we can revisit Einstein's ideas on physical reality and see that, from the perspective of considering a new kind of object, here termed `non-individuals', it is possible to sustain that they still obey some of Einstein's conditions for `physical realities', so that it will be possible to talk of a `principle of separability' in a sense which is not in complete disagreement with quantum mechanics. So, Einstein's departure from quantum mechanics might be softened at least concerning a form of his realism (locality still remains a challenge of course), for we guess that the incompatibility between quantum mechanics (field theories included) and some form of `separability' makes sense only if the objects of discourse are thought as `classical' objects, typical of classical ontology.

Aggregation operators for fuzzy ontologies

Fuzzy ontologies extend classical ontologies to allow the representation of imprecise and vague knowledge. Although a relatively important amount of work has been carried out in the field during the last years and they have been successfully used in several applications, several notions from fuzzy logic have not been considered yet in fuzzy ontologies. Among them are aggregation operators, mathematical functions used to fuse different pieces of information, which is a very common need. Some examples of aggregation operators are weighted sums, Ordered Weighting Averaging operators and fuzzy integrals.In this work, we integrate fuzzy ontologies and aggregation operators. As a theoretical formalism, we provide the syntax and semantics of a fuzzy Description Logic with fuzzy aggregation operators. We provide a reasoning algorithm for the family of operators that are representable using a Mixed Integer Linear Programming optimization problem. We also show how to encode some examples of aggregation operators using the language Fuzzy OWL 2.

Construction of fuzzy ontologies from fuzzy XML models

The success and proliferation of the Semantic Web depends heavily on construction of Web ontologies. However, classical ontology construction approaches are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. Therefore, great efforts on construction of fuzzy ontologies have been made in recent years. In particular, XML is imposing itself as a standard for representing and exchanging information on the Web, topics related to the modeling of fuzzy data have become very interesting in the XML data context. Therefore, constructing fuzzy ontologies from fuzzy XML data resources may make the existing fuzzy XML data upgrade to Semantic Web contents, and the constructed fuzzy ontologies may be useful for improving some fuzzy XML applications.This paper proposes a formal approach and an automated tool for constructing fuzzy ontologies from fuzzy XML data resources. Firstly, we propose a formal definition of fuzzy XML models (including the document structure fuzzy DTDs and the document content fuzzy XML documents). On this basis, we propose a formal approach for constructing fuzzy ontologies from fuzzy XML models, i.e., transforming a fuzzy XML model (including fuzzy DTD and fuzzy XML document) into a fuzzy ontology. Also, we give the proof of correctness of the construction approach, and provide a detailed construction example. Furthermore, we implement a prototype tool called FXML2FOnto, which can automatically construct fuzzy ontologies from fuzzy XML models. Finally, in order to show that the constructed fuzzy ontologies may be useful for improving some fuzzy XML applications, we focus on investigating how to reason on fuzzy XML models (e.g., conformance, inclusion, and equivalence) based on the constructed fuzzy ontologies, and it turns out that the reasoning tasks of fuzzy XML models can be checked by means of the reasoning mechanism of fuzzy ontologies.

Construction of Fuzzy Ontologies from Fuzzy UML Models

Abstract The success and proliferation of the Semantic Web depends heavily on construction of Web ontologies. However, classical ontology construction approaches are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. Therefore, great efforts on construction of fuzzy ontologies have been made in recent years. In this paper, we propose a formal approach and develop an automated tool for constructing fuzzy ontologies from fuzzy UML models. Firstly, we propose formalization methods of fuzzy UML models and fuzzy ontologies, where fuzzy UML models and fuzzy ontologies can be represented and interpreted by their respective formal definitions and semantic interpretation methods. Then, we propose an approach for constructing fuzzy ontologies from fuzzy UML models, i.e., transforming fuzzy UML models (including the structure and instance information of fuzzy UML models) into fuzzy ontologies. Furthermore, following the proposed approach, we implement ...

From classical ontology to who magazine: digital whoness: identity, privacy and freedom in the cyberworld (capurro, r., et al; 2013) [book review

This book poses a range of important questions. Who ? as distinct from what ? are we? Can the self be digitized? Will or can the algorithm replace the soul and the psyche? What are the intercultural determinants of private/public ethics? How is the interplay between private and public spheres of experience to be enacted? Where is the fine line between trust and control? How is trust to be engendered in a cyber world that enables ?self-determined world-sharing with selected others? when in the background ?service-providing masters of digital cybernetics? loom large? According to the authors, privacy and publicness are not ?properties of things, data or persons, but rather ascriptions dependent upon the specific social and cultural context.?

JOINING GÖDEL AND ZADEH FUZZY LOGICS IN FUZZY DESCRIPTION LOGICS

Ontologies have succeeded as a knowledge representation formalism in many domains of application. Nevertheless, they are not suitable to represent vague or imprecise information. To overcome this limitation, several extensions to classical ontologies based on fuzzy logic have been proposed. Even though different fuzzy logics lead to fuzzy ontologies with very different logical properties, the combined use of different fuzzy logics has received little attention to date. This paper proposes a fuzzy extension of the Description Logic [Formula: see text] — the logic behind the ontology language OWL 2 — that joins Gödel and Zadeh fuzzy logics. We analyze the properties of the new fuzzy Description Logic in order to provide guidelines to ontology developers to exploit the best features of each fuzzy logic. The proposal also considers degrees of truth belonging to a finite set of linguistic terms rather than numerical values, thus being closer to real experts' reasonings. We prove the decidability of the combined logic by presenting a reasoning preserving procedure to obtain a crisp representation for it. This result is generalized to offer a similar reduction that can be applied when any other finite t -norms, t -conorms, negations or implications are considered in the logic.

Web Ontologies as Renewal of Classical Philosophical Ontology

AbstractDo Web devices (addresses, tags, networks, and the rest) have counterparts in classical ontology? Yes, but they allow us also to introduce more refined distinctions. In addition, their dynamic use could inspire a dynamic reconception of classical ontology. In the process of making explicit ontological types, different types can be undistinguished at the first step (considered as “floating types”) to be defined only in a further step, one in which their function as distinguishers of other kinds of entities has to be made explicit. The fact that the ontological import of some node in a network of tags and addresses could evolve with the transformation of the network can most easily find an interpretation in this dynamic conception of ontology.

A Further Review of the Incompatibility between Classical Principles and Quantum Postulates

The traditional “realist” conception of physics, according to which human concepts, laws and theories can grasp the essence of a reality in our absence, seems incompatible with quantum formalism and it most fruitful interpretation. The proof rests on the violation by quantum mechanical formalism of some fundamental principles of the classical ontology. We discuss if the conception behind Einstein’s idea of a reality in our absence, could be still maintained and at which price. We conclude that quantum mechanical formalism is not formulated on those terms, leaving for a separated paper the discussion about the terms in which it could be formulated and the onto-epistemological implications it might have.

Revisiting Consistency Conditions for Quantum States of Systems on Closed Timelike Curves: An Epistemic Perspective

There has been considerable recent interest in the consequences of closed timelike curves (CTCs) for the dynamics of quantum mechanical systems. A vast majority of research into this area makes use of the dynamical equations developed by Deutsch, which were developed from a consistency condition that assumes that mixed quantum states uniquely describe the physical state of a system. We criticise this choice of consistency condition from an epistemic perspective, i.e., a perspective in which the quantum state represents a state of knowledge about a system. We demonstrate that directly applying Deutsch's condition when mixed states are treated as representing an observer's knowledge of a system can conceal time travel paradoxes from the observer, rather than resolving them. To shed further light on the appropriate dynamics for quantum systems traversing CTCs, we make use of a toy epistemic theory with a strictly classical ontology due to Spekkens and show that, in contrast to the results of Deutsch, many of the traditional paradoxical effects of time travel are present.

An Introduction to Nicolai Hartmann’s Critical Ontology

Nicolai Hartmann contributed significantly to the revitalization of the discipline of ontology in the early twentieth century. Developing a systematic, post-Kantian critical ontology ‘this side’ of idealism and realism, he subverted the widespread impression that philosophy must either exhaust itself in foundationalist epistemology or engage in system-building metaphysical excess. This essay provides an introduction to Hartmann’s approach in light of the recent translation of his early essay ‘How is Critical Ontology Possible?’ (1923) In it Hartmann criticizes both the pretensions of epistemology as well as the principal errors of classical ontology, and he proposes a series of correctives that lead to his development of a highly original and elaborate stratified categorial ontology. This introduction explains the most important errors of the ‘old’ ontology, his correctives to them, and further fleshes out these correctives with reference to his mature ontological work.

Decision making with a fuzzy ontology

Knowledge mobilisation is a transition from the prevailing knowledge management technology that has been widely used in industry for the last 20 years to a new methodology and some innovative methods for knowledge representation, formation and development and for knowledge retrieval and distribution. Knowledge mobilisation aims at coming to terms with some of the problems of knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the knowledge mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone.

Special issue on fuzzy ontologies and fuzzy markup language applications

Latest research on formal methods for knowledge representation based on semantic web technologies witnessed how ontologies have become a fundamental and critical component for developing applications in different real world scenarios. Indeed, ontologies formally model application domains to enable reuse of knowledge and allow people and software agents to share a common understanding of the structure of information. The body of a knowledge modeled through an ontological approach is based on the conceptualization idea, i.e., an abstract and simplified view of the knowledge related to given application scenario. However, it is widely pointed out that classical ontology model is not sufficient to deal with imprecise and vague knowledge strongly characterizing some real world applications. Soft computing techniques can enhance ontological knowledge representation by providing methods for directly dealing with imprecision and vagueness. Indeed, fuzzy set theory may extend the conventional ontology idea with a collection of fuzzy or vague terms like ‘‘creamy’’, ‘‘hot’’, ‘‘large’’, for which a clear and precise definition is not possible. In this scenario, the fuzzy markup language (FML) represents an important result because it allows fuzzy scientists to express their ‘‘imprecise’’ ideas in abstract and interoperable way by improving their productivity and, at the same time, increasing the average quality of their works. The objective of this special issue is to highlight an ongoing research on fuzzy and FML approaches for knowledge semantic representation based on ontologies, as well as their applications on various domains. This volume contains seven papers that consider different aspects of research on fuzzy ontologies and FML. The first four papers describe the applications exploiting fuzzy theory and ontology. Updating Generalized Association Rules with Evolving Fuzzy Taxonomies by WenYang Lin, Ja-Hwung Su, and Ming-Cheng Tseng proposes an algorithm for mining generalized association rules with fuzzy taxonomic structures where the taxonomy may change as time passes; as shown by their empirical evaluations, the proposed algorithms yield high performances even in high degree of taxonomy evolution. Crowdsourcing techniques to create a fuzzy subset of SNOMED CT for semantic tagging of medical documents by David T. Parry and Tsung-Chun Tsai describes an approach to identifying subsets of medical knowledge contained in the SNOMED CT dictionary via a crowdsourcing technique. The research aims to assist clinicians in coding small freetext documents such as radiology reports. Fuzzy Ontologies-based User Profiles applied to enhance e-Learning Activities by Mateus Ferreira-Satler, Francisco P. Romero, Victor H. Menendez-Dominguez, Alfredo Zapata and Manuel E. Prieto shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-Learning environments. Decision making with a fuzzy ontology by Christer Carlsson, Matteo Brunelli and Jozsef Mezei shows how soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy G. Acampora (&) Department of Computer Science, University of Salerno, Salerno, Italy e-mail: gacampora@unisa.it

Incorporation of Fuzzy Theory with Heavyweight Ontology and Its Application on Vague Information Retrieval for Decision Making

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

D eL orean: A reasoner for fuzzy OWL 2

Today, there is a growing interest in the development of knowledge representations able to deal with uncertainty, which is a very common requirement in real world applications. Despite the undisputed success of ontologies, classical ontologies are not suitable to deal with uncertainty and, consequently, several extensions with fuzzy logic and rough logic, among other formalisms, have been proposed. In this article we describe D eL orean 2, the first ontology reasoner that supports fuzzy extensions of the standard languages OWL and OWL 2. In a strict sense, D eL orean is not a reasoner but a translator from fuzzy rough ontology languages ( GZ SROIQ ( D ) ) into classical ontology languages ( SROIQ ( D ) ) . This allows using classical (widely available) Description Logic inference engines to reason with the representation resulting from the transformation. We describe the main features of the application: evolution, functionality, architecture, graphical interface, input language, and implementation details.

Reasoning and change management in modular fuzzy ontologies

The growing emphasis on complexity concerns for ontologies has attracted significant interest from both the researcher’s and the practitioner’s communities in modularization techniques as a way to decrease the complexity of managing huge ontologies. On the other hand, it has been widely pointed out that classical ontologies are not appropriate to deal with imprecise and vague knowledge, which is inherent to several real world domains. In order to handle these types of knowledge, some fuzzy extensions of classical ontologies are presented, yielding fuzzy ontologies. In this paper, we integrate modular ontologies with fuzzy ontologies, i.e., the notion of modular fuzzy ontologies is presented. Furthermore, we present an infrastructure for the representation of and reasoning with modular fuzzy ontologies based on distributed fuzzy description logics.

On the Meaning of the Constant “c” in Modern Physics

In modern physics, the constant “c” plays a twofold role. On the one hand, “c” is the well known velocity of light in an empty Minkowskian space–time, on the other hand “c” is a characteristic number of Special Relativity that governs the Lorentz transformation and its consequences for the measurements of space–time intervals. We ask for the interrelations between these two, at first sight different meanings of “c”. The conjecture that the value of “c” has any influence on the structure of space–time is based on the operational interpretation of Special Relativity, which uses light rays for measurements of space–time intervals. We do not follow this way of reasoning but replace it by a more realistic approach that allows to show that the structure of the Minkowskian space–time can be reconstructed already on the basis of a restricted classical ontology (Mittelstaedt, Philosophie der Physik und der Raum-Zeit, Mannheim: BI-Wissenschaftsverlag, 1988 and Mittelstaedt, Kaltblutig: Philosophie von einem rationalen Standpunkt, Stuttgart: S. Hirzel Verlag, pp. 221–240, 2003), and that without any reference to the propagation of light. However, the space–time obtained in this way contains still an unknown constant. We show that this constant agrees numerically with “c” but that it must conceptually clearly be distinguished from the velocity of light. Hence, we argue for a clear distinction between the two faces of “c” and for a dualism of space–time and matter.

A Fuzzy Expert System for Diabetes Decision Support Application

An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.

A Type-2 Fuzzy Ontology and its Application to Personal Diabetic Diet Recommendation

It has been widely pointed out that classical ontology is not sufficient to deal with imprecise and vague knowledge for some real-world applications like personal diabetic-diet recommendation. On the other hand, fuzzy ontology can effectively help to handle and process uncertain data and knowledge. This paper proposes a novel ontology model, which is based on interval type-2 fuzzy sets (T2FSs), called type-2 fuzzy ontology (T2FO), with applications to knowledge representation in the field of personal diabetic-diet recommendation. The T2FO is composed of 1) a type-2 fuzzy personal profile ontology ( type-2 FPPO); 2) a type-2 fuzzy food ontology ( type-2 FFO); and 3) a type-2 fuzzy-personal food ontology (type-2 FPFO). In addition, the paper also presents a T2FS-based intelligent diet-recommendation agent ( IDRA), including 1) T2FS construction; 2) a T2FS-based personal ontology filter; 3) a T2FS-based fuzzy inference mechanism; 4) a T2FS-based diet-planning mechanism; 5) a T2FS-based menu-recommendation mechanism; and 6) a T2FS-based semantic-description mechanism. In the proposed approach, first, the domain experts plan the diet goal for the involved diabetes and create the nutrition facts of common Taiwanese food. Second, the involved diabetics are requested to routinely input eaten items. Third, the ontology-creating mechanism constructs a T2FO, including a type-2 FPPO, a type-2 FFO, and a set of type-2 FPFOs. Finally, the T2FS-based IDRA retrieves the built T2FO to recommend a personal diabetic meal plan. The experimental results show that the proposed approach can work effectively and that the menu can be provided as a reference for the involved diabetes after diet validation by domain experts.

(Re)Conceptualising mnemonic technology in light of hermeneutic ontology

This paper lays out the background and foreground of how we come to conceptualise our world by providing an analysis of the notion of ontology. It argues that there are three conceptually separable discourses that can be identified in the Western philosophical tradition: ‘classical ontology’, ‘noetic ontology’, and ‘hermeneutic ontology’. Through the lenses of these three general ontologies, the regional ontology of information is explicated and is then further expanded upon in line with hermeneutic ontology’s emphasis on the social–historical contingency of human existence. Through this, it is argued that the mnemonic capacities and attitudes of human beings, and the relationship of these capacities and attitudes towards the formation of these beings, should not be considered in isolation from the development of different mnemonic technologies for the inscription, storage, organisation, retrieval, and dissemination of information. This argument is presented by considering the historical development and implementation of the primarily linguistic technologies of orality, literacy, print culture, and the emerging digital culture.

Fluctuation-dissipation theorem provides a simple analytical relationship between post-stress heart rate recovery and heart rate variability during the stress

capabilities. The intent is not to suggest that an agent-based framework is “the” format for an executable ontology layer; the experience with classic ontologies suggests that it is impossible to produce a definitive knowledge representation tool. It is fully expected that other researches will develop similar types of tools, using different modeling paradigms. However, we believe that an ABMF demonstrates a robust, evolvable approach and will provide an essential translational step toward the goal of having as many steps as possible of the discovery process be automated. Eventually, this type of architecture would allow the automated generation of models that can be picked through by the researcher, providing a truly evolutionary solution to the synthetic aspect of biomedical research.